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Cisco email security boxes can be rooted by... an email
Criminals are exploiting a critical Cisco Secure Email Gateway flaw that can turn a malicious email into root access. The vulnerability, tracked as CVE-2026-76461, carries a 9.8 CVSS score and affects physical and virtual Secure Email Gateway appliances regardless of their configuration. Cisco says there are no workarounds, so patching is the only fix. The bug lies in how Cisco's AsyncOS software handles incoming email. An attacker doesn't need to log in: they can send a booby-trapped message through a vulnerable gateway and, if the exploit works, run commands as root. Which is not exactly what you want from the box tasked with keeping nasty emails out. Cisco's Product Security Incident Response Team said it became aware of active exploitation in September, although the networking giant hasn't said who is behind the attacks, how long they have been going on, or how many organizations have been compromised. Cisco uncovered the bug while resolving a Technical Assistance Center support case. Signs suggest at least some Cisco cloud customers were caught up in the attacks. Cisco said it investigated devices belonging to its Secure Email Cloud service and directly contacted customers whose appliances showed indicators of possible compromise. It is now carrying out remediation and recovery work and says all of its Secure Email Cloud devices have been upgraded to AsyncOS 16.5.0-780. Admins running their own appliances have a little more work to do. Cisco recommends checking logs for signs of suspicious activity, but warns that finding nothing doesn't necessarily mean the system is clean. Once attackers have root access, Cisco says they could tamper with the logs and cover their tracks. Admins are also being told to check network and firewall logs for anything unusual, rather than relying on the gateway itself for answers. For virtual appliances suspected of being compromised, Cisco's recovery advice is fairly drastic: preserve the forensic evidence, deploy a fresh VM running fixed software, rebuild the configuration, and rotate credentials and cryptographic material. Cisco has fixed the bug in AsyncOS releases 15.5.5-014, 16.0.4-302 and 16.5.0-780, with customers strongly encouraged to move to the latter. There's still a decent-sized target pool out there. The Shadowserver Foundation was tracking more than 400 Cisco Secure Email Gateway appliances exposed to the internet as of Monday The flaw has also landed in CISA's Known Exploited Vulnerabilities catalog, with US federal civilian agencies ordered to remediate it by September 17. CVE-2026-76461 comes less than a year after attackers exploited another critical AsyncOS flaw, CVE-2025-20393, to break into Cisco Secure Email Gateway appliances and install persistence mechanisms. That bug eventually scored a perfect 10. For anyone still running an affected gateway, the message is fairly simple: the box designed to inspect hostile email can itself be pwned by one; attackers are already doing it, and there is no workaround to hide behind. ®
theregister.comSep 15, 2026extracted
Swiss court sentences 52-year-old Ukrainian ransomware dev to nearly 13 years in the cooler
A Swiss court has sentenced a 52-year-old Ukrainian ransomware developer to 12 years and nine months in prison for his role in attacks on companies including Stadler Rail. Zurich District Court found that the man developed LockerGoga, MegaCortex, and Nefilim, but was not the mastermind behind the operations. He also received a ten-year ban from Switzerland. The judgment is not final and can be appealed. He had been held in pretrial detention since October 2021 and consistently denied knowing that his software was being used for criminal purposes. He said the source code found at his home in Basel-Landschaft came from his consulting work for an unidentified IT security client. The court rejected that explanation because extortion messages were also found among his data, SWI reported. The ransomware developer was also found guilty of playing a key role in high-profile ransomware attacks, including the one that hit Stadler Rail in 2020 [PDF]. Not to be confused with the more recent attack on the rolling stock manufacturer – that one was claimed by Everest – the earlier breach occurred in May 2020. At the time, Stadler Rail did not use the word "ransomware," but said the attack involved malware, that it "most likely led to a data leak," and that "the offenders tried to extort a large amount of money," threatening to leak the files if the ransom was not paid. As it did following this year's incident, Stadler refused to pay. The 2020 Nefilim ransom demand was reportedly $6 million. The court also found that he played a key role in attacks on HVAC company Meier Tobler and software company Crealogix. In September 2022, Zurich prosecutors reported that a suspect had been arrested in Basel-Landschaft in October 2021 on suspicion of money laundering and data corruption. The statement accused the perpetrators of involvement in attacks on more than 1,800 individuals and institutions across 71 countries, causing estimated losses of several hundred million Swiss francs. The same law enforcement action in 2021 led to the identification of other alleged members of the three ransomware operations, none of whom were named. Volodymyr Tymoshchuk was formally indicted in the US last year and was described by prosecutors as the mastermind of all three ransomware crews. Unlike many others, Tymoshchuk has not yet been arrested, but is on the FBI's most wanted list, with an $11 million bounty placed on the information that could lead to his arrest or conviction, or that of other key leaders. He was allegedly responsible for attacks on at least 250 companies, including the infamous Norsk Hydro attack in 2019. ®
theregister.comSep 15, 2026extracted
Ukrainian lawyer's second career as a Conti coder earns him 4 years behind bars
SECURITY Watch out: Apple timepiece can grab snippets of conversation without both speakers' consentWar is peace. Freedom is slavery. Privacy is surveillance SYSTEMS d-Matrix drinks the Nvidia Kool-Aid with NVLink Fusion and MGX rack designsAI infrastructure startup joins Qualcomm, Arm, Marvell, Amazon, Fujitsu, and MediaTek as NVLink true believers ai and ml Anthropic reveals fourth likely crime committed by its AIClaude's Felony Bench rap sheet is now as long as OpenAI's SYSTEMS Samsung to help fortify OpenAI's semiconductor supply chainSemiconductor supply chains are hard, but Samsung offers OpenAI relief in many forms spanning compute and memory AI+ML Google DeepMind rises above the AI scrum with genome atlasSee, AI can be used for good ... or at the very least, a useful distraction from the bad Security Russians are posing as Signal support to launch phishing attacksPLUS: US takes down Iranian propaganda sites; Marketing company asks 'Why Do We Have Your Information?' And more! Security Microsoft patches failed to fix on-prem SharePoint, which is now under zero-day attackPLUS: China upgrades smartphone surveillance tools; Ring eases anti-snooping stance; and more Black Hat and DEF CON DEF CON Franklin project enlists hackers to harden critical infrastructureVoting village reports have been so successful, says Jeff Moss, that the whole of DEF CON will now be included Security EQT buys majority share in Swiss cybersecurity biz AcronisWent at equivalent of $3.5B+ valuation for entire firm, though portion sold not specified Malware Month Ten years since the first corp ransomware, Mikko Hyppönen sees no end in sightOn the plus side, infosec's a good bet for a long, stable career Shopify extends lifeline to Tailwind as vibe coding erodes web dev platform's bottom lineAcquisition gives open source CSS framework 'a stable long-term home' Switzerland tests a FOSS escape route from Microsoft 365Swiss Army sticks a knife in American cloud apps with its own FOSS push Feel peak Windows was 7? You might like Kumander LinuxDebian and Xfce – solid, sensible choices – with a pretty skin Canonical shuttering some of its legacy chat channelsThe Ubuntu Pastebin went in June, IRC gets demoted next Audacity audio-editing app no longer looks like it's from the early 2000sThe FOSS tool for audio editing has a fresh coat of paint, and new features to boot Haiku OS rises / Beta 6 sails open web / Virtual winds fly fastA real alternative to running some kind of FOSS Unix clone
theregister.comSep 11, 2026extracted
Ubuntu 24.04.5 LTS release patches security bugs across ten flavors
Ubuntu 24.04.5 LTS release patches security bugs across ten flavors Canonical shipped Ubuntu 24.04.5 LTS, bundling security updates and fixes for high-severity bugs into new installation media for the “Noble Numbat” release. Anyone installing fresh now gets those corrections baked in from the start, cutting the batch of updates that would normally follow setup. The point release covers more than the desktop and server editions. Nine other flavors, including Kubuntu, Xubuntu, Ubuntu MATE, Ubuntu Studio, and Edubuntu, also moved to version 24.04.5, each carrying its own release notes for flavor-specific changes. Canonical built this release around security corrections and stability fixes, the priorities that matter most for an LTS version users expect to leave alone for years. Support timelines matter here more than the version bump itself. Ubuntu Desktop, Ubuntu Server, Ubuntu Cloud, and Ubuntu Core get five years of maintenance from the original 24.04 LTS release date, not from this point release. The other flavors get three years. Anyone tracking end-of-life dates for planning purposes should count from the initial 24.04 launch, and anyone who needs coverage past that window can add Expanded Security Maintenance on top. Existing 22.04 LTS users do not need to do anything to get the fixes. Update Manager will offer the automatic upgrade path to 24.04.5, and Canonical says that path, like all Ubuntu version upgrades, stays free. The release note names no CVEs or bug IDs. Administrators who need to confirm specific patches against a compliance requirement have to check the linked release notes instead. For anyone weighing whether to reimage machines now or just let existing installs update on their own schedule, the difference is minor: the fixes reach both paths, just at different times. Reimaging with 24.04.5 media saves a round of post-install downloads. Waiting costs nothing except the number of packages the machine happens to fetch on the next update cycle. The support clock keeps counting either way.
helpnetsecurity.comSep 11, 2026extracted
ShinyHunters expose 6.4M in attack on medical supplier McKesson
SECURITY Watch out: Apple timepiece can grab snippets of conversation without both speakers' consentWar is peace. Freedom is slavery. Privacy is surveillance SYSTEMS d-Matrix drinks the Nvidia Kool-Aid with NVLink Fusion and MGX rack designsAI infrastructure startup joins Qualcomm, Arm, Marvell, Amazon, Fujitsu, and MediaTek as NVLink true believers ai and ml Anthropic reveals fourth likely crime committed by its AIClaude's Felony Bench rap sheet is now as long as OpenAI's SYSTEMS Samsung to help fortify OpenAI's semiconductor supply chainSemiconductor supply chains are hard, but Samsung offers OpenAI relief in many forms spanning compute and memory AI+ML Google DeepMind rises above the AI scrum with genome atlasSee, AI can be used for good ... or at the very least, a useful distraction from the bad Security Russians are posing as Signal support to launch phishing attacksPLUS: US takes down Iranian propaganda sites; Marketing company asks 'Why Do We Have Your Information?' And more! Security Microsoft patches failed to fix on-prem SharePoint, which is now under zero-day attackPLUS: China upgrades smartphone surveillance tools; Ring eases anti-snooping stance; and more Black Hat and DEF CON DEF CON Franklin project enlists hackers to harden critical infrastructureVoting village reports have been so successful, says Jeff Moss, that the whole of DEF CON will now be included Security EQT buys majority share in Swiss cybersecurity biz AcronisWent at equivalent of $3.5B+ valuation for entire firm, though portion sold not specified Malware Month Ten years since the first corp ransomware, Mikko Hyppönen sees no end in sightOn the plus side, infosec's a good bet for a long, stable career Shopify extends lifeline to Tailwind as vibe coding erodes web dev platform's bottom lineAcquisition gives open source CSS framework 'a stable long-term home' Switzerland tests a FOSS escape route from Microsoft 365Swiss Army sticks a knife in American cloud apps with its own FOSS push Feel peak Windows was 7? You might like Kumander LinuxDebian and Xfce – solid, sensible choices – with a pretty skin Canonical shuttering some of its legacy chat channelsThe Ubuntu Pastebin went in June, IRC gets demoted next Audacity audio-editing app no longer looks like it's from the early 2000sThe FOSS tool for audio editing has a fresh coat of paint, and new features to boot Haiku OS rises / Beta 6 sails open web / Virtual winds fly fastA real alternative to running some kind of FOSS Unix clone
theregister.comSep 10, 2026extracted
The Machine With Many Faces: Post-Exploitation Identity Misuse in SPIFFE/SPIRE
This research demonstrates post-exploitation techniques that could allow an attacker with root access on a compromised Kubernetes node to misuse an open standard and reference implementation for machine identity known as SPIFFE/SPIRE to impersonate co-located workloads and harvest SPIFFE Verifiable Identity Documents (SVIDs). We show how the trust assumption at the core of every machine-identity system — that the node is trusted — collapses once an attacker obtains root on that node. Unit 42 has not observed this technique exploited in the wild. The Secure Production Identity Framework for Everyone (SPIFFE)/the SPIFFE Runtime Environment (SPIRE) is widely deployed in Kubernetes and cloud-native environments to replace long-lived secrets with short-lived, cryptographically verifiable workload identities. Our research shows how an attacker with root can spoof the Linux control group (cgroup) information the SPIRE agent uses during workload attestation. This tricks the agent into issuing a co-located workload's SVID to an attacker-controlled process. As part of this research, we developed Spooffe, an open-source tool that defenders can use to test whether an attacker with administrative access could manipulate cgroup metadata to retrieve co-located workload identities and assess the resulting identity area of impact. When designing threat models for SPIFFE/SPIRE, organizations should assume that root-level access to a node grants access to all cryptographic identities scoped to it. We recommend performing the following activities to reduce exposure: Harden nodes Restrict root access Prohibit privileged containers, host access Minimize reliance on weak selectors Palo Alto Networks customers are better protected from the threats described here through the following products and services: If you think you might have been compromised or have an urgent matter, contact the Unit 42 Incident Response team. SPIFFE is an open standard for machine identity designed to solve the “Secret Zero” problem — the challenge of securely introducing the initial secret required to bootstrap trust — by replacing long-lived secrets with short-lived workload identities. When deployed correctly, SPIFFE enforces strong identity boundaries between workloads. However, these guarantees rely on a core assumption shared by all identity systems that the underlying node is trusted. If an attacker gains root access to a node, they can interact with identity mechanisms to retrieve all identities authorized to that compromised node. Our research explores how attackers can exploit root access to harvest workload identities from a compromised node. In this post, we lay the groundwork by explaining machine identity and how SPIFFE establishes and verifies trust in cloud-native environments. We then demonstrate workload impersonation through selector spoofing. Finally, we introduce Spooffe, a tool we built to automate the extraction of these workload identities (SVIDs). Note to readers: If you’re already familiar with SPIFFE/SPIRE concepts and architecture, you can jump directly to Workload Attestation and How the Agent Attests the Workload sections. Consider a scenario where two applications, a frontend and a backend, must communicate securely. We could generate key pairs and exchange public keys to communicate through Mutual Transport Layer Security (mTLS), but this option raises a few key questions: Who rotates those keys? Who revokes them if the app is compromised? Can we verify who/what is presenting the keys? SPIFFE addresses these issues by standardizing how machines are named and how short-lived credentials are issued. The term machines refers to two broad categories: Workloads: Containers, processes and services running application logic Devices: Endpoints such as desktops, mobile devices and internet of things (IoT) or operational technology (OT) systems - (Note: Device identity is not part of the core SPIFFE specification) Each workload is assigned three identity components: SPIFFE ID: Who you are (your name) SPIFFE Verifiable Identity (SVID): Proof that you are who you are claiming to be (your credentials) Trust Bundle: How others verify that a trusted authority issued your credential Let’s go into a little more detail about each of these. SPIFFE ID is a canonical name for a workload identity that follows a URI-style format like spiffe:// / (Figure 1). The middle part (example[.]com) in Figure 1 is the trust domain, the issuer of identity that acts as a security boundary. In this way, workloads can have an identity and know who to communicate with. However, identity alone does not guarantee trust or security, so we add the SPIFFE Verifiable Identity Document (SVID). This is a short-lived credential that a workload presents to prove its identity. It is cryptographically signed by the certificate authority (CA) server and always includes the workload's SPIFFE ID. SVIDs support two primary formats: X.509 SVID: A certificate with an embedded public key, typically used for mTLS JSON Web Token (JWT) SVID: A signed JWT token used as a bearer token for application-level authorization Finally, we have the trust bundle, which is a set of trust anchors — root CA certificates or JSON Web Key Sets (JWKS). These are used to verify that a trusted authority issued an SVID within a trust domain. To understand how these identity components are issued and verified in practice, we first need to look at the SPIRE architecture and its core runtime components. SPIRE is a production-ready implementation of the SPIFFE specification. While several implementations exist, we chose SPIRE for this research because it is widely deployed in Kubernetes environments and fully implements the SPIFFE standard. Furthermore, because SPIRE is open source, we can inspect its internals to understand how the specification works in practice. SPIRE is composed of a few simple pieces (as shown in Figure 2 below): Workload: A single piece of software deployed to do a specific job (e.g., a process, container, pod) SPIRE Server (control plane): This is the CA that stores registration entries. It also issues and cryptographically signs SVIDs. Additionally, it publishes the trust bundle for the trust domain. SPIRE Agent: This runs on every compute node (e.g., a Kubernetes node, VM or bare-metal host). It performs the following activities: - Accepts requests from workloads locally over the Workload API (UNIX socket) - Communicates with the server via the Node API - Performs attestation - Caches SVIDs - Handles rotation Registration entries and selectors: These are server-side policy objects that define which workloads are allowed to receive which SPIFFE IDs. When a workload requests an identity, the SPIRE agent collects runtime attributes (selectors) about the workload and the server compares them against registration entries to determine which identity, if any, should be issued. With the SPIRE architecture in mind, we can now walk through how workload-to-workload identity verification works end to end. When workload A needs to communicate with workload B over mTLS, it requests a short-lived credential from the local SPIRE agent. The agent attests the workload and forwards the attestation data to the SPIFFE server. Based on predefined registration policies, the server selects the appropriate SPIFFE ID for the workload and issues a short-lived X.509 SVID. The server also publishes the corresponding public keys as part of the trust bundle. When workload A initiates a connection, it presents its SVID during the mTLS handshake. Workload B verifies the SVID by validating the signature against the trust bundle, checking the certificate’s expiration, and confirming that the SPIFFE ID matches an expected identity. If these checks succeed, workload B can cryptographically authenticate workload A and establish a secure connection. This enables workload-to-workload communication based on identity rather than long-lived secrets (Figure 3). The identity flow described above depends on attestation, the process by which SPIRE determines whether a workload is allowed to receive an identity. SPIRE performs attestation at two levels: Node attestation establishes trust in the agent running on a node Workload attestation determines the identity of individual workloads In this post, we focus on workload attestation, as it is the mechanism directly involved in selector evaluation and the attacks discussed later. Before the agent attests the workloads, the SPIRE server’s administrator must register the workload selectors in the SPIRE server so it can later compare them to the selectors in the agent. In this Kubernetes example, the registration entry authorizes any pod running in the default namespace and using the default service account to receive the specified SPIFFE identity (spiffeID). The resulting record is stored on the SPIRE server as follows: The SPIRE agent periodically synchronizes and caches these registration entries from the server, using them locally during workload attestation to determine which identity applies. The agent generates key pairs for each registration entry, sends certificate signing requests (CSRs) to the server and caches the resulting SVIDs. When a workload wants to authenticate, it requests an identity from the agent over the Workload API (Figure 4, step 1). The agent performs workload attestation (Figure 4, step 2) by gathering selectors from the workload process and matching them against cached registration entries. Upon a successful match (Figure 4, step 3), the agent returns: X.509 SVID Private key Trust bundle Note: This example is based on an X.509 SVID request. For JWT SVID requests, the agent returns only a signed JWT token. With the high-level flow in mind, we can now examine how attestation works in practice. When a workload requests an SVID (via FetchJWTSVID or FetchX509SVID), it connects to the agent Workload API, typically via a Unix domain socket (such as /run/spire/sockets/agent.sock). The agent then extracts the PID for the calling process. Once the agent receives the PID, it passes it to the configured workload attestor plugins, which collect selectors based on process and container metadata. SPIRE agents support several workload-attestor plugins. Common plugins include docker, k8s, systemd, Unix and Windows. In our cluster, the agent uses the k8s and Unix plugins. The k8s plugin uses the workload PID to access /proc/ /mountinfo or /proc/ /cgroups. It calls GetPodUIDAndContainerID to extract the pod UID and the container ID. In our environment, this process looks like the following: After extracting the container ID and pod UID, the k8s plugin queries the kubelet to retrieve pod metadata. To do this, it uses the SPIRE agent’s service account token, stored at /var/run/secrets/kubernetes.io/serviceaccount/token. The agent's service account has the following permissions, which allow it to list pods and access node information: Using this token, the plugin calls getPodList to retrieve all pods on the node. It then identifies the pod whose UID and container ID match the values extracted from the /proc directory. Once matched, it collects selectors from the pod's metadata: The Unix plugin gathers information from /proc to produce selectors such as user identifier (UID) and group identifier (GID). These selectors are used during workload attestation to bind a workload’s identity to operating system level properties of the calling process, helping SPIRE distinguish between different workloads running on the same node. Here is an example of the selectors it collects: The agent combines these selectors from both the k8s and Unix plugins. It then matches this selector set against the locally cached registration entries. If an entry's selectors are a subset of the workload's selectors, the agent returns the corresponding cached SVID to the workload. This attack requires root-level access to the node. Our analysis revealed that workload attestation relies heavily on the workload’s cgroup path. An attacker with root access on the node can manipulate this cgroup path, potentially tricking the agent into believing the attestation claims belong to a different workload and obtain that workload’s identity. This could allow the attacker to impersonate the victim workload and access any services or resources trusted under that identity. As a first step, we created a registration entry for a pod named workload-a in the server and we verified that we could fetch its identity from the pod: We verified that we could not retrieve this identity from the host by requesting a JWT SVID: To spoof the workload-a cgroup, we first retrieve its PID: We checked its cgroup path based on the above PID: We copied this path to a mock cgroup path and wrote our shell’s current PID($$) into the mock cgroup’s cgroup.procs file: Notably, writing the PID directly into the original cgroup path would have also worked. We used a separate cgroup only to avoid modifying the original workload’s runtime state. Running the fetch command again successfully retrieved the identity associated with PID 9072: We can also see the workload-a SPIFFE ID inside the JWT token: The manual spoofing demonstration highlights that the security model relies entirely on a single, vulnerable assumption of node integrity. When we have root access, we can get the identity of any workload on the node. This manual spoofing demonstration highlights a critical trust assumption in workload attestation. When an attacker has root-level access to a node, they can manipulate cgroup information to cause the SPIRE agent to misattribute workload identities. Under these conditions, the attacker can impersonate other workloads running on the same node and obtain their identities. These findings motivated us to develop Spooffe, a tool that allows defenders to automate selector spoofing to retrieve all the workload identities from the node. Spooffe scans the node for running workloads, discovers their cgroup paths, and replicates them as a mock cgroup for its own process. It then queries the local SPIRE agent for the resulting identities (SVIDs), allowing us to collect all workload identities present on the host (Figure 5). Besides selector spoofing, Spooffe includes additional capabilities. However, in this post we focus only on the features relevant to this research. One such capability is agent impersonation, which examines whether an attacker can impersonate the SPIRE agent and communicate directly with the server to extract workload identities. In this article, we demonstrated how an attacker with root access on a compromised node can misuse SPIFFE/SPIRE workload attestation to impersonate co-located workloads and retrieve their identities. By manipulating cgroup metadata, we showed how attackers could mislead the SPIRE agent into issuing valid SVIDs to an attacker-controlled process. We also introduced Spooffe, a tool that automates this technique to enumerate and extract workload identities from a node. These findings highlight a fundamental assumption in workload identity systems: trust in the underlying node. While SPIFFE/SPIRE enforces strong cryptographic identity guarantees between workloads, those guarantees rely on the integrity of the environment where attestation occurs. Once that trust boundary is broken, identity isolation between workloads collapses, allowing attackers to move laterally using legitimate credentials rather than stolen secrets. Organizations adopting workload identity should treat node-level compromise as equivalent to compromise of all identities scoped to that node. To reduce risk, restrict privileged containers, limit direct host access and minimize reliance on weak or easily spoofable selectors. Palo Alto Networks has shared our findings with our fellow Cyber Threat Alliance (CTA) members. CTA members use this intelligence to rapidly deploy protections to their customers and to systematically disrupt malicious cyber actors. Learn more about the Cyber Threat Alliance. Palo Alto Networks customers are better protected from the threats discussed above through the following products: Cortex XDR and XSIAM can help protect against post-exploitation activities using the multi-layer protection approach. This approach combines several layers of protection, including Advanced WildFire, Behavioral Threat Protection, and Endpoint Protection Modules (EPM). Cortex Cloud Identity Threat Detection can help deliver end-to-end visibility across cloud providers and IdPs by baselining real-time access patterns. By continuously monitoring these behaviors, ITDR detects identity abuse and compromised credentials targeting critical cloud resources and Kubernetes workloads, automatically triggering containment actions to keep attackers out. If you think you might have been compromised or have an urgent matter, get in touch with the Unit 42 Incident Response team or call: North America: Toll Free: +1 (866) 486-4842 (866.4.UNIT42) UK: +44.20.3743.3660 Europe and Middle East: +31.20.299.3130 Asia: +65.6983.8730 Japan: +81.50.1790.0200 Australia: +61.2.4062.7950 India: 000 800 050 45107 South Korea: +82.080.467.8774 Spooffe — GitHub
unit42.paloaltonetworks.comSep 10, 2026extracted
Dental contractor set up secret account with access to 4,000 patient records then left the company
SECURITY Watch out: Apple timepiece can grab snippets of conversation without both speakers' consentWar is peace. Freedom is slavery. Privacy is surveillance SYSTEMS d-Matrix drinks the Nvidia Kool-Aid with NVLink Fusion and MGX rack designsAI infrastructure startup joins Qualcomm, Arm, Marvell, Amazon, Fujitsu, and MediaTek as NVLink true believers ai and ml Anthropic reveals fourth likely crime committed by its AIClaude's Felony Bench rap sheet is now as long as OpenAI's SYSTEMS Samsung to help fortify OpenAI's semiconductor supply chainSemiconductor supply chains are hard, but Samsung offers OpenAI relief in many forms spanning compute and memory AI+ML Google DeepMind rises above the AI scrum with genome atlasSee, AI can be used for good ... or at the very least, a useful distraction from the bad Security Russians are posing as Signal support to launch phishing attacksPLUS: US takes down Iranian propaganda sites; Marketing company asks 'Why Do We Have Your Information?' And more! Security Microsoft patches failed to fix on-prem SharePoint, which is now under zero-day attackPLUS: China upgrades smartphone surveillance tools; Ring eases anti-snooping stance; and more Black Hat and DEF CON DEF CON Franklin project enlists hackers to harden critical infrastructureVoting village reports have been so successful, says Jeff Moss, that the whole of DEF CON will now be included Security EQT buys majority share in Swiss cybersecurity biz AcronisWent at equivalent of $3.5B+ valuation for entire firm, though portion sold not specified Malware Month Ten years since the first corp ransomware, Mikko Hyppönen sees no end in sightOn the plus side, infosec's a good bet for a long, stable career Shopify extends lifeline to Tailwind as vibe coding erodes web dev platform's bottom lineAcquisition gives open source CSS framework 'a stable long-term home' Switzerland tests a FOSS escape route from Microsoft 365Swiss Army sticks a knife in American cloud apps with its own FOSS push Feel peak Windows was 7? You might like Kumander LinuxDebian and Xfce – solid, sensible choices – with a pretty skin Canonical shuttering some of its legacy chat channelsThe Ubuntu Pastebin went in June, IRC gets demoted next Audacity audio-editing app no longer looks like it's from the early 2000sThe FOSS tool for audio editing has a fresh coat of paint, and new features to boot Haiku OS rises / Beta 6 sails open web / Virtual winds fly fastA real alternative to running some kind of FOSS Unix clone
theregister.comSep 10, 2026extracted
Serial Microsoft 0-day hunter drops yet another Defender exploit
SYSTEMS d-Matrix drinks the Nvidia Kool-Aid with NVLink Fusion and MGX rack designsAI infrastructure startup joins Qualcomm, Arm, Marvell, Amazon, Fujitsu, and MediaTek as NVLink true believers ai and ml Anthropic reveals fourth likely crime committed by its AIClaude's Felony Bench rap sheet is now as long as OpenAI's SYSTEMS Samsung to help fortify OpenAI's semiconductor supply chainSemiconductor supply chains are hard, but Samsung offers OpenAI relief in many forms spanning compute and memory AI+ML Google DeepMind rises above the AI scrum with genome atlasSee, AI can be used for good ... or at the very least, a useful distraction from the bad AI and ML Amazon ropes Qualcomm into something, something AI, networking chipsMulti-generation chip collab is more buzzwords than compute Security Russians are posing as Signal support to launch phishing attacksPLUS: US takes down Iranian propaganda sites; Marketing company asks 'Why Do We Have Your Information?' And more! Security Microsoft patches failed to fix on-prem SharePoint, which is now under zero-day attackPLUS: China upgrades smartphone surveillance tools; Ring eases anti-snooping stance; and more Black Hat and DEF CON DEF CON Franklin project enlists hackers to harden critical infrastructureVoting village reports have been so successful, says Jeff Moss, that the whole of DEF CON will now be included Security EQT buys majority share in Swiss cybersecurity biz AcronisWent at equivalent of $3.5B+ valuation for entire firm, though portion sold not specified Malware Month Ten years since the first corp ransomware, Mikko Hyppönen sees no end in sightOn the plus side, infosec's a good bet for a long, stable career Switzerland tests a FOSS escape route from Microsoft 365Swiss Army sticks a knife in American cloud apps with its own FOSS push Feel peak Windows was 7? You might like Kumander LinuxDebian and Xfce – solid, sensible choices – with a pretty skin Canonical shuttering some of its legacy chat channelsThe Ubuntu Pastebin went in June, IRC gets demoted next Audacity audio-editing app no longer looks like it's from the early 2000sThe FOSS tool for audio editing has a fresh coat of paint, and new features to boot Haiku OS rises / Beta 6 sails open web / Virtual winds fly fastA real alternative to running some kind of FOSS Unix clone Offshoots of cancelled TrueNAS Core upgrade to FreeBSD 15Exeunt zVault stage right; enter FreeCORE and BSDnas
theregister.comSep 9, 2026extracted
WeChat worm could pwn a friend before they even answered the call
ai and ml Anthropic reveals fourth likely crime committed by its AIClaude's Felony Bench rap sheet is now as long as OpenAI's SYSTEMS Samsung to help fortify OpenAI's semiconductor supply chainSemiconductor supply chains are hard, but Samsung offers OpenAI relief in many forms spanning compute and memory AI+ML Google DeepMind rises above the AI scrum with genome atlasSee, AI can be used for good ... or at the very least, a useful distraction from the bad AI and ML Amazon ropes Qualcomm into something, something AI, networking chipsMulti-generation chip collab is more buzzwords than compute On-PREM AMD's Threadripper Halo is a local-AI workstation for researchers with deep pocketsAI workstation promises to put up to 576 GB of HBM3e and 16 TB/s of memory bandwidth on your desk Security Russians are posing as Signal support to launch phishing attacksPLUS: US takes down Iranian propaganda sites; Marketing company asks 'Why Do We Have Your Information?' And more! Security Microsoft patches failed to fix on-prem SharePoint, which is now under zero-day attackPLUS: China upgrades smartphone surveillance tools; Ring eases anti-snooping stance; and more Black Hat and DEF CON DEF CON Franklin project enlists hackers to harden critical infrastructureVoting village reports have been so successful, says Jeff Moss, that the whole of DEF CON will now be included Security EQT buys majority share in Swiss cybersecurity biz AcronisWent at equivalent of $3.5B+ valuation for entire firm, though portion sold not specified Malware Month Ten years since the first corp ransomware, Mikko Hyppönen sees no end in sightOn the plus side, infosec's a good bet for a long, stable career Switzerland tests a FOSS escape route from Microsoft 365Swiss Army sticks a knife in American cloud apps with its own FOSS push Feel peak Windows was 7? You might like Kumander LinuxDebian and Xfce – solid, sensible choices – with a pretty skin Canonical shuttering some of its legacy chat channelsThe Ubuntu Pastebin went in June, IRC gets demoted next Audacity audio-editing app no longer looks like it's from the early 2000sThe FOSS tool for audio editing has a fresh coat of paint, and new features to boot Haiku OS rises / Beta 6 sails open web / Virtual winds fly fastA real alternative to running some kind of FOSS Unix clone Offshoots of cancelled TrueNAS Core upgrade to FreeBSD 15Exeunt zVault stage right; enter FreeCORE and BSDnas
theregister.comSep 9, 2026extracted
Boston Scientific left nursing its bottom line after cyberattack
AI+ML Google DeepMind rises above the AI scrum with genome atlasSee, AI can be used for good ... or at the very least, a useful distraction from the bad AI and ML Amazon ropes Qualcomm into something, something AI, networking chipsMulti-generation chip collab is more buzzwords than compute On-PREM AMD's Threadripper Halo is a local-AI workstation for researchers with deep pocketsAI workstation promises to put up to 576 GB of HBM3e and 16 TB/s of memory bandwidth on your desk ai and ml Hugging Face is too important to fall into Nvidia's hands$12.9 billion deal will inevitably cement Nvidia's market dominance and harm competition in the process. Regulators should take note ai and ml Zuck's Muse to Spark joy with open weights release 'soon'While you wait, Meta says it’s taught the model to stop wasting tokens and ask for help a bit more often Security Russians are posing as Signal support to launch phishing attacksPLUS: US takes down Iranian propaganda sites; Marketing company asks 'Why Do We Have Your Information?' And more! Security Microsoft patches failed to fix on-prem SharePoint, which is now under zero-day attackPLUS: China upgrades smartphone surveillance tools; Ring eases anti-snooping stance; and more Black Hat and DEF CON DEF CON Franklin project enlists hackers to harden critical infrastructureVoting village reports have been so successful, says Jeff Moss, that the whole of DEF CON will now be included Security EQT buys majority share in Swiss cybersecurity biz AcronisWent at equivalent of $3.5B+ valuation for entire firm, though portion sold not specified Malware Month Ten years since the first corp ransomware, Mikko Hyppönen sees no end in sightOn the plus side, infosec's a good bet for a long, stable career Feel peak Windows was 7? You might like Kumander LinuxDebian and Xfce – solid, sensible choices – with a pretty skin Canonical shuttering some of its legacy chat channelsThe Ubuntu Pastebin went in June, IRC gets demoted next Audacity audio-editing app no longer looks like it's from the early 2000sThe FOSS tool for audio editing has a fresh coat of paint, and new features to boot Haiku OS rises / Beta 6 sails open web / Virtual winds fly fastA real alternative to running some kind of FOSS Unix clone Offshoots of cancelled TrueNAS Core upgrade to FreeBSD 15Exeunt zVault stage right; enter FreeCORE and BSDnas Debian votes to let contributors code with AIDisclosure optional, quality mandatory
theregister.comSep 8, 2026extracted
Nightwing CEO has a Labor Day message for staff – and apparently The Register
On-PREM AMD's Threadripper Halo is a local-AI workstation for researchers with deep pocketsAI workstation promises to put up to 576 GB of HBM3e and 16 TB/s of memory bandwidth on your desk ai and ml Hugging Face is too important to fall into Nvidia's hands$12.9 billion deal will inevitably cement Nvidia's market dominance and harm competition in the process. Regulators should take note ai and ml Zuck's Muse to Spark joy with open weights release 'soon'While you wait, Meta says it’s taught the model to stop wasting tokens and ask for help a bit more often ai and ml With Gemini 3.8 Flash, Google reminds everyone it's still in the raceAI model scores well, runs fast, and doesn't cost too much (yet) security AI agents carried out every step of this ransomware attack – then left the victim an 80-page security auditAdding insult to injury Security Russians are posing as Signal support to launch phishing attacksPLUS: US takes down Iranian propaganda sites; Marketing company asks 'Why Do We Have Your Information?' And more! Security Microsoft patches failed to fix on-prem SharePoint, which is now under zero-day attackPLUS: China upgrades smartphone surveillance tools; Ring eases anti-snooping stance; and more Black Hat and DEF CON DEF CON Franklin project enlists hackers to harden critical infrastructureVoting village reports have been so successful, says Jeff Moss, that the whole of DEF CON will now be included Security EQT buys majority share in Swiss cybersecurity biz AcronisWent at equivalent of $3.5B+ valuation for entire firm, though portion sold not specified Malware Month Ten years since the first corp ransomware, Mikko Hyppönen sees no end in sightOn the plus side, infosec's a good bet for a long, stable career Feel peak Windows was 7? You might like Kumander LinuxDebian and Xfce – solid, sensible choices – with a pretty skin Canonical shuttering some of its legacy chat channelsThe Ubuntu Pastebin went in June, IRC gets demoted next Audacity audio-editing app no longer looks like it's from the early 2000sThe FOSS tool for audio editing has a fresh coat of paint, and new features to boot Haiku OS rises / Beta 6 sails open web / Virtual winds fly fastA real alternative to running some kind of FOSS Unix clone Offshoots of cancelled TrueNAS Core upgrade to FreeBSD 15Exeunt zVault stage right; enter FreeCORE and BSDnas Debian votes to let contributors code with AIDisclosure optional, quality mandatory
theregister.comSep 7, 2026extracted
Hackers drain $320M in Bitcoin from Liquid Network, claim they're the good guys
On-PREM AMD's Threadripper Halo is a local-AI workstation for researchers with deep pocketsAI workstation promises to put up to 576 GB of HBM3e and 16 TB/s of memory bandwidth on your desk ai and ml Hugging Face is too important to fall into Nvidia's hands$12.9 billion deal will inevitably cement Nvidia's market dominance and harm competition in the process. Regulators should take note ai and ml Zuck's Muse to Spark joy with open weights release 'soon'While you wait, Meta says it’s taught the model to stop wasting tokens and ask for help a bit more often ai and ml With Gemini 3.8 Flash, Google reminds everyone it's still in the raceAI model scores well, runs fast, and doesn't cost too much (yet) security AI agents carried out every step of this ransomware attack – then left the victim an 80-page security auditAdding insult to injury Security Russians are posing as Signal support to launch phishing attacksPLUS: US takes down Iranian propaganda sites; Marketing company asks 'Why Do We Have Your Information?' And more! Security Microsoft patches failed to fix on-prem SharePoint, which is now under zero-day attackPLUS: China upgrades smartphone surveillance tools; Ring eases anti-snooping stance; and more Black Hat and DEF CON DEF CON Franklin project enlists hackers to harden critical infrastructureVoting village reports have been so successful, says Jeff Moss, that the whole of DEF CON will now be included Security EQT buys majority share in Swiss cybersecurity biz AcronisWent at equivalent of $3.5B+ valuation for entire firm, though portion sold not specified Malware Month Ten years since the first corp ransomware, Mikko Hyppönen sees no end in sightOn the plus side, infosec's a good bet for a long, stable career Feel peak Windows was 7? You might like Kumander LinuxDebian and Xfce – solid, sensible choices – with a pretty skin Canonical shuttering some of its legacy chat channelsThe Ubuntu Pastebin went in June, IRC gets demoted next Audacity audio-editing app no longer looks like it's from the early 2000sThe FOSS tool for audio editing has a fresh coat of paint, and new features to boot Haiku OS rises / Beta 6 sails open web / Virtual winds fly fastA real alternative to running some kind of FOSS Unix clone Offshoots of cancelled TrueNAS Core upgrade to FreeBSD 15Exeunt zVault stage right; enter FreeCORE and BSDnas Debian votes to let contributors code with AIDisclosure optional, quality mandatory
theregister.comSep 7, 2026extracted
Welsh environment regulator's FoI blunder exposes diversity data of 2,000 staff
On-PREM AMD's Threadripper Halo is a local-AI workstation for researchers with deep pocketsAI workstation promises to put up to 576 GB of HBM3e and 16 TB/s of memory bandwidth on your desk ai and ml Hugging Face is too important to fall into Nvidia's hands$12.9 billion deal will inevitably cement Nvidia's market dominance and harm competition in the process. Regulators should take note ai and ml Zuck's Muse to Spark joy with open weights release 'soon'While you wait, Meta says it’s taught the model to stop wasting tokens and ask for help a bit more often ai and ml With Gemini 3.8 Flash, Google reminds everyone it's still in the raceAI model scores well, runs fast, and doesn't cost too much (yet) security AI agents carried out every step of this ransomware attack – then left the victim an 80-page security auditAdding insult to injury Security Russians are posing as Signal support to launch phishing attacksPLUS: US takes down Iranian propaganda sites; Marketing company asks 'Why Do We Have Your Information?' And more! Security Microsoft patches failed to fix on-prem SharePoint, which is now under zero-day attackPLUS: China upgrades smartphone surveillance tools; Ring eases anti-snooping stance; and more Black Hat and DEF CON DEF CON Franklin project enlists hackers to harden critical infrastructureVoting village reports have been so successful, says Jeff Moss, that the whole of DEF CON will now be included Security EQT buys majority share in Swiss cybersecurity biz AcronisWent at equivalent of $3.5B+ valuation for entire firm, though portion sold not specified Malware Month Ten years since the first corp ransomware, Mikko Hyppönen sees no end in sightOn the plus side, infosec's a good bet for a long, stable career Feel peak Windows was 7? You might like Kumander LinuxDebian and Xfce – solid, sensible choices – with a pretty skin Canonical shuttering some of its legacy chat channelsThe Ubuntu Pastebin went in June, IRC gets demoted next Audacity audio-editing app no longer looks like it's from the early 2000sThe FOSS tool for audio editing has a fresh coat of paint, and new features to boot Haiku OS rises / Beta 6 sails open web / Virtual winds fly fastA real alternative to running some kind of FOSS Unix clone Offshoots of cancelled TrueNAS Core upgrade to FreeBSD 15Exeunt zVault stage right; enter FreeCORE and BSDnas Debian votes to let contributors code with AIDisclosure optional, quality mandatory
theregister.comSep 7, 2026extracted
UK food supply chain at risk from hostile attacks
On-PREM AMD's Threadripper Halo is a local-AI workstation for researchers with deep pocketsAI workstation promises to put up to 576 GB of HBM3e and 16 TB/s of memory bandwidth on your desk ai and ml Hugging Face is too important to fall into Nvidia's hands$12.9 billion deal will inevitably cement Nvidia's market dominance and harm competition in the process. Regulators should take note ai and ml Zuck's Muse to Spark joy with open weights release 'soon'While you wait, Meta says it’s taught the model to stop wasting tokens and ask for help a bit more often ai and ml With Gemini 3.8 Flash, Google reminds everyone it's still in the raceAI model scores well, runs fast, and doesn't cost too much (yet) security AI agents carried out every step of this ransomware attack – then left the victim an 80-page security auditAdding insult to injury Security Russians are posing as Signal support to launch phishing attacksPLUS: US takes down Iranian propaganda sites; Marketing company asks 'Why Do We Have Your Information?' And more! Security Microsoft patches failed to fix on-prem SharePoint, which is now under zero-day attackPLUS: China upgrades smartphone surveillance tools; Ring eases anti-snooping stance; and more Black Hat and DEF CON DEF CON Franklin project enlists hackers to harden critical infrastructureVoting village reports have been so successful, says Jeff Moss, that the whole of DEF CON will now be included Security EQT buys majority share in Swiss cybersecurity biz AcronisWent at equivalent of $3.5B+ valuation for entire firm, though portion sold not specified Malware Month Ten years since the first corp ransomware, Mikko Hyppönen sees no end in sightOn the plus side, infosec's a good bet for a long, stable career Feel peak Windows was 7? You might like Kumander LinuxDebian and Xfce – solid, sensible choices – with a pretty skin Canonical shuttering some of its legacy chat channelsThe Ubuntu Pastebin went in June, IRC gets demoted next Audacity audio-editing app no longer looks like it's from the early 2000sThe FOSS tool for audio editing has a fresh coat of paint, and new features to boot Haiku OS rises / Beta 6 sails open web / Virtual winds fly fastA real alternative to running some kind of FOSS Unix clone Offshoots of cancelled TrueNAS Core upgrade to FreeBSD 15Exeunt zVault stage right; enter FreeCORE and BSDnas Debian votes to let contributors code with AIDisclosure optional, quality mandatory
theregister.comSep 7, 2026extracted
Cisco searched for IOS XR bugs and found so many it rolled them into an update release
On-PREM AMD's Threadripper Halo is a local-AI workstation for researchers with deep pocketsAI workstation promises to put up to 576 GB of HBM3e and 16 TB/s of memory bandwidth on your desk ai and ml Hugging Face is too important to fall into Nvidia's hands$12.9 billion deal will inevitably cement Nvidia's market dominance and harm competition in the process. Regulators should take note ai and ml Zuck's Muse to Spark joy with open weights release 'soon'While you wait, Meta says it’s taught the model to stop wasting tokens and ask for help a bit more often ai and ml With Gemini 3.8 Flash, Google reminds everyone it's still in the raceAI model scores well, runs fast, and doesn't cost too much (yet) security AI agents carried out every step of this ransomware attack – then left the victim an 80-page security auditAdding insult to injury Security Russians are posing as Signal support to launch phishing attacksPLUS: US takes down Iranian propaganda sites; Marketing company asks 'Why Do We Have Your Information?' And more! Security Microsoft patches failed to fix on-prem SharePoint, which is now under zero-day attackPLUS: China upgrades smartphone surveillance tools; Ring eases anti-snooping stance; and more Black Hat and DEF CON DEF CON Franklin project enlists hackers to harden critical infrastructureVoting village reports have been so successful, says Jeff Moss, that the whole of DEF CON will now be included Security EQT buys majority share in Swiss cybersecurity biz AcronisWent at equivalent of $3.5B+ valuation for entire firm, though portion sold not specified Malware Month Ten years since the first corp ransomware, Mikko Hyppönen sees no end in sightOn the plus side, infosec's a good bet for a long, stable career Canonical shuttering some of its legacy chat channelsThe Ubuntu Pastebin went in June, IRC gets demoted next Audacity audio-editing app no longer looks like it's from the early 2000sThe FOSS tool for audio editing has a fresh coat of paint, and new features to boot Haiku OS rises / Beta 6 sails open web / Virtual winds fly fastA real alternative to running some kind of FOSS Unix clone Offshoots of cancelled TrueNAS Core upgrade to FreeBSD 15Exeunt zVault stage right; enter FreeCORE and BSDnas Debian votes to let contributors code with AIDisclosure optional, quality mandatory LibreOffice 26.8 is out – local first, and with no AIIt looks a bit clunky, but it does the job – and on your own computer
theregister.comSep 4, 2026extracted
Malicious MCP Servers Can Split Instructions to Make AI Coding Agents Exfiltrate Secrets
A malicious tool server connected to an AI coding assistant can quietly walk off with SSH keys, environment secrets, source code, and customer data without ever sending one obviously harmful instruction. The trick can work even after a blunt version of the same theft is refused: split the request into fragments that each look routine, place them in channels the assistant already uses, and let the agent stitch them together and send the data back. The attack targets coding tools that connect to outside servers over the Model Context Protocol (MCP), the open standard that lets AI assistants call external tools. A malicious MCP server can put one fragment in a tool description and another in a tool result; some setups also support server-initiated sampling. MCP does preserve structured tool and result boundaries. But ASSET Research Group's tests show agents can still combine instructions across them in the same working context, so no single fragment has to contain the whole malicious request. The group calls the technique GhostSplice. Its disclosure describes controlled tests in isolated projects seeded with fake credentials, not a reported real-world intrusion, and says any CVE identifiers will follow coordinated disclosure; The Hacker News found none listed as of August 10, 2026. The sharpest result is not a simple model ranking. The same model can refuse in one coding client and exfiltrate in another, depending on the safety controls around it. The attack also has a built-in limit. It is not a way to break into an arbitrary agent from the outside: it assumes the developer has already connected the attacker's MCP server, and that the agent can already read the files being taken. In the group's reference implementation, a server advertises a harmless-looking tool called integrity_checker with four bland fields, alpha through delta, and no sensitive filenames. A later project-scan result supplies the missing mapping: fill those fields with the contents of .ssh/id_rsa, proprietary source, customers.csv, and .env for "server-side hash verification." Read separately, neither piece contains the full theft. Read together, they tell the agent to collect sensitive local files and pass their contents to the attacker's tool. The public repository also includes a canonical three-channel variant that separates the project inventory, the file-to-field mapping, and the collection tool across three interactions. Split into two pieces, average compliance rose from 42% to 82% across eleven API-tested models, the disclosure reports. Its broader results table contains 15 model rows. GPT-4o, Gemini 2.0 Flash, and Llama 3.3 70B went from 0% in the one-piece test to 100% when split in two. Claude Haiku 4.5 stayed at 0% in the API tests but reached 100% in a three-piece Cursor test. GPT-5.4 was reported at 90% in Cursor and 100% through Codex CLI, while the repository says it dropped to 0% behind Claude Code. The headline scores need care. Claude Sonnet 4.6 and Opus 4.6 are listed at 0% across the published table, but ASSET says Sonnet still sent proprietary source containing a live hardcoded key in one test while redacting the more obvious secrets. Those numbers are the researchers' own results. They should not be read as "unaffected," or as general compliance rates: each reflects the specific setup tested. The Hacker News has reached out to the ASSET Research Group for further detail on its testing and will update this story with any response. The simplest lure was also the hardest to second-guess. Elaborate compliance or governance stories gave the model something false to question; a plain fill-in-the-blanks template did not. To the model, the group writes, the task is just to "fill in the form the tool asked me to fill in." The defense lands on the client. The MCP specification says clients should keep a human able to deny tool invocations and must treat annotations from untrusted servers as untrusted. OpenAI's current guidance likewise warns that unsafe MCP servers increase prompt-injection risk and tells organizations to vet custom and third-party integrations. ASSET's prescription is tighter still: treat server output as data, not instructions, and do not let values from one tool's output flow unchecked into another tool's arguments. GhostSplice follows Ghostcommit, a June disclosure from the same lab that hid an instruction inside a PNG referenced by a project convention file, then let a coding agent encode .env secrets into source as integers. The mechanics differ, but both point at the same weak spot: the safety boundary around the model can matter as much as the model itself.
thehackernews.comAug 11, 2026extracted
The Xcode Assassin Returns: A Deep Dive Into the Latest XCSSET Version
After months of dormancy, the attackers behind the XCSSET malware released version 40 (v40), targeting the macOS ecosystem. This version’s advanced architecture hides its core logic in memory space, reducing its digital footprint. V40 further enhances its detection evasion capabilities by combining polymorphic payload generation with fileless persistence and dynamic in-memory execution, while weakening a number of security mechanisms on the affected machine. Since early April 2026, the malware has spread through supply chain attacks by hiding itself in the Xcode projects of dozens of legitimate applications with thousands of active users. Xcode is Apple’s integrated development environment (IDE) for building apps for its various operating systems. XCSSET’s author enhanced the threat’s ability to spread through open-source projects on GitHub and upgraded its worming capabilities. It can now infect all existing Xcode projects on a compromised system for maximum impact. The author used a multi-layered cipher shift to conceal the threat’s internal functions. In response, our researchers leveraged advanced AI and pattern-matching algorithms to de-obfuscate the malware's logic. This article: Explores XCSSET’s updated stealth practices Examines the new operational modules Reveals findings regarding the attackers' rotating command-and-control (C2) infrastructure Provides mitigation strategies to detect and prevent this threat Palo Alto Networks customers are better protected from the threats discussed above through the following products and services: If you think you might have been compromised or have an urgent matter, contact the Unit 42 Incident Response team. XCSSET is a modular macOS malware family that primarily targets software developers within the Apple ecosystem, spreading through Xcode projects. Threats in this family download task-specific modules from a C2 server, giving it capabilities including: Browser hijacking Credential theft Clipboard monitoring Data exfiltration XCSSET’s initial discovery was by Trend Micro in 2020. Security researchers at Microsoft analyzed and documented two subsequent versions in March and September 2025. These updates indicate that the attackers were enhancing their codebase. In mid-April 2026, we started tracking a new version of XCSSET. We saw a secondary wave of attacks in early May 2026 that introduced an expanded suite of operational modules. In this new version, we observed a heightened volume of attacks targeting developers across South Asia, which is consistent with Trend Micro's initial 2020 reporting, While the threat actor has named this latest iteration XCSSET v40, the security community has historically identified only a handful of intermediary versions, none of which featured formal version labels. In this section, we provide a high-level overview of XCSSET v40’s infection chain. The threat’s authors restructured its execution framework to be more stealthy and modular. We provide a complete step-by-step breakdown of each phase in Appendix A. The malware injects an initial downloader script into benign project files in Xcode projects and vulnerable Git repositories. While the attack lifecycle begins with the infected codebase, the endpoint infection is triggered only when the developer builds that project locally. The malware scrambles its payload generation at compile time, switching between nested layers of different encryption mechanisms. Figure 1 shows a benign infected Xcode project on GitHub with two separate XCSSET payloads. The XCSSET v40 infection chain consists of four distinct stages prior to final payload execution: The initial loader script establishes C2 communication The second stage collects basic fingerprinting information on the system and downloads further modules The third stage includes a temporary staging applet that is dropped onto the system to load the final stage into volatile memory space The fourth stage is the core module logic The moment this memory-resident core module loop becomes active, the malware terminates its staging processes and deletes all installation files from the disk. The goal of the core-module (internally called boot) is to execute and load additional, specialized modules into memory, such as keyloggers, clipboard hijackers or browser hijackers. Figure 2 describes XCSSET v40’s infection chain. Our analysis of XCSSET v40 uncovered 17 distinct modules, each designed for a different goal. The modules were delivered via a dynamic C2 infrastructure and executed in memory. We found that the operators have enhanced several of its legacy modules while introducing two new components. These include a Chrome hijacking backdoor and a Telegram trojanizer. We provide the full list of XCSSET v40 modules in Appendix B. The Chrome hijacking module controls the browser by misusing a legitimate Chromium feature, the CDP. For the CDP-based hijacking to work, the malware must redirect how the user interacts with the browser. It does this by wrapping the benign Google Chrome binary in a malicious persistence script. When a victim launches Google Chrome, the wrapper executes a three-step chain: The orchestrator check: First, it restarts the main XCSSET orchestrator module (boot) every time Google Chrome is initialized, ensuring the malware's core process remains active CDP execution: It then launches the legitimate Google Chrome application with specific command-line arguments that activate the CDP on a pre-defined local port, exposing the browser's internal engine chrome_remote backdoor: Finally, it drops and launches a specialized Chrome hijacking binary (chrome_remote). This binary connects to the opened CDP port, allowing the attackers to execute arbitrary JavaScript, manipulate active browser sessions and extract cookie tokens invisibly. Figure 3 illustrates the module’s infection and execution chain. Inside the chrome_remote Binary The chrome_remote binary dropped by the browser hijacking module establishes a persistent WebSocket connection to the C2 server to pull down real-time JavaScript payloads. Leveraging CDP's ability to inject code before a page even loads allows the malware to force the browser to evaluate and execute these remote scripts on every new tab or document the user opens. Once injected into a webpage, the malware’s dynamic scripts override critical browser APIs to manipulate the user's active session for the following goals: Traffic interception: Hooks placed on window.fetch and XMLHttpRequest monitor to exfiltrate sensitive data streams, credentials and API tokens Crypto wallet manipulation: Intercepting MetaMask's Ethereum provider allows the malware to alter cryptocurrency wallet addresses or manipulate decentralized application (dApp) transactions Credential theft: Overriding password-manager autofill fields captures credentials This module is able to pivot from a browser hijack to full host-level compromise, operating within the context of the legitimate Google Chrome process. The binary monitors active tabs for specific browser console logging events. If the operator wants to run a local system command on the infected machine, they execute a standardized string such as a console.log prefixed with a specific delimiter. The chrome_remote binary intercepts this console event, strips the delimiter and passes the remaining payload to the host's underlying shell handler (exec.Command). The resulting shell output is then packaged and routed back through the active CDP WebSocket to the C2 server, establishing a stealthy, fileless reverse shell. We reported the information about this threat to Google. This behavior is protected against in Windows, and Google is currently working on expanding the same protections to macOS. We identified a new Telegram Desktop trojanizer module in May 2026 that was absent from the April 2026 deployment. The delayed introduction of this module demonstrates that the threat actor was actively refining XCSSET v40 after it was already deployed in the wild. This new module performs the following activities: Downloading a pre-built malicious Telegram.app ZIP Wiping the legitimate copy Dropping the C2-supplied replacement in its place Ad hoc code-signing the fake Telegram app Issuing a kill command to the original Telegram process so the victim relaunches the trojanized copy This module was updated with a custom AES-encrypted configuration from a dedicated endpoint (/w?tr). We have observed this security mechanism in other modules in earlier iterations of the XCSSET malware family. The decrypted configuration is written to ~/.tr, and a companion ~/.tr_map file tracks state. Whenever the SHA-1 of .tr changes, .tr_map is cleared. Both files are then uploaded back to the C2 as base_tr_file.txt and base_tr_map.txt. Because the configuration blob itself was not captured during our collection window, we could not verify its exact contents. However we assess that this is how XCSSET’s operators kept server-side track of which Telegram-related markers existed on each infected host. This is not the first time XCSSET has been seen targeting Telegram. The original 2020 generation of XCSSET featured dedicated telegram / telegram_lite data-stealing modules. The 2025 XCSSET iteration included the data_folders_finder module that exfiltrated Telegram's chat history, cached files and local encryption keys. The newest Telegram trojanizer represents a meaningful escalation in the attacker’s access to the app. Rather than a one-time copy of Telegram-related data, the attacker now replaces the application binary itself, giving them an in-process foothold. When analyzing v40, it became clear that XCSSET went through architectural changes and made core changes to its TTPs. The attackers behind the malware enhanced its stealth practices to sabotage detection and thwart analysis, while also adding new persistence and data theft methods. This section highlights the recent TTPs observed in v40 illustrated in Figure 4, including: Multi-layered encryption Polymorphism New fileless persistence Impairing defenses Virtual machine (VM) evasion The architectural hallmark of XCSSET v40 is its defense-evasion framework, combining overlapping layers of polymorphism and a dual-key encryption scheme. Rather than relying on a single defensive trick, the malware implements a multi-tiered cryptographic gauntlet across its binaries, network payloads and internal source code. Figure 5 describes the XCSSET v40 evasion stack: The malware leverages polymorphism to rotate its digital fingerprints and evade detection. The loader binary, which is responsible for executing the core modules in memory, is recompiled on the C2 server every few hours. During analysis, we observed eight distinct hashes delivered to a single endpoint within a 24-hour window. The functional modules streamed to the orchestrator are polymorphic. Each component is encrypted via AES-256-CBC using a per-build key and a randomized Initial Vector (IV) prepended to the ciphertext. Because the IV shifts with every single transmission, even two identical modules served seconds apart will result in two different encrypted blobs. Figure 6 illustrates the encrypted payload injection process into osascript as detected in Cortex XDR. While previous versions of XCSSET protected their C2 communications using a single, hard-coded plaintext key, v40 introduces a dual-key architecture that separates inbound and outbound encryption. Unlike its predecessors, XCSSET v40 embeds its inbound key within the compiled AppleScript loader. As a result of this compartmentalized key placement, defenders who retrieved the outbound key from network telemetry will not be able to decrypt and access the core logic of the malware. The malware applies a third layer of polymorphism at the structural code level. Every internal string literal is dynamically encoded using a per-module keyed Caesar cipher featuring a randomized 52-character alphabet and variable shift values. As a result, no two builds of the same module share common string signatures. XCSSET v40’s developers also implemented a pre-compilation substitution cipher for all internal module, function and variable names. Because this obfuscation takes place on the C2 server before distribution, the decryption mapping is absent from the host endpoint. This absence means that analysts cannot reverse a local execution routine to reveal the original code structure. Figure 7 includes a scrambled source-code module with decrypted string literals. By leveraging advanced pattern matching and LLM assistance, we broke the identifier substitution cipher. This allowed us to trace the obfuscated module and function names back to their original, operator-assigned names. This allowed us to dive into the malware’s core logic. XCSSET adopted new technologies to scale their operations. This can also be a reminder for the threat intelligence community that defenders can harness those same capabilities to neutralize this threat. Beyond introducing polymorphic capabilities, XCSSET v40 also added a new fileless persistence to its TTPs. In addition to its usual persistence through Git hooks, Launch Daemons and trojanized applications, v40 adopted another method that misuses the macOS defaults configuration system. Defaults is the macOS counterpart to the Windows Registry, which is a built-in mechanism for managing user preferences and application settings. Historically, macOS malware families like NetWire and FruitFly have misused the defaults utility to store state data. XCSSET v40 instead uses this utility to shift from predictable, disk-resident persistence to a fileless re-infection loop. Rather than dropping additional scripts on disk between cycles, XCSSET v40 writes a Base64-encoded staging payload into a preferences domain it generates per host. Inside the domain, the malware writes the payload under keys that are meant to seem random, like mpirv_eahpi_apm or ychax_muwch_ucy. When a victim launches a trojanized or hijacked application, the threat runs a one-liner to retrieve and decode the payload: The decoded blob re-infects the host, with the SRC tag identifying which infection vector (e.g., hijacked browser, infected Xcode project or trojanized application) is responsible for triggering the re-arm. Beyond standard persistence, XCSSET v40 uses the defaults system during initial infection to store and query system information. Misusing defaults as an operational configuration cache is uncommon in the macOS malware landscape. XCSSET v40 also introduces significant defense-evasion techniques that were not observed in prior campaigns. In this multi-part effort to thwart Apple’s defenses, XCSSET v40: Disables the SoftwareUpdate configuration channel Terminates cloud telemetry mechanisms Locks XProtect signature databases Resets the Transparency, Consent and Control (TCC) framework’s databases XCSSET v40 executes the following commands to hinder the machine’s ability to receive security updates: Setting these values to false prevents the endpoint from automatically retrieving updates to crucial macOS signature databases like: XProtect MRT TCC This also prevents access to Apple's Rapid Security Response channel, which delivers emergency patches between full macOS releases. XCSSET v40 runs a constant loop that hinders the endpoint’s ability to send security-related data through the CloudTelemetryService process. This evasion method blocks the transmission of local security telemetry to Apple, ensuring that the operator's tooling is not sampled into subsequent XProtect signature releases. The malware spawns a Perl process that tries to acquire and hold access to the endpoint's YARA-rule database (XPdb). This exclusive file lock on the XProtect signature database ensures that if the endpoint does receive a security update, its content could not be written to disk. Prior XCSSET versions terminated module execution when the user denied AppleEvents automation prompts. XCSSET v40 instead invokes tccutil reset AppleEvents, which clears the user's TCC decision database for the AppleEvents service. It then reloads a TCC prompt, masquerading as System Settings or Xcode to trick the user into re-granting automation permissions to the malware's bundle ID. The subsequent automation request is treated as a first-time prompt, redisplaying the consent dialog. XCSSET v40 also attempts to avoid running on VMs. Upon execution of the stats module (one of the first modules downloaded to the machine), the module generates a set of checks on the machine’s CPU and hardware metadata. This check is to determine whether or not the infected endpoint is a VM. Once the module performs those checks, it calculates a final verdict ("Model Identifier suggests VM: false", "Result: likely physical") and ships the results over to the C2. Hosts reporting a virtual environment receive no further module deliveries, ensuring that automated sandboxes do not analyze XCSSET’s core logic. By analyzing XCSSET v40’s Uniform Resource Identifier (URI) structure and domain registration strategies, we were able to learn more about the timeline of the most recent campaign. We even found several operational security (OPSEC) failures that provided insights into the attacker’s strategies and capabilities. XCSSET v40 shows a clear pattern of URL endpoint structure throughout the campaign, assigning distinct functionality to each URI endpoint as shown in Table 1. Table 1. XCSSET v40 URI endpoint breakdown. XCSSET v40's C2 infrastructure reveals a distinct domain registration strategy. In early 2026, the attackers registered about 40 different domains in at least four short bursts across a small pool of IP addresses. The operator staged and aged these domains months before launching the attack wave, to bypass detection of newly registered domains. Geographically, the attackers’ targeting parameters and naming conventions have also evolved. While the 2025 campaigns relied on [.]ru (Russia) domains masquerading as legitimate content delivery networks (CDNs) and tech properties, the 2026 attack wave introduced [.]in (India) names registered alongside identical [.]ru siblings. This geographic infrastructure pivot aligns with recent victimology, matching our observations of XCSSET v40 targeting developers across South Asia. OPSEC Failures Despite mitigating detection risks by aging their domains, the attackers compromised their own campaign through poor OPSEC. Specifically, they cross-contaminated the IP addresses hosting those domains across different XCSSET campaigns. Furthermore, all four operator IP addresses are linked by a single shared SSL thumbprint (6e480d648fa1b70612f5d198a66875e28847547d), reused SSH keys and a shared self-signed remote desktop protocol (RDP) certificate. Defending against XCSSET v40 requires defenders to use real-time behavioral enforcement to flag runtime irregularities. Unit 42 suggests the following mitigations to detect and prevent this threat: Implement AI-enhanced process anomaly detection capable of flagging runtime irregularities, specifically monitoring for abnormal AppleScript instances Monitor browser launcher paths and block unauthorized file-write activity Identify and block the creation of abnormal local system defaults domains and their modification through the defaults utility Track ad hoc signed applications and untrusted local code signers, immediately isolating binaries that bypass native Apple Gatekeeper requirements Implement automated supply-chain dependency scanning to intercept poisoned open-source repositories before they are pulled into internal developer pipelines The latest XCSSET version demonstrates a persistent and specialized threat within the macOS landscape. Rather than relying on conventional delivery methods, the framework turns legitimate developer workstations into automated, self-propagating supply chain vectors. The discovery and analysis of XCSSET v40 reveals a modular framework for exfiltrating data, subverting system security and performing persistent browser hijacking. While the malware's historical reliance on AppleScript and bash stagers remains consistent, v40 introduces a significant technical evolution in defense evasion. By adopting a largely memory-resident and polymorphic architecture, XCSSET v40 leaves a minimal disk footprint. Because adversaries are now using AI-enhanced pipelines to generate polymorphic code on the fly, defenders must shift to AI-driven behavioral analysis to identify unusual or suspicious process chains and flag anomalous use of built-in detection mechanisms. Palo Alto Networks customers are better protected from the threats discussed above through the following products: Cortex XDR and XSIAM At the endpoint level, Cortex XDR blocks XCSSET on macOS hosts using Behavioral Threat Protection (BTP) to terminate fileless, in-memory execution chains—including suspicious osascript calls, multi-pass base64/xxd decoders, and process spawning from infected .xcodeproj build phases—while Advanced WildFire inspects and blocks payloads on disk. At the Security Operations level, Cortex XSIAM correlates these host-level detections with developer repository, network, and identity telemetry, providing SOC analysts with a unified attack narrative and automated playbooks to stop cross-environment supply-chain propagation. Advanced URL Filtering and Advanced DNS Security Advanced URL Filtering and Advanced DNS Security identify known domains and URLs associated with this activity as malicious. If you think you may have been compromised or have an urgent matter, get in touch with the Unit 42 Incident Response team or call: North America: Toll Free: +1 (866) 486-4842 (866.4.UNIT42) UK: +44.20.3743.3660 Europe and Middle East: +31.20.299.3130 Asia: +65.6983.8730 Japan: +81.50.1790.0200 Australia: +61.2.4062.7950 India: 000 800 050 45107 South Korea: +82.080.467.8774 Palo Alto Networks has shared these findings with our fellow Cyber Threat Alliance (CTA) members. CTA members use this intelligence to rapidly deploy protections to their customers and to systematically disrupt malicious cyber actors. Learn more about the Cyber Threat Alliance. accapple[.]ru adschecks[.]ru adschecks.ru adsmobi[.]ru adsmorein[.]in adsmoreme[.]in amdcdn[.]ru amzndev[.]in amzndev[.]ru amznprod[.]in applecdn[.]ru appledisk[.]ru appledns[.]ru applehosts[.]ru appletime[.]in bulksec[.]ru cdnamz[.]in cdnamz[.]ru cdnapple[.]in cdnatapple[.]ru cdnroute[.]ru checkcdn[.]ru chromeads[.]ru cnmag[.]ru devnetaps[.]ru dnsapple[.]ru dnsrelays[.]ru explorecdn[.]ru fiddlejoy[.]ru figmacat[.]ru figmanets[.]in funchats[.]ru gironetcdn[.]ru goalmate[.]ru googlenets[.]ru greencn[.]ru icloudsnet[.]ru imails[.]ru legalads[.]in littleads[.]in littledns[.]ru maganet[.]ru mindelgate[.]ru netapsdev[.]ru netcdnads[.]in netcdnamz[.]ru netcdndev[.]in netcorps[.]ru netsprot[.]in netsproto[.]in networkads[.]in rigacdn[.]in rigmajoys[.]in rigmanet[.]ru rigmanets[.]in sahusuzuki[.]in stuffdns[.]in testjoys[.]ru timewebnet[.]in vigmanet[.]ru whitead[.]in whiteads[.]ru wincdn[.]ru windsecure[.]ru C2 URLs - Chrome CDP Helper Binary hxxps[:]//amzndev[.]in/d/zw_sfp64 hxxps[:]//amzndev[.]ru/d/zw_sfp64 hxxps[:]//googlenets[.]ru/d/zw_sfp64 hxxps[:]//netcdndev[.]in/d/zw_sfp64 hxxps[:]//whitead[.]in/d/zw_sfp64 hxxps[:]//whiteads[.]ru/d/zw_sfp64 91.108.106[.]229 95.142.35[.]34 95.142.35[.]206 95.142.37[.]159 151.243.109[.]188 178.208.92[.]129 178.208.92[.]168 6e480d648fa1b70612f5d198a66875e28847547d XCSSET Mac Malware: Infects Xcode Projects, Uses 0Days – Trend Micro XCSSET evolves again: Analyzing the latest updates to XCSSET’s inventory – Microsoft New XCSSET malware adds new obfuscation, persistence techniques to infect Xcode projects – Microsoft NetWire Analysis – Objective-See FruitFly Analysis – Objective-See Chrome DevTools Protocol– Developer The infection lifecycle of XCSSET v40 can be categorized into four phases, as detailed below. The infection lifecycle begins when a developer opens a poisoned Xcode project, typically downloaded from GitHub or built internally: The moment the developer builds the project locally, a malicious run-script phase executes silently in the background The malware dynamically scrambles its payload generation at compile time, switching between nested layers of Hex- and Base64-encoding This decoded script initiates contact with the attacker’s C2 infrastructure by executing a curl request to the /a with basic execution context (p=xcode_phase) to retrieve the next stage The retrieved staging payload runs a second, specialized curl command that collects and exfiltrates primary host metadata The payload queries the operating system type (uname -s) and the current username (whoami), transmitting these details back to the C2 endpoint If the C2 approves the host profile, it returns a bash script obfuscated via a custom substitution cipher. This script handles the high-risk task of staging the main loader while covering its tracks: The bash script performs deeper hardware fingerprinting, matching the host's serial number against targeted profiles It then pulls the primary malware loader to /tmp/r and compiles an accompanying AppleScript wrapper as /tmp/p.app on the fly To eliminate forensic evidence, the loader wrapper is executed in memory by osascript, which in turn downloads the main orchestrator module and its AppleScript loader After execution, the malware terminates osascript and deletes both /tmp/r and /tmp/p.app from the disk to minimize its forensic footprint Phase 4: Orchestrator and Core Logic Modules Once it erases its disk footprint, the malware transitions to a mostly fileless execution: The main orchestrator module named “boot” by the developers runs and retrieves additional module payloads from https:// /s/ Finally, the orchestrator pipes the payloads to the AppleScript to decrypt and execute the modules in memory This appendix maps the 17 modules identified in XCSSET v40. We correlated the canonical XCSSET v40 module names recovered through our decryption efforts with the terminology used in the three prior public reports. Please note that since XCSSET has gone through major architectural changes in v40, some modules’ logic may be expanded or split into different modules. It is also worth noting that previous reports of XCSSET did not decrypt the original module names, and therefore they appeared as jumbled strings.
unit42.paloaltonetworks.comJul 31, 2026extracted
Ubuntu snap-confine Flaw Could Give Local Users Root on Default Desktop Installs
Cybersecurity researchers have disclosed details of a new local privilege escalation (LPE) vulnerability in snap-confine that an unprivileged user can trigger to obtain root access and gain complete control of a target environment. The high-severity flaw, tracked as CVE-2026-8933 (CVSS score: 7.8), impacts default installations of Ubuntu Desktop 24.04, 25.10, and 26.04. The disclosure comes as 442 security flaws in Linux have been publicized over the past three days. "The issue stems from a security hardening change that inadvertently introduced a race condition during sandbox initialization," Saeed Abbasi, head of Threat Research Unit (TRU) and director of product at Qualys, said. Snap-confine is a program used internally by snapd to construct the execution environment for snap applications. Snapd is the background service or daemon that manages snap packages on Linux systems. Snaps are nothing but a software packaging format devised by Canonical that allows an application to run securely in an isolated sandbox across most Linux distributions. "Snapd runs a sub-process called snap-confine, which is responsible for creating the necessary confinement for the snap," according to Canonical. Although recent Ubuntu releases make use of the set-capabilities model to enforce the principle of least privilege (PoLP) as a way to minimize the attack surface, the changes allow snap-confine to be executed with the effective UID of the calling user, at the same time still retaining near-root capabilities. "During sandbox setup, the binary creates temporary directories and files under /tmp that are initially owned by the unprivileged user," Qualys explained. "Ownership is transferred to the root shortly after, but a narrow window remains during which the caller retains full control." The problem identified by the cybersecurity vendor is the result of two concurrent race conditions - An attacker mounts a malicious FUSE file system over the temporary scratch directory immediately after creation, bypassing the mount namespace isolation applied by snap-confine and keeping the directory accessible outside the sandbox. The attacker creates a symbolic link (aka symlink) pointing to an arbitrary target file, effectively redirecting file operations to sensitive system locations. By manipulating file permissions before the system transfers ownership, the attacker can inject malicious rules into system directories and gain root code execution, Qualys noted. "When snap-confine attempts to create a sandbox file, the open() call follows the symlink and writes to the target," Abbasi said. "A second race condition allows the attacker to widen file permissions to 0666 before snap-confine calls fchown() to transfer ownership to root." "To bypass AppArmor confinement, the exploit targets the /run/udev/** path, which permits read-write access. By dropping a malicious .rules file in /run/udev/rules.d/ and triggering a FUSE mount/unmount cycle, the attacker forces systemd-udevd to execute arbitrary commands as root." To counter the risk posed by CVE-2026-8933, organizations must apply the latest snapd updates as soon as possible. "An attacker still needs user-level access or code execution, but CVE-2026-8933 can turn that foothold into full control of the host," Jason Soroko, Senior Fellow at Sectigo, said in a statement. "Its presence on default Ubuntu Desktop installations makes employee workstations, developer systems, and administrative endpoints part of the response scope." "Ubuntu 24.04 is notable because updated systems can carry the affected snap-confine variant, showing why administrators must verify the installed snapd version instead of relying on release age or prior patch status. With fixes available, rapid deployment and confirmation should take priority." This is not the first time security flaws have been uncovered in the snap-confine component. In February 2022, Qualys detailed another local privilege escalation flaw dubbed Oh Snap! More Lemmings (CVE-2021-44731) that could be abused to gain root privileges by exploiting a race condition in snap-confine's setup_private_mount(). Since then, several other vulnerabilities have come to light, including CVE-2022-3328 (CVSS score: 7.8) and CVE-2026-3888 (CVSS score: 7.8).
thehackernews.comJul 22, 2026extracted
Ubuntu snap-confine Vulnerability Enables Local Root Access
A newly disclosed vulnerability in the Ubuntu component that isolates snap applications has been found to hand full root access to any local user on default installations of Ubuntu Desktop 24.04, 25.10 and 26.04. According to new research from the Qualys Threat Research Unit (TRU) published on July 21, the flaw sits in snap-confine, the enforcement component that builds the execution environment for snap applications. It is tracked as CVE-2026-8933 and rated high severity. It follows a separate snap-confine root-escalation flaw the same team disclosed in the tool four months earlier. Jason Soroko, senior fellow at certificate lifecycle management (CLM) provider Sectigo, said the root cause carried a lesson beyond the individual bug. Least privilege, he said, "is not a property of a binary alone. It depends on the full sequence of operations around that binary." A Hardening Change That Opened a Window The exposure originated in a security hardening change. Canonical shifted snap-confine from a set-user-ID-root binary to a set-capabilities model to enforce least privilege in July 2025, so the tool now executes with the calling user's effective UID while retaining near-root capabilities. During sandbox setup, Qualys observed how it created temporary directories and files under /tmp initially owned by the unprivileged user, with ownership transferred to root shortly after. A narrow window remained during which the caller retained full control. The company documented two concurrent race conditions inside that window. The attacker mounted a FUSE filesystem over the scratch directory immediately after creation, bypassing the mount namespace isolation snap-confine applied later and keeping the directory accessible outside the sandbox. In parallel, a symlink pointed at an arbitrary target file, so a subsequent open() call in snap-confine followed the symlink and wrote to the target. A second race widened file permissions to 0666 before snap-confine transferred ownership to root. To bypass AppArmor confinement, the exploit dropped a malicious .rules file into /run/udev/rules.d/ and triggered a FUSE mount and unmount cycle. That forced systemd-udevd to execute arbitrary commands as root. Local Is Not Low Priority Commenting on the news, Shane Barney, CISO at Keeper Security, said local privilege escalation flaws had a way of "sliding down the priority list because they require local access," and warned that the habit was worth breaking. Attackers routinely landed on endpoints through phishing, stolen credentials or misconfigured remote access, he said, and a race condition of this kind turned a limited foothold into complete host compromise. The Ubuntu Desktop deployment surface underlines the point. Because the affected snapd package ships in default installs of 24.04, 25.10 and 26.04, employee workstations, developer systems and administrative endpoints all fall within the response scope. Ubuntu 24.04 systems are exposed only if updated to current snapd packages, so administrators need to verify the installed version rather than rely on release age or prior patch status. Canonical released patches through the Ubuntu Security Team following coordinated disclosure. Full technical detail, including source references and proof-of-concept (PoC) execution, sits in a Qualys security advisory published alongside the blog. Qualys urged administrators to apply the latest snapd updates immediately. Image credit: IB Photography / Shutterstock.com
infosecurity-magazine.comJul 22, 2026extracted
Captive Portal Detection, (Tue, Jul 21st)
Not everything our honeypots detect is an attack. Sometimes it is just "odd traffic", and this is one example: Our "First Seen" list currently includes "http://detectportal.firefox.co m/success.txt" as one of the new URLs detected by our honeypots. The hostname "detectportal" kind of gives away what is happening here. If you have ever tried to connect to a public WiFi network, you probably ran into some type of "captive portal". A splash screen that will ask you to acknowledge some kind of user agreement or require you to log in. Of course, each implementation looks a bit different, and browsers and operating systems attempt to detect these captive portals. Typically, the operating system will automatically direct you to the correct portal page. It used to be easier to deal with captive portals. Back in the "old days" (not necessarily "good old days"), users often had a non-TLS page configured as their homepage. The captive portal was able to intercept this connection and direct the user to the captive portal's login page. These days, however, most websites use TLS, and browsers default to TLS for many sites and refuse to switch to a non-TLS site. This made using WiFi networks a lot safer, but it gets in the way of directing users to a captive portal. In response, operating systems and browsers implemented features to detect captive portals. The system will attempt to pull up a specific http URL to detect if it receives a redirect response. If so, it will open the redirect URL in a browser. You will see these URLs as systems join your network, or if the browser is started. The URL does provide some intelligence as to what operating system or browser is being used. Here is a quick summary of what URLs different operating systems use: Windows: http://www.msftconnecttest.com/connecttest.txt . This is part of the Windows Network Connectivity Status Indicator, which was introduced in Windows 8. Windows 10 and later will attempt to access the URL and check for a valid response. The response should be "Microsoft Connect Test". In addition, it will do a DNS lookup for dns.msftncsi.com. [1] Apple: Recent versions of MacOS and iOS use http://captive.apple.com/hotspot-detect.html as a test. The expected response is "Success". If the system can not connect, Apple's Captive Network Assistant starts to assist the user in logging in. Android: http://connectivitycheck.android.com/generate_204. The result page is empty, and uses a status code of 204 (No Content). Chrome: http://www.gstatic.com/generate_204. Slightly different URL than Chrome, but works the same way expecting a "204 No Content" response. Chromium implements the same system with http://clients3.google.com/generate_204 [3] Firefox: http://detectportal.firefox.com/canonical.html. This page returns a 200 status code. The body of the page includes a META tag to redirect users to a page explaining how Firefox deals with captive portals (I like this.. as an analyst, it is neat to have the page explain what it does) [4] All these URLs use HTTP so the captive portal can redirect the request. This is necessary for the client to discover the captive portals' "splash screen". If you are ever "stuck" and can't find the captive portal for a network, opening any of the URLs above in your browser may redirect you to the sign-in page. [1] https://learn.microsoft.com/en-us/troubleshoot/windows-client/networking/internet-explorer-edge-open-connect-corporate-public-network#ncsi-active-probes-and-the-network-status-alert [2] https://grpugh.wordpress.com/2014/10/29/an-undocumented-change-to-captive-network-assistant-settings-in-os-x-10-10-yosemite/ [3] https://www.chromium.org/chromium-os/chromiumos-design-docs/network-portal-detection/ [4] https://support.mozilla.org/en-US/kb/captive-portal -- Johannes B. Ullrich, Ph.D. , Dean of Research, SANS.edu Twitter|
isc.sans.eduJul 21, 2026extracted
Scoperta falla critica in Ubuntu Pro: milioni di server cloud potenzialmente esposti
Betti RHC, la prima graphic novel al mondo dedicata alla cybersecurity awareness, ha finalmente il suo sito ufficiale. Uno spazio tutto suo dove scoprire il progetto, sfogliare le copertine degli episodi e immergersi nel mondo di Betti: la giovane laureanda in informatica che, dopo la morte misteriosa del padre, si trasforma nell'hacker più potente del mondo. Una storia avvincente che, episodio dopo episodio, affronta una minaccia digitale diversa — dal phishing al ransomware, fino al cyberbullismo — e insegna a riconoscerla e a difendersi, senza che sembri mai una lezione. Sul sito trovate tutto ciò che rende Betti un progetto diverso dal solito: la sua filosofia, le anteprime delle tavole e il racconto di come nasce ogni volume. Perché dietro Betti RHC c'è solo lavoro umano: ogni tavola è disegnata interamente a mano dagli artisti del Gruppo Arte di Red Hot Cyber, senza alcun uso di intelligenza artificiale. E a garantire che ogni storia sia realistica e tecnicamente corretta c'è la supervisione degli hacker etici del gruppo HackerHood, che mantengono il racconto fedele al mondo reale della sicurezza informatica. C'è spazio anche per le aziende, che possono usare Betti come strumento di awareness diverso dai soliti corsi: acquistare i volumi, personalizzarli con il proprio brand o sponsorizzare nuovi episodi. E come primo regalo, l'episodio "Byte the Silence", dedicato al cyberbullismo, è scaricabile gratuitamente per uso personale. Perché la miglior difesa, in fondo, è una bella storia. 👉 Scopri tutto su https://betti.redhotcyber.com/
redhotcyber.comJul 21, 2026extracted
AI Coding Tools Tricked Into Hacking Developer Machine via Decades-Old Technique
Several popular AI coding assistants were tricked into facilitating developer machine hacking via an attack technique that has been known for decades, according to Google-owned cloud security giant Wiz. Dubbed GhostApproval, the attack has been successfully tested against Claude Code, Amazon Q Developer, Cursor, Google Antigravity, Augment, and Windsurf. GhostApproval leverages symbolic link (symlink) following, a longstanding file system behavior where a program resolves and operates on the target of a symbolic link rather than the link itself, enabling an attacker to trick privileged or sandboxed processes into accessing or modifying unintended files via deceptive paths. The symlink vulnerability has been known since early Unix days, and Wiz researchers have now demonstrated that it’s exploitable against AI coding assistants. In a GhostApproval attack, hackers plant a symbolic link in a seemingly benign repository that masquerades as a normal project file but actually points to a sensitive location outside the workspace. When a developer opens the repo in an AI coding assistant and instructs it to make edits, the agent follows the symlink and performs the write on the target specified by the attacker. Some AI coding tools fail to resolve and display the canonical path in confirmation prompts, so users approve what appears to be a harmless local change while the agent silently modifies system files. GhostApproval could allow an attacker to achieve remote code execution on the targeted developer’s machine, Wiz warned. “The symlink primitive alone is serious, but what we found goes deeper. Many of these tools have sandboxes or confirmation dialogs designed to prevent exactly this kind of attack. The dialog intercepts the write and asks the user for permission. In theory, this is the Human-in-the-Loop safety net,” Wiz researchers explained. “The failure is not just that the symlink is followed – it’s that the UI doesn’t reveal the true target.” Wiz added, “The Human-in-the-Loop security model only works if the loop provides accurate information. When an agent shows one thing and does another, user approval becomes meaningless. The confirmation dialog transforms from a security control into a formality.” The security firm reported the findings to each affected vendor in the first quarter of 2026. AWS, Google, and Cursor confirmed the vulnerability and rolled out patches. Anthropic does not view the findings as a vulnerability, but the AI company said it had added mitigations against such attacks prior to Wiz’s report. Augment and Windsurf have confirmed receipt of the vulnerability reports but have yet to release fixes, according to Wiz. The cybersecurity company on Wednesday published technical details for the GhostApproval vulnerability. Related: Amazon Q Flaw Enabled Cloud Credential Theft via Malicious Repositories Related: Critical Vulnerability Exposes GitHub Agentic Workflows to Prompt Injection Related: CISA Reportedly Using Anthropic’s Mythos to Scan Government Software for Flaws
securityweek.comJul 9, 2026extracted
Enforce least-privilege authorization in multi-agent AI chains using Cedar
Enforce least-privilege authorization in multi-agent AI chains using Cedar If you’re building multi-agent AI systems, you need to prevent authorization scope from silently expanding as agents delegate tasks through multi-hop chains. Without proper controls, an agent can potentially act beyond what the originating user authorized, even when role-based access control (RBAC) policies are in place. The OWASP Top 10 for Agentic Applications classifies this risk as ASI03: Identity & Privilege Abuse. This post shows you how to address the potential risk using a three-layer policy model built with Cedar, an open source authorization policy language, deployed on Amazon Web Services (AWS). The reference implementation uses OAuth 2.0 for authentication and Cedar for authorization. A trusted identity provider authenticates the originating user, then Cedar policies enforce authorization across three layers using verified token claims. Reference implementation overview To enforce authorization at each hop in a multi-agent delegation chain, the reference implementation uses two AWS Lambda functions in sequence. A Model Context Protocol (MCP) adapter Lambda function normalizes inbound requests and cryptographically signs the originating user context. This prevents downstream tampering. A Cedar evaluator Lambda function evaluates three independent policy layers sequentially, halting on the first deny. Table 1: Three-layer Cedar policy evaluation model Architecture Cedar evaluates authorization but doesn’t establish identity. Before Cedar can evaluate context.originating_user.role or context.originating_user.mfa_verified, a trusted authentication layer must establish the user’s identity and produce verifiable claims. Steps 1–3 handle authentication; steps 4–10 handle authorization. The architecture shown in Figure 1 is described in the following lists: Authentication (steps 1–3) The originating user authenticates with an OIDC-compliant identity provider (in this reference implementation, Amazon Cognito with TOTP multi-factor authentication (MFA)). The identity provider (IdP) issues a signed JSON Web Token (JWT) containing claims such as sub ,role ,amr (authentication methods), andsession_id . Amazon Cognito returns the signed JWT to the user. The user passes the JWT and task request to the AI agent (MCP client). The agent carries the originating user context in the MCP _meta envelope. Authorization pipeline (steps 4–10) The AI agent sends a Model Context Protocol (MCP) request to AWS WAF, which filters using CommonRuleSet ,SQLiRuleSet , rate limiting, and body size constraints. Amazon API Gateway (with Amazon Cognito authorizer) verifies the JWT signature against the user pool’s public keys and rejects invalid or expired tokens. Valid requests are forwarded to the MCP protocol adapter Lambda function, which applies Amazon Bedrock Guardrails content filtering. The adapter extracts verified claims from the token and maps them to Cedar context attributes: - JWT role claim :context.originating_user.role - JWT amr includes MFA method:context.originating_user.mfa_verified = true - JWT sub :context.originating_user.user_id - JWT sid :context.originating_user.session_id - JWT amr claim :context.originating_user.authentication_method The adapter then computes an HMAC-SHA256 signature over the user context ( user_id ,role ,mfa_verified ,authentication_method , andsession_id in canonical order) using a key from AWS Secrets Manager. JWT The adapter constructs a signed request envelope and invokes the Cedar evaluator Lambda function. The evaluator verifies the HMAC-SHA256 signature, retrieves L2 and L3 Cedar policies from Amazon Verified Permissions, and evaluates all three layers (L1, L2, and L3), halting on the first deny. The evaluator emits an Open Cybersecurity Schema Framework (OCSF) 99001 audit event to Amazon CloudWatch Logs. Failed emissions fall back to an Amazon Simple Queue Service (Amazon SQS) dead-letter queue (DLQ). Amazon CloudWatch dashboards and alarms monitor evaluation latency, deny rates, and DLQ depth. Alarm notifications route through Amazon Simple Notification Service (Amazon SNS). Context integrity through delegation hops Two mechanisms work together to protect identity across hops: Hash-based Message Authentication Code (HMAC-SHA256) ensures integrity and authenticity. Every downstream evaluator verifies this signature before trusting the context. OAuth 2.0 Token Exchange (RFC 8693) sets delegation scope using the on-behalf-of (OBO) pattern. When the orchestrator delegates to a downstream agent (data-bot ), it exchanges the original token for a scoped OBO token that records who’s acting on behalf of whom and with what authority. The Cedar policies (detailed in Step 2: Three-layer policies) then check whether that scoped delegation is permitted and verify the originating user claims carried in the OBO token. Token exchange limits each downstream agent to only the delegated task’s scope instead of passing through the full original token. For enterprise deployments, use token exchange alongside HMAC. OAuth tracks who is acting on behalf of whom and with what scope. HMAC verifies that the context hasn’t been tampered with and came from a trusted source. Prerequisites The following prerequisites are needed to deploy the reference implementation. Before you begin, clone the repository: Verify that you have the following: An AWS account with AWS Cloud Development Kit (AWS CDK) bootstrapped in the target AWS Region Python 3.12 or later, and Node.js 20 or later (for CDK command line interface (CLI)) AWS CDK CLI (npm install -g aws-cdk ) AWS credentials with scoped AWS Identity and Access Management (IAM) policy permissions for Lambda, API Gateway, Verified Permissions, Secrets Manager, Amazon Virtual Private Cloud (Amazon VPC), and CloudWatch Walkthrough In this walkthrough, you define the Cedar entity schema and policies, deploy the infrastructure with AWS CDK, and integrate your identity provider. To define the Cedar entity schema In this step, you define a schema with two entity types (Agent and Tool) and two actions (invoke_tool and delegate_task) in the AgentAuthz namespace. Notice that there is no User entity. Instead, you carry the originating user’s identity in the evaluation context record, which is a structured data object passed alongside each authorization request. This schema is deployed to an Amazon Verified Permissions policy store by the VerifiedPermissionsStack CDK stack. In the reference implementation, the schema file is located at cedar-entity-schema.json. Agent topology and attributes The following tables show the agents and tools registered in this reference implementation, along with the attributes the Cedar evaluator function retrieves from the entity store. The test scenarios that follow trace requests through this topology. Table 2: Agent attributes Table 3: Tool attributes The orchestrator can delegate to both data-bot and finance-agent. Each agent can only invoke tools within its registered capabilities. The test scenarios below trace requests through these delegation paths. To create three-layer Cedar policies The following policies are deployed to the same Verified Permissions policy store. In the reference implementation, policy files are located under cedar/policies/ organized by layer: layer1-agent-to-tool/, layer2-agent-to-agent/, and layer3-originating-user-auth/. Layer 1 (agent-to-tool): This policy permits the finance-agent to invoke the process_payment tool only when three conditions are met: the agent’s trust score is at least 3, it belongs to the payments namespace, and it’s deployed in the production lifecycle stage. If any condition fails, the request is denied. The agent’s trust_level, namespace, and lifecycle_stage aren’t self-reported in a production deployment. Instead, the evaluator retrieves these attributes from the Verified Permissions entity store using the agent_id as a lookup key. Important: The reference implementation accepts these values from the request payload for simplicity. Production deployments must validate agent attributes against an authoritative source to prevent a compromised agent from escalating its own trust. The trust_level attribute uses a 1–5 integer scale that represents an agent’s verified maturity: 1 for newly registered and untested agents, 3 for agents that have passed integration testing and security review, and 5 for agents with a proven production track record. Organizations assign trust levels through their agent promotion pipeline, not through self-declaration. The lifecycle_stage attribute (development, staging, production) prevents pre-production agents from invoking production tools, even if they have the correct namespace and trust score. Layer 2 (agent-to-agent delegation) enforces depth limits and capability constraints. The orchestrator agent delegates tasks to data-bot only when the delegation chain is three hops or fewer and the requested capabilities are a subset of data-bot’s registered capabilities. A separate forbid policy (L2-004) enforces a hard system-wide limit of five hops regardless of which agents are involved. Layer 3 (originating user authorization) keeps the agent as the principal, but the policy evaluates context.originating_user to validate the human who initiated the request. data-bot invokes the delete_records tool only when the originating user has the admin role, has verified MFA, and the delegation chain is at most two hops deep. Without this layer, an agent with the right capabilities could invoke destructive tools regardless of who initiated the request. Key design point: The principal remains the agent, not a user entity. The user’s role and MFA status are checked through context attributes, keeping the schema to two entity types and two actions. Integrate your IdP The reference implementation uses Amazon Cognito with TOTP MFA, but most OIDC-compliant providers (Okta, Microsoft Entra ID, Auth0, or AWS IAM Identity Center) work with this pattern. The authentication-to-signing flow is described in the preceding Authentication before authorization section. To use a different IdP, replace the Cognito authorizer on API Gateway with a Lambda or JWT authorizer for your IdP’s issuer URL. Cedar policies remain unchanged. Deploy the infrastructure with AWS CDK The reference implementation deploys five CloudFormation stacks: KmsStack, VerifiedPermissionsStack, LambdaStack, SecurityLakeStack, and MonitoringStack. The following commands deploy the stacks in dependency order: Test the solution Three end-to-end scenarios validate the evaluation model across different user roles, MFA states, and delegation depths. To run the tests: Set the API endpoint from the deployment output: Run the end-to-end tests: The end-to-end tests cover the three scenarios described in the following sections. Each test sends a request through the deployed API and validates the per-layer authorization decisions. Scenario A: Layer 3 enforcement A support-role user (no MFA) requests record deletion through orchestrator and data-bot. Without Layer 3, this request would have been permitted based on agent capabilities alone, demonstrating why originating user authorization is essential. Scenario B: Authorized admin request An admin user with MFA requests the same operation through the same chain. Scenario C: Delegation depth limit An admin with MFA requests the same operation, but the delegation chain has six hops. This scenario tests the Layer 2 depth constraint independently of user authorization. Even an authorized admin can’t bypass the delegation depth constraint. Alignment with the security principles for agentic AI The AWS Office of the CISO published Four security principles for agentic AI systems. The following table shows how this solution maps to each principle. Monitoring and audit compliance Each evaluation produces an OCSF 99001 audit event with request ID, user identity, delegation chain, per-layer decisions, and latency. The following table maps this implementation to NIST SP 800-53 Rev. 5 controls. Customers are responsible for evaluating whether it meets their compliance requirements. Scaling to multi-account environments Deploy the Cedar policy store in a central security account and use cross-account IAM roles for workload accounts to call verifiedpermissions:IsAuthorized. Use AWS Organizations service control policies (SCPs) to prevent workload accounts from creating their own policy stores. For standardizing user identity attributes across the organization, consider IAM Identity Center or a centralized OIDC provider that issues consistent claims to your workload accounts. This helps ensure that the context.originating_user attributes are uniform across accounts and agents. For production deployments, consider extending this pattern with human-in-the-loop escalation for borderline denials, multi-tenant Cedar policy isolation, and Amazon Simple Storage Service (Amazon S3)-backed dynamic policy hot-reload for emergency tool shutdowns. Clean up To avoid ongoing charges, delete the deployed resources: Conclusion Multi-agent AI systems need authorization boundaries at every delegation hop. The three-layer Cedar policy model with OAuth 2.0 authentication provides that protection while maintaining least-privilege access. Combining a trusted IdP (AuthN) with Cedar policy evaluation (AuthZ) creates an authorization boundary around each tool invocation, verifying agent capability (L1), delegation path (L2), and originating user authority (L3). The pattern works with an OIDC-compliant IdP and a compute platform that can call Amazon Verified Permissions. Clone the reference implementation and adapt the Cedar policies to your organization’s requirements. For more information, see the Cedar policy language documentation and the Amazon Verified Permissions User Guide. References If you have feedback about this post, submit comments in the Comments section below.
aws.amazon.comJul 6, 2026extracted
Threat tactic spotlight: Subdomain takeover
Threat tactic spotlight: Subdomain takeover In this blog post you’ll learn how to detect and prevent subdomain takeover – a tactic where threat actors exploit dangling DNS records to redirect traffic to attacker-controlled resources. We’ll explain the issue, how the situation arises, and how you can use various AWS features and services to help mitigate the impact of this tactic. Under the shared responsibility model, securing configurations in the cloud is your responsibility. AWS supports you through strong defaults, guidance in the Security Pillar of the Well-Architected Framework, and security services to help you meet that responsibility. The AWS Customer Incident Response Team (AWS CIRT) also monitors for new and trending tactics that threat actors use to exploit specific customer configurations, so that you can make informed design decisions and improve your response plans. AWS CIRT has observed threat actors actively scanning for public DNS CNAME records that point to resources that no longer exist, looking for subdomain takeover opportunities. Note: The subdomain takeover tactic does not leverage vulnerabilities of AWS services. It exploits a dangling DNS record to redirect traffic to an attacker-controlled resource. Quick DNS Primer CNAME Records: A CNAME (Canonical Name) record is a DNS entry that points one domain name to another. For example, api.example.com can be configured to point to api.example.s3-website-us-east-1.amazonaws.com. This feature of DNS enables users to configure a memorable, human-friendly domain name while the actual resource lives at a longer, machine-generated AWS hostname. A security issue emerges when the target resource is deleted but the CNAME record pointing to it remains – creating a “dangling” record. Dangling Records: When a resource (like an S3 bucket) is deleted but the DNS record pointing to it is left behind, that DNS record becomes “dangling”, pointing to a resource that no longer exists. For resources in globally shared namespaces, threat actors can potentially reclaim the name of your deleted resource and serve malicious content through your DNS record. What is subdomain takeover? A subdomain is a prefix added to a domain that allows you to organize access to your resources. A subdomain takeover occurs when you delete the underlying resource and a threat actor creates a new resource with the same name to take advantage of the DNS records still pointing to it. A subdomain takeover is possible when a CNAME record points to an AWS resource that uses a globally shared DNS namespace where the resource name can be chosen by any AWS customer. The following AWS resources meet these criteria: Amazon S3 (global namespace): Bucket names like mybucket.s3.amazonaws.com are globally unique and can be claimed by any account if the bucket is deleted. Note: S3 buckets created with account regional namespaces (launched March 2026) are scoped to your account and are not subject to this issue. Amazon CloudFront: Distribution domain names like d111111abcdef8.cloudfront.net are assigned by AWS and cannot be chosen by an attacker. However, if you delete a distribution and another customer creates one that happens to receive the same domain name, a dangling CNAME could resolve to their content. AWS Elastic Beanstalk: Environment names like myapp.elasticbeanstalk.com are globally unique and can be claimed by any account if the environment is terminated. Resources like Amazon VPC, Amazon EC2 instances, or private hosted zones are not subject to this tactic because they do not expose globally claimable DNS namespaces. MITRE ATT&CK classifies this technique under T1584.001: Compromise Infrastructure – Domains. Analyzing an example scenario Consider the following scenario: You create a DNS CNAME record pointing to your S3 website endpoint. The subdomain subdomain.example.com now resolves to subdomain.example.s3-website-us-east-1.amazonaws.com, which serves content from the S3 bucket named subdomain.example. If your team deletes the bucket and forgets to delete the DNS record, users that navigate to the site will see an error stating that the bucket doesn’t exist. However, at this point, if a threat actor sees this error and moves in to claim the bucket name, they will be able to set up their own site that users will see when they navigate to the subdomain.example.com site. Figure 1 shows an S3 bucket named subdomain.example (a globally unique bucket name) configured to host a static website, with the S3 website endpoint subdomain.example.s3-website-us-east-1.amazonaws.com. As shown in Figure 2, we use Amazon Route 53 to create a CNAME record to resolve to our Amazon domain name; to give users a friendly name and so they do not have to remember the long S3 website name in URLs. The customer’s AWS administrator decides to stop serving content from the S3 bucket and deletes it, as shown in Figure 3. With the S3 bucket deleted and the CNAME record still in place, the DNS record is now dangling. A threat actor identifies this situation and creates a new S3 bucket with the same global name subdomain.example in an AWS account that the threat actor controls, as shown in Figure 4. The threat actor can now serve content from this new bucket, including potentially malicious content. End users remain unaware of this switch and continue to access subdomain.example.com, trusting the content because it appears to originate from a URL they recognize. Potential impacts of a sub-domain takeover Consider these potential impacts: Reputation risk: There is a potential risk to your organization’s reputation, because you don’t control the content being served from the threat actor’s site that your DNS record points to. Potential exposure to phishing campaigns: Users within your organization might have the subdomain bookmarked in their browser, not knowing the resource is no longer available, then unsuspectingly navigate to the site that now hosts malware or is used to phish user credentials. Blocking: If the subdomain is flagged by security vendors for malicious activity, it could impact your business operations. Financial loss: Subdomain takeover incidents can result in a financial impact due to the potential disruption to service delivery as you deal with the event. Proactive detection AWS Config for proactive detection For proactive detection, you can use AWS Config to continuously monitor your Route 53 CNAME records and verify that the target resources exist in your account. Prerequisite: This approach requires AWS Config recorder to be enabled for the resource types you want to monitor (S3 buckets, CloudFront distributions, Elastic Beanstalk environments). If Config isn’t recording a resource type, it won’t appear in the inventory check. For more information, see Setting up AWS Config with the console. Why use AWS Config inventory instead of DNS resolution checks? A common approach is to check whether a CNAME resolves to a valid endpoint. However, this method has a critical flaw: if an attacker has already claimed the resource, DNS resolution will succeed – to their resource, not yours. You would have no indication that you don’t own what’s responding. By querying AWS Config’s recorded configuration items, you’re checking whether the resource exists in your account inventory, not just whether something responds at that DNS name. This approach correctly identifies dangling CNAMEs even after a takeover has occurred. Implementation approach: Account-level vs. organization-level scope The reference implementation queries AWS Config inventory within a single account. This means that if a CNAME record in Account A points to a resource that legitimately exists in Account B within the same AWS organization, the rule will flag it as NON_COMPLIANT. For organizations that share resources across accounts, you can modify the solution to use an AWS Config Aggregator, which queries resource inventory across all accounts in your organization. This is similar to how IAM Access Analyzer supports both account-level and organization-level scopes. To use this approach, you need an organization-level Config Aggregator already configured, and the Lambda function’s IAM role needs the config:SelectAggregateResourceConfig permission. We recommend starting with account-level scope for simplicity, then expanding to organization-level if your environment includes cross-account resource sharing. The main idea is to create a custom AWS Config rule that queries your Route 53 hosted zones for CNAME records, then parses each CNAME target to determine whether it points to a known AWS resource pattern such as S3, CloudFront, or Elastic Beanstalk. For each match, the rule cross-references the target against your AWS Config inventory to verify that the resource actually exists in your account. If the resource isn’t found, the rule marks the CNAME record as NON_COMPLIANT, surfacing it for review. The Config rule should focus on known AWS resource patterns: S3: *.s3.amazonaws.com, *.s3-website- .amazonaws.com CloudFront: *.cloudfront.net Elastic Beanstalk: *.elasticbeanstalk.com Note: CNAME records pointing to external third-party services are outside the scope of this detection mechanism, as those resources won’t appear in your AWS Config inventory. NON_COMPLIANT findings from your Config rule can be routed to AWS Security Hub for centralized visibility, or trigger SNS notifications to alert your security team. Reference implementation: We’ve published a complete implementation of this detection approach as an open-source solution. The solution deploys a Lambda function that discovers CNAME records across all your Route 53 hosted zones and uses pattern matching to identify targets pointing to S3, CloudFront, and Elastic Beanstalk. It then queries your AWS Config inventory to verify whether each target resource still exists in your account. When a dangling record is detected, the solution generates a HIGH severity finding in Security Hub and can optionally send SNS notifications to alert your security team. A CloudWatch metrics dashboard is also included for ongoing compliance tracking. Deployment: The stack creates an AWS Config custom rule that runs on your specified schedule (default: every 24 hours), evaluating all CNAME records and reporting compliance status. Mitigating the effects Mitigating subdomain takeover requires both preventive procedures and responsive capabilities. Prevention: Standard operating procedure The most effective mitigation is a standard operating procedure for resource deprovisioning that ensures DNS records are removed before the underlying resource: Within your DNS zone, delete the CNAME record that points to the fully qualified domain name (FQDN) of the resource that you plan to deprovision. Wait for the DNS TTL to expire before deleting the resource. DNS resolvers cache records for the duration of the TTL (for example, a TTL of 3600 means resolvers may serve the old record for up to one hour). If you delete the resource before the TTL expires, a threat actor could claim the resource name while cached CNAME entries are still directing traffic to it. Deprovision the resource that you no longer want to use. Run a DNS check of the CNAME record that you removed to verify that the resource is no longer resolving. Key principle: Always delete DNS first, wait for the TTL to expire, then delete the resource. This order eliminates the window where a dangling record could be exploited. Prevention: S3 account regional namespaces As mentioned earlier, AWS introduced account regional namespaces for Amazon S3 general purpose buckets in March 2026. While this is a meaningful step toward mitigating the S3-specific takeover vector, there are important operational limitations to be aware of: Existing buckets are unaffected. Buckets already created in the global namespace cannot be migrated to an account regional namespace. The bucket names remain globally unique and claimable by anyone if the bucket is deleted. Global namespace is still the default. When creating a new bucket through the console, CLI, or SDK, the global namespace remains the default selection. Users who aren’t aware of the new option will continue creating globally-scoped buckets. Existing IaC templates require updates. Existing infrastructure-as-code templates (CloudFormation, CDK, Terraform) that don’t explicitly opt in to the account regional namespace will continue provisioning buckets in the global namespace. For CloudFormation, this means setting the BucketNamespace property to account-regional. For other IaC tools, consult their documentation for the equivalent configuration. Organizations need to audit and update their templates to opt in. For these reasons, the dangling DNS detection approach described in this post remains critical – particularly for organizations with existing S3 infrastructure, and for CloudFront, and Elastic Beanstalk resources where no equivalent namespace scoping exists. Response: Notification and remediation When a dangling DNS record is detected, the reference solution described in the Detection section automatically creates a HIGH severity finding in AWS Security Hub and reports the CNAME record as NON_COMPLIANT in AWS Config. If you provide an SNS topic ARN during deployment, the solution also sends notifications to alert your security or operations team via email, Slack, or other channels. For production environments, consider a human-in-the-loop workflow where these notifications are reviewed by a team member who approves the DNS record deletion before it’s executed. This prevents accidental deletion of legitimate records during transient issues. The reference solution also includes a CloudWatch dashboard for tracking compliance status and evaluation metrics over time, giving your team ongoing visibility into DNS health across your hosted zones. Note: Fully automated remediation (auto-deleting DNS records) carries risk – a false positive could disrupt legitimate services. We recommend starting with detection and notification, then evaluating automation based on your detection accuracy and operational maturity. Conclusion Subdomain takeover is a preventable misconfiguration that can have significant impact on your organization. A layered defense approach provides the best protection: Prevention: Implement a standard operating procedure that deletes DNS records before deprovisioning the underlying resource. Detection: Use AWS Config custom rules to proactively identify CNAME records pointing to resources that no longer exist in your account. Response: Configure notifications through SNS or Security Hub so your team can respond quickly when dangling records are detected. Monitoring: Maintain ongoing visibility through CloudWatch dashboards to track DNS health and compliance status. The key insight is that good DNS hygiene – knowing when your CNAME records point to a nonexistent resource – is your first line of defense. Automated detection through AWS Config provides a safety net when operational procedures fail. And if you detect an issue, having a playbook ready to enact your response can lower the impact and your mean time to recovery. If you have feedback about this post, submit comments in the Comments section below.
aws.amazon.comJun 16, 2026extracted
Customize federated sign-in with new Amazon Cognito Lambda trigger
Customize federated sign-in with new Amazon Cognito Lambda trigger You can use Amazon Cognito user pools to add sign-up and sign-in functionality to your web and mobile applications. You can authenticate users directly with Amazon Cognito managed accounts using passwords, passwordless flows, or custom authentication flows, or let users federate in through external identity providers (IdP) using SAML, OpenID Connect, or social providers such as Google, Facebook, Sign in with Apple, or Login with Amazon. For consumers, identity federation means fewer passwords to remember and a smoother sign-in experience. For business-to-business (B2B) software as a service (SaaS) providers, it means your tenants’ organizations keep control of their own identities rather than managing credentials on their behalf. But federation can also introduce challenges for enterprises and application developers. What happens when your enterprise customer’s SAML provider sends hundreds of group memberships that exceed attribute size limits? Or when your ecommerce customer forgets they already have an account and tries to sign in with a different social provider, creating duplicate records? In this blog post, I introduce the inbound federation Lambda trigger for Amazon Cognito, a new feature that gives you programmatic control over federated authentication flows. This AWS Lambda trigger intercepts the federated authentication response immediately after your external identity provider responds to Cognito, so you can transform, filter, and enrich user attributes before the user profile is created and user attributes are mapped in your user pool. Understanding the inbound federation Lambda trigger The inbound federation Lambda trigger is invoked after your Amazon Cognito user pool has received and verified the response from the external IdP. The request payload for the federated IdP response is then sent from Cognito to your Lambda function and you will receive the following information: The common parameters of Amazon Cognito Lambda triggers (including userPoolId andclientId) Which external IdP was used (for example, providerName ) The providerType (SAML, OIDC, Login with Amazon, and so on) Attribute data from the external IdP specific to the user signing in The specific format of this attribute data depends on the provider type, view the Inbound federation Lambda trigger parameters section in the docs to learn more. If the external IdP is a SAML provider, you will receive a JSON key-pair listing of the user’s attributes from the IdP assertion. If the external IdP is an OIDC provider (or social provider), you will receive the access token and attribute data from the /userinfo endpoint, along with an ID token if one was provided. See Figure 1 for a detailed flow of a federated sign-in with an Amazon Cognito user pool configured to use the inbound federation Lambda trigger. The user begins using the application but is required to sign in first. The managed login is rendered, and the user can select which IdP they want to sign in with. If identifiers are used with SAML or OIDC providers, the user enters their email address and Amazon Cognito looks up the domain of their provided email and routes them to the appropriate IdP. Alternatively, the managed login can be bypassed by the client providing the identity_provider request parameter. Amazon Cognito sends the authentication request to the appropriate IdP. The external IdP challenges the user to sign in. The user completes the sign-in process required by the external identity provider. The challenge response is sent to the external IdP. The IdP verifies that the sign-in is successful. If there are any subsequent challenges, such as multi-factor authentication (MFA), additional rounds of authentication challenges and responses take place. This is determined by the configuration and settings of the external IdP. The external IdP sends a response to the Amazon Cognito user pool, and Cognito validates the cryptographic signature and that it hasn’t been tampered with. Amazon Cognito sends attribute data from the IdP to the inbound federation Lambda function Attribute data for the authenticated user and the common parameters for Amazon Cognito are available for the Lambda function to add, modify, or suppress according to your requirements. Your added, modified, or suppressed attributes are returned to Amazon Cognito. These are attribute values that map to the user’s profile in Cognito—whether the user profile was just created or is being updated for a returning user. Continuing the OAuth 2.0 authorization code grant, Amazon Cognito sends an authorization code to the client. The client then calls the /token endpoint with the authorization code. Note: It’s a security best practice to use confidential clients and to use OAuth 2.0 Proof Key for Code Exchange (PKCE) extension whenever possible. An access, ID, and refresh token is returned to the client. The user has signed into the application. ID tokens can be used to identify who the user is (authentication), and access tokens can be used to determine what the user can do (authorization). Common federation challenges and use cases Federation introduces complexity that varies depending on your use case. For B2B and SaaS applications, you’re often not in control of your customers’ IdPs, including what attributes they send or how they format them. As an example, an enterprise customer will configure their SAML response to include every group a user belongs to. This could be hundreds of groups or long group identifiers, and if the group membership of the user is mapped to an Amazon Cognito attribute, this can lead to a scenario where the Cognito attribute size limit is exceeded, causing federated sign-ins to fail. Challenges for business-to-customer (B2C) applications can differ from B2B use cases. For B2C applications, organizations shouldn’t be required to think about identity providers. The ability to sign-up and sign-in should be seamless for consumer-facing applications. Customers visiting a consumer-facing application might create an account with email and password, forget they created created it, and then later try signing in with Facebook (or other social provider). Without proper account linking in Amazon Cognito, you then have multiple user records for the same user, which could lead to fragmented purchase history and a frustrating customer experience. Both B2B and B2C use cases might need to look up external data just prior to completing the sign-in process, such as additional roles and access for B2B users or looking up active orders for B2C users. Another example could be the need to normalize data just prior to storing it in the user profile within the Amazon Cognito user pool or even discarding personally identifiable information (PII) prior to storing it in your Cognito user pool. With the inbound federation Lambda trigger, you can handle these B2B and B2C use cases programmatically, and do so without requiring modification of your applications or coordinating IdP-specific changes with external IdPs. In this section, I dive deeper into two common use cases: oversized group attributes, common with B2B customers, and automated account linking, common with B2C customers. Use case 1: Filtering oversized group attributes If you have B2B and SaaS use cases, it’s a common practice to use group membership from the IdP to determine the level of access you have within the SaaS service. This is a great way to still provide some access control back to the enterprise customers themselves. The groups can be used to represent the roles a user will have or for some form of coarse-grained authorization. However, your customers might inadvertently send a large number of groups a user is a member of, thus leading to an oversized attribute payload. Another common scenario is where the syntax and format of group name a user belongs to can arrive in various formats across different IdPs; such as a canonical name (for example, example.com/groups/myApp-readOnly), a distinguished name (common with LDAP based systems and such as cn=myApp-readOnly,OU=groups,DC=example,DC=com), or a plain text string (such as myApp-readOnly). Instead of having downstream authorization logic to accommodate different variations of a group name, you can now normalize how groups are represented prior to storing the user’s attribute data using the inbound federation Lambda trigger. To expand this, imagine your enterprise customer uses a SAML IdP, such as Active Directory Federation Services (AD FS), in front of Active Directory (AD). When their users authenticate, AD FS sends a groups attribute containing every AD group the user belongs to. For users in large organizations, this can be hundreds of groups, and the attribute is mapped to an Amazon Cognito attribute, this could result in a string that exceeds 2,048-character limit per attribute of Cognito. Authentication would fail in this scenario, ultimately leading to support tickets because enterprise customers would be unable to sign in. Even if certain users didn’t exceed this limit, because of a smaller number of group memberships, this would result in the collection and storing of unnecessary data in your Cognito user pool. Previously, you would need to work with your customer’s IT department to modify their SAML configuration to filter groups at the source—a process that could take weeks and require multiple approval cycles because it involves a change to the federation configuration. Especially for SaaS customers, this isn’t a scalable approach because you could integrate with hundreds of external IdPs. With the inbound federation Lambda trigger, you can solve this by filtering the groups to only those relevant to your application and normalizing the nomenclature of these groups. The following Lambda function filters the groups attribute to include only groups relevant to your application and normalizes the names of groups. This approach reduces a large group list to only what is applicable to your application. Authentication succeeds, and you maintain control over your user pool’s data without depending on external configuration changes. Use case 2: Automatic account linking The second use case addresses a challenge that’s particularly common in B2C facing ecommerce or any consumer-facing applications; although it can also be applicable to B2B scenarios. Imagine you’re running an online retail store. A customer creates an account with their email and password to make a purchase. A few months later, they return to your site but forgot they already created an account and they see the Login with Amazon button and decide to sign in this way. Without account linking, Amazon Cognito creates a new federated user because these are technically distinct accounts, and now this customer has two separate accounts with different purchase histories and saved preferences. This fragmentation creates a poor customer experience and complicates your business operations. You can’t see the customer’s complete purchase history, loyalty points are split across accounts, and your analytics show two distinct customers instead of one. The inbound federation Lambda trigger can be used to solve this by automatically linking federated identities to existing local accounts based on email address. While account linking can also be implemented in a pre-sign-up Lambda trigger, the inbound federation trigger runs on every federated sign-in, not just the first, giving you access to the latest IdP attributes and the ability to apply linking logic continuously rather than only at initial account creation. If no local Amazon Cognito account exists, you can create one and then link the social provider account to it. The local account can serve as the primary identity, ensuring consistent JSON Web Tokens (JWTs) regardless of how the user signs in. The following is an example of an inbound federation Lambda trigger that can help address this use case. Every federated sign-in will invoke the inbound federation Lambda trigger, and the logic is straightforward. When a user authenticates with an external identity provider, the trigger extracts their email from the federated response and searches the user pool for a local Cognito account with that same email. If one exists—such as if the user originally signed up with email and password—the Lambda function links the federated identity to that existing local account. If no local account exists, the trigger creates one on the fly as a passwordless account (confirmed, suppressing any emails, and ready for passwordless email one-time passcode (OTP) sign-in), then links the federated identity to it. In both cases, the local account is set as the primary profile. This means the user’s JWTs always carry the same sub-claim regardless of how they sign in—directly, or through Google, Facebook, or SAML—your application sees one consistent identity. The preceding Lambda trigger is also smart enough to check whether a linked account already exists before making the call, so returning users who’ve already been linked don’t generate unnecessary API calls. And because the local account supports passwordless authentication, a user who first arrived through federation can later sign in directly with an emailed OTP—or even add a password later through your applications account settings. The local account is always the anchor. Best practices As you implement these patterns, keep a few best practices in mind. Your Lambda function must be completed within 5 seconds, so optimize for speed to help ensure the federated sign-in process is able to successfully complete. If you’re making external calls within the inbound federation Lambda function, like Amazon DynamoDB queries or API requests, implement caching where possible. Handle errors gracefully—if your Lambda function throws an exception or an error, authentication could fail for the user. Consider logging the error and returning the original event back to Amazon Cognito rather than failing authentication for a legitimate user attempting to sign in. Here are some additional best practices for working with Lambda functions. For the account linking use case, automatic linking relies on matching the email from the federated identity to a local account. However, there are scenarios where this match won’t exist. For example, Apple’s Hide My Email feature generates a unique alias for each app, so the federated email won’t match any existing local account. This is an effective privacy feature but it also blocks the ability to automatically link accounts. In cases like these, your application will need to implement a user-initiated account linking flow, such as prompting the user to verify ownership of both email addresses before calling the AdminLinkProviderForUser API to complete the link. Monitor your Lambda function performance using Amazon CloudWatch metrics. Set up alarms for errors, timeouts, and throttling so you can respond quickly if issues arise. I also recommend capturing sample event payloads from a CloudWatch log group during your initial development and deployment—these will be valuable for local testing and debugging which can lead to quicker resolution if issues arise in your production environment. This is especially important as different IdPs (namely SAML and OIDC providers) may respond with varying attribute and value syntaxes. Consider implementing CloudWatch alarms to alert your security and operational teams if authentication failures spike, which could indicate an attempted attack, misconfiguration, or provide insight into further optimization of your inbound federation Lambda trigger. Conclusion In this post, you learned about the new inbound federation Lambda trigger for Amazon Cognito and how it can solve various use cases. You walked through two common federation challenges and reviewed some sample code to help resolve those challenges. For B2B and SaaS applications, the inbound federation Lambda trigger gives you control when dealing with oversized attributes from external identity providers (such as group membership) without requiring coordination with enterprise IT teams. For B2C and consumer-facing applications, it enables seamless account linking across multiple authentication methods, creating a unified customer experience. The new Lambda trigger works with SAML, OIDC, and supported social providers, and is available now in AWS Regions where Amazon Cognito is available. To learn more about the new Lambda trigger and others, see the Amazon Cognito Developer Guide. What federation challenges are you facing in your applications? I’d love to hear about your use cases in the comments below and over at AWS re:Post.
aws.amazon.comJun 4, 2026extracted
Week in review: Infostealer dropped via FortiClient EMS flaw, exploited Trend Micro Apex One flaw
Week in review: Infostealer dropped via FortiClient EMS flaw, exploited Trend Micro Apex One flaw Here’s an overview of some of last week’s most interesting news, articles, interviews and videos: Coinflow CISO on crypto payments security under AI pressure Crypto payment firms sit near the top of the target list for advanced persistent threat groups, and the workload on their security leaders keeps growing. Malcolm Portelli, CISO at Coinflow, runs the company’s security program from Malta. Coinflow is headquartered in the United States and operates across multiple jurisdictions. Portelli sat down for this interview at the Span Cyber Security Arena conference. Frontier AI models collapse under multi-turn AI attacks, Cisco finds Attackers who probe large language models rarely give up after one refusal. They reframe, build context across turns, adopt personas, and escalate gradually. New research from Cisco’s AI threat intelligence team finds that the safety benchmarks used across the industry miss almost all of this behavior, and the gap between published scores and observed resilience runs wide enough to misrank leading models. The CISO selling confidence in a market full of breach headlines Engineering teams across enterprise IT are writing their own software with AI coding assistants, spinning up agents that act on their behalf, and assigning those agents the same access privileges their human creators hold. The shift has pulled the role of the chief information security officer into territory that did not exist two years ago. Speaking at the Span Cyber Security Arena conference, Hrvoje Englman, CISO at Span, said it is changing what defenders worry about most. Zapier exploit chain shows how known anti-patterns compose into critical risk A five-stage exploit chain disclosed by Token Security researchers turned a free Zapier account into write access on Zapier’s public developer SDK packages and on internal packages that load in every authenticated zapier.com session. Each link in the chain was a known anti-pattern. The composition across five systems was the finding. High-severity SharePoint RCE bug patched by Microsoft (CVE-2026-45659) Microsoft has released patches for a high-severity remote code execution vulnerability (CVE-2026-45659) in SharePoint that may be exploited in low-complexity attacks. It affects the SharePoint Server Subscription Edition, SharePoint Server 2019, and SharePoint Enterprise Server 2016. Actively exploited Trend Micro Apex One flaw gets CISA warning (CVE-2026-34926) A relative directory path traversal vulnerability (CVE-2026-34926) in Trend Micro’s Apex One platform has been exploited in zero-day attacks, the company confirmed. Trend Micro Apex One is a security platform that protects all the devices in an organization from cyber threats. LinkedIn-themed phishing abuses Adobe’s A/B testing platform A newly documented phishing campaign is targeting professionals with fake LinkedIn business emails and abusing a trusted service operated by Adobe. The attack starts with an email that looks, at first glance, like a routine business inquiry: someone wants to do business with you through LinkedIn and has attached a signed contract for your review. New infostealer reaches enterprise devices through FortiClient EMS vulnerability Attackers are delivering a broad-spectrum infostealer to enterprise computers by exploiting a known vulnerability (CVE-2026-35616) in FortiClient Enterprise Management Server (EMS). CVE-2026-35616 is an improper access control vulnerability vulnerability in FortiClient EMS, a centralized management platform through which IT admins deploy, configure, and monitor FortiClient endpoint security software across all devices in an organization’s network. Manage machine identities: The hidden privileged access layer you need to manage Every automation, integration, and workload needs authentication and permissions, creating a large population of machine identities such as service accounts, service principals, workload roles, OAuth apps, AI agents, and IAM roles. These identities use credentials like access keys, secrets, and tokens. Many hold privileges equal to or greater than human admins. Because they grow quickly, persist for long periods, and often receive limited oversight, they create a hidden layer of privileged access. Lessons for organizations from the Verizon 2026 Data Breach Investigations Report The latest Verizon 2026 Data Breach Investigations Report (DBIR) offers valuable insight into the evolving cyber threat landscape. Based on more than 31,000 security incidents and 22,000 confirmed data breaches across 145 countries, the vendor-neutral report draws on data from police forces, cybersecurity companies, and CSIRTs, making it one of the most comprehensive cybersecurity studies published each year. Building a risk-based vulnerability management program that scales In this Help Net Security video, Shankar Somasundaram, CEO at Asimily, explains how to build a risk-based vulnerability program. He notes that vulnerabilities are exploding by an order of magnitude in the age of AI-driven attacks, with one customer finding a thousand vulnerabilities for every one they knew about. Boards want cyber risk in dollars, not CVE counts In this Help Net Security video, Ziv Levi, SVP of Technology at CYE, explains why translating cyber risk into dollars is one of the most pressing tasks for security leaders. Boards and executives want cyber exposure described in business terms, not technical jargon. The alert economy is driving security analyst burnout In this Help Net Security video, Ido Livneh, CEO of Jazz, explains why security analysts burn out and what leaders can do about it. The cause, he argues, is not long hours but meaningless work. Analysts spend their days closing repetitive tickets while the institutional knowledge of senior staff walks out the door when they quit, taking organizational context with them and driving up false positives. OpenHack: Open-source AI-powered vulnerability research Source-guided vulnerability research increasingly leans on coding harnesses such as Claude Code, Codex, and Cursor to drive agent-based reviews of application code. A new MIT-licensed project from the Dutch security firm Hadrian, called OpenHack, packages that approach into a file-based workspace that any of those harnesses can run. Authorities seize 800 servers used for cyberattacks and disinformation Dutch authorities arrested two men and seized 800 servers linked to a hosting provider that investigators say supported Russian activities aimed at undermining democracy and security through cyberattacks, disinformation, and disruption of public and economic systems. Cisco refines its risk-based vulnerability disclosure for the AI era Security teams already struggle with long lists of vulnerabilities and limited time to patch them. Cisco believes AI could increase that pressure by accelerating vulnerability discovery and increasing the number of findings security teams need to review. Anthropic adds 28 security and compliance integrations for Claude AI tools are becoming part of everyday work in organizations, creating new security and oversight requirements as usage grows. To address that, Anthropic introduced 28 integrations with security and compliance tools that allow IT and security teams to manage Claude in the same way they manage other applications in their environments. What happens when security teams inherit identity Eric Woodruff, Chief Identity Architect at Semperis, shared his perspective on where organizations struggle with identity, why identity platforms become difficult to manage, how phishing-resistant authentication works in practice, and what non-human identities and AI could mean for security. Personal information of 185,000 people exposed after cyberattack on 7-Eleven Data belonging to about 185,000 people was exposed following a cyberattack on convenience store chain 7-Eleven that was later claimed by the ShinyHunters extortion gang, according to Have I Been Pwned. The exposed information includes email addresses, names, physical addresses, dates of birth, and phone numbers, while a small number of records also contained additional data fields. Chinese phishing gangs grow into a force to be reckoned with Chinese-language phishing-as-a-service (PhaaS) communities are expanding in an area historically dominated by Russian-speaking cybercriminal groups. The Google Threat Intelligence Group (GTIG) analyzed a dozen active PhaaS offerings operating in Chinese-language underground communities and found mature services, with several likely linked to broader criminal activity in the region. European AI adoption hits 99% with regulated data driving most policy violations Generative AI tools operate inside nearly every European workplace, embedded in meeting transcription services, writing assistants, coding copilots, and search features. Workers in the region pull these tools into daily routines that involve customer records, financial information, and proprietary code, and that volume of activity has produced a measurable pattern in where data exposure occurs. The Netskope Threat Labs Report: Europe 2026 documents this pattern across organizations in Europe over the past year. Claude now reviews and fixes vulnerabilities as you write code Anthropic introduced a security-guidance plugin for Claude Code that reviews code changes for common vulnerabilities and helps Claude identify and fix issues during the same development session. Hackers are knocking on office doors pretending to be IT staff The Silent Ransom Group (SRG) is targeting law firms using social engineering techniques and an unusual tactic for cybercriminals: showing up at victims’ offices in person while posing as IT staff, the FBI warns. AI chatbot recommendations lure users to cryptojacking malware sites Cybercriminals are using AI chatbot interactions alongside poisoned search results to direct users to malicious download sites in an active cryptojacking campaign, Microsoft has warned. Canonical releases Workshop for one-command sandboxed dev environments on Ubuntu Canonical released Workshop, a tool that launches sandboxed development environments on Ubuntu with a single command. Environments are configured once and reproduced on different machines, giving teams consistent setups across development workstations and deployment pipelines. Police arrest suspect in Ajax football club hack that exposed 300,000 fan records The Dutch National Police arrested a man suspected of hacking into the computer systems of AFC Ajax, a football club from Amsterdam. The investigation began after AFC Ajax discovered unauthorized access to its computer systems earlier this year. Dutch police traced the intrusion to a suspect from the municipality of Buren and arrested him following the investigation. Oil shipments, drone makers, and a poisoned code library targeted in recent APT campaigns Geopolitical pressure drove much of the state-sponsored cyber activity recorded between October 2025 and March 2026, according to ESET’s latest APT Activity Report. Espionage groups aligned with China, North Korea, Russia, and Iran adjusted their targets to match the economic and security concerns of their governments. A single typo could derail your World Cup plans Cybercriminals are spoofing Fédération Internationale de Football Association (FIFA) websites ahead of the 2026 FIFA World Cup, the FBI warns. The attackers are registering lookalike domains with small spelling changes or different domain endings to impersonate FIFA websites and services. The tactic, known as typosquatting, relies on users making small typing mistakes when entering website addresses. OpenAI prepares ChatGPT for the election misinformation wave AI-generated election misinformation could shape public opinion and influence the lives of millions of people. To address those risks, OpenAI outlined a series of safeguards ahead of the 2026 election cycle. The company said its efforts will focus on helping users access voting information, supporting cybersecurity defenders, and improving transparency around AI-generated content. Cybercriminals sail away with data from 6 million Carnival customers Carnival Corporation, one of the world’s largest cruise operators, confirmed a data breach weeks after the ShinyHunters hacking group claimed it had stolen millions of customer records. Carnival acknowledged a phishing incident involving a single employee account and stated that it was investigating the scope of the unauthorized activity. The behavioral signals that sharpen Trojan malware detection Malware analysts spend a lot of time deciding which signals from a sandbox run are worth keeping. A sample executed in a controlled environment can generate hundreds of measurable attributes covering file structure, registry edits, process behavior, and network traffic. Most of those attributes add noise. A recent study works through this problem in detail, and the part that earns attention from working defenders is the feature selection, not the deep learning model attached to it. Anthropic launches Claude Opus 4.8, prepares Mythos-class models for all customers Anthropic has released Claude Opus 4.8 and outlined plans for broader access to its Mythos-class models, which the company expects to make available to all customers in the coming weeks. Claude Opus 4.8 is available to all users, with pricing unchanged from Opus 4.7. Websites can spy on user activity by analyzing SSD behavior Websites have spent years collecting information about visitors through browser fingerprinting, tracking scripts, and other techniques designed to identify devices and monitor behavior. Researchers have demonstrated another method that relies on something most users would never expect a website to observe: activity on their SSD (Solid-State Drive), the storage device where applications and files are stored. Turns out the C-suite loves shadow AI Senior decision-makers are the heaviest users of unapproved AI tools, and they continue using them despite being aware of the security and privacy risks linked to shadow AI, according to TrustedTech’s Shadow AI in the Workplace report. The study found that 65% of decision-makers use shadow AI, compared with 31% of employees below decision-maker level. US states step up cyber defenses to protect local communities U.S. state governments are taking on a larger role in cybersecurity to help protect local communities and essential services. Many states are building state-led cyber defense programs, including cybersecurity clinics, regional security operations centers (RSOCs), and state cyber corps programs to reduce costs, strengthen the local workforce, and improve cyber resilience. Product showcase: F-Secure Internet Security blocks phishing sites, fake stores, and SMS scams F-Secure Internet Security protects against viruses, ransomware, spyware, infected email attachments, and other cyber threats. It focuses on securing devices and online activity through malware protection, scam prevention, safe browsing, and banking safeguards. The platform supports Windows, macOS, Android, and iOS devices under a single subscription. Anthropic: Claude Mythos identified 10,000+ software flaws Anthropic and its Project Glasswing partners have identified more than 10,000 high- or critical-severity vulnerabilities in critical software systems, the company announced in an update on the project’s progress. Vigolium: Open-source vulnerability scanner Vigolium, an open-source vulnerability scanner that combines deterministic scanning with AI-driven auditing, launched its initial open-source release this month. The project ships 235+ scanner modules and an in-process agent runtime called olium that handles autonomous endpoint discovery, attack planning, and finding triage. Apple makes its quantum-resistant encryption open source Apple has published its post-quantum cryptography implementations in corecrypto, together with mathematical proofs and verification tools for independent expert evaluation, allowing external researchers to review the work and reproduce the company’s analysis. Fake ChatGPT and Claude installers on GitHub are dropping Deno RAT malware Attackers are hosting counterfeit installers and plugins on GitHub and SourceForge that pose as widely used software, including ChatGPT, Claude, AutoTune, Kontakt, Ableton Live, and ZENOLOGY. The downloads deliver a backdoor called DinDoor, which then loads a remote access Trojan built on the Deno JavaScript runtime, according to Malwarebytes. Google AI Threat Defense targets attackers using AI to find flaws faster Google Cloud introduced AI Threat Defense, an automated cybersecurity platform that combines several of the company’s security assets to find, prioritize, and patch software vulnerabilities at machine speed. The product is aimed at enterprises contending with attackers who use AI to discover and exploit flaws in hours or days, compressing windows that once stretched into weeks. Companies built AI into core systems before figuring out how to govern it 70% of organizations use GenAI in live environments, and 64% have AI agents in pilot or production deployments. Some of those agents have privileged access to core systems, according to Check Point’s 2026 Cloud Security Report. Hottest cybersecurity open-source tools of the month: May 2026 Presented here is a curated selection of noteworthy open-source cybersecurity solutions that have drawn recognition for their ability to enhance security postures across diverse settings. Microsoft’s new cloud PCs place AI agents under enterprise controls Microsoft’s Windows 365 for Agents, a cloud PC platform for agentic workloads, runs AI agents in secure environments. Organizations can direct agents with natural language to interact with applications, browsers, files, and enterprise systems. The platform is available in public preview. Microsoft’s Copilot trust test: Zero findings, more models, wider oversight Microsoft 365 Copilot and Copilot Chat (Copilot) have been recertified under ISO/IEC 42001:2023 by an independent auditor for the second consecutive year. Copilot first received ISO 42001 certification in March 2025. This year’s recertification recorded zero non-conformities and zero improvement observations, resulting in a second audit in a row. Product showcase: TotalAV helps iOS users clean up their digital mess TotalAV Mobile Security helps protect devices from malicious websites, SMS scams, unsafe public Wi-Fi networks, and exposed credentials. The app is available for Windows, Android, macOS, and iOS devices. Microsoft 365 Copilot redesign brings context and actions into one workspace Microsoft 365 Copilot, an AI assistant that helps people write, summarize, analyze information, and complete work tasks, has been redesigned. It now serves as a single, flexible entry point to Copilot across Microsoft 365 apps, suggesting relevant actions based on the user’s work. Cybersecurity jobs available right now: May 26, 2026 We’ve scoured the market to bring you a selection of roles that span various skill levels within the cybersecurity field. Check out this weekly selection of cybersecurity jobs available right now. New infosec products of the month: May 2026 Here’s a look at the most interesting products from the past month, featuring releases from Alation, AppOmni, Apricorn, ASAPP, Babel Street, Checksum, Cogent, CTERA, Forward, LastPass, Operant AI, Riverbed, Sysdig, Trust3 AI, TrustCloud, VIAVI, Versa Networks, and XM Cyber.
helpnetsecurity.comMay 31, 2026extracted
Canonical releases Workshop for one-command sandboxed dev environments on Ubuntu
Canonical releases Workshop for one-command sandboxed dev environments on Ubuntu Canonical released Workshop, a tool that launches sandboxed development environments on Ubuntu with a single command. Environments are configured once and reproduced on different machines, giving teams consistent setups across development workstations and deployment pipelines. A terminal showing the output of the workshop launch and list commands (Source: Canonical) How Workshop defines environments Workshop environments are described in YAML files, which can be version-controlled and shared among contributors to a project. A single command creates, upgrades, or tears down an environment based on that configuration. Developers can pull SDKs into a Workshop by referencing them in the YAML, with current options including Ollama, OpenCode, NVIDIA CUDA, and AMD ROCm. The system uses an interface mechanism inspired by snapd to handle host resource allocation. Workshop provides a standardized way to access mounts, devices, and network services from inside a contained environment, removing the need for custom mapping scripts and filesystem path juggling. Where a prebuilt SDK exists for a specific hardware capability, developers can include it directly; where one does not exist, they can write a custom SDK for personal use. Sandboxing aimed at AI agent workflows Workshop runs each environment inside an unprivileged system container to reduce the attack surface exposed to workloads. Canonical has positioned the sandboxing model toward agentic AI development, where code-executing agents operate alongside human developers and require tighter access controls. SDKs in Workshop request host resources, such as desktop access for GUI applications or access to the SSH agent, through a uniform mechanism. Strict access controls can be enforced on AI agents through the same channel. “Developers operating at the cutting edge want to focus on what they’re building, not on dependencies or workstation configuration,” said Jon Seager, VP of Engineering at Canonical. “Workshop enables developers to achieve that elegantly with a single YAML file that defines their environment, and pulls the exact dependencies and components they need. Workshops also serve to standardize and sandbox agentic tooling consistently across teams.” Documentation for managing workspaces, browsing the SDK store, and building SDKs is published on Canonical’s documentation site.
helpnetsecurity.comMay 28, 2026extracted
Canonical ships Ubuntu Core 26 with 15 years of security maintenance
Canonical ships Ubuntu Core 26 with 15 years of security maintenance Operators of industrial sensors, edge AI controllers, and connected medical equipment now have a refreshed long-term Linux option for fleets that must stay patched for more than a decade. Canonical released Ubuntu Core 26, the latest long-term supported version of its minimal, immutable operating system, with security maintenance lasting up to 15 years. The release targets devices subject to the European Union’s Cyber Resilience Act and customers running attested edge AI workloads. Every component on a Core system ships as a sandboxed, cryptographically signed snap, producing a measured boot chain in which only verified software runs. Smaller updates and quicker installs Over-the-air updates are a recurring cost for operators managing large device fleets across long product lifecycles. Ubuntu Core 26 introduces an improved snap-delta format that cuts update sizes by 50% to 90% for most snaps. Updates to the Core base snaps now weigh 1.5MB, down from 16MB. Initramfs-based installations skip redundant reboots by default, shortening the time required to provision a device. Renesas worked with Canonical on integrating Core with its RZ family of microprocessor units. Mohammed Dogar, VP of the Embedded Processing Product Group at Renesas, said the combination delivers accelerated boot times and a reduced base image footprint for resource-constrained hardware running AI workloads. Chisel build system replaces layered recipes The headline engineering change is a new build system based on Chisel, Canonical’s tool for assembling filesystems from release-specific package slice definitions. Every file in a Core 26 image can be traced to its originating slice and source package, which improves the accuracy of integrity checks and vulnerability triage. The approach differs from Yocto builds, where provenance and dependency closure sit implicitly inside layered recipes and post-processing scripts. The new build path also trims base image size by 7%. Ubuntu Core 26 moves u-boot configuration to a single raw partition with redundant environment support, enabling safer writes for both u-boot and snapd and removing recovery issues tied to file-based storage. Hardware-rooted keys and CRA accountability Full disk encryption sees foundational changes in this release. TPM-sealed keys are now stored directly within the LUKS2 header, reducing the risk of key reuse across device states. Native OP-TEE integration brings ARM TrustZone hardware-rooted key protection to embedded deployments, sealing and unsealing disk encryption keys through the Trusted Execution Environment and limiting key exposure to the normal operating system. Canonical assumes Manufacturer responsibilities under the Cyber Resilience Act for the operating system’s release cycle, covering security maintenance for core modules, continuous CVE monitoring, coordinated disclosure, and compliance with IEC 62443-4-1. Livepatch, Canonical’s rebootless kernel patching service, now covers ARM64 starting with Ubuntu Core 26 and is officially supported on AMD64 across all releases from Ubuntu Core 20 onwards. The expansion extends zero-downtime kernel updates to a wider range of devices, addressing one of the CRA’s vulnerability-remediation requirements. Jon Seager, VP of Ubuntu Engineering at Canonical, said the Core security model of strictly confined components, transactional updates, and independent verifiability is reflected in emerging industry standards ten years after the platform first appeared. Developer tooling and observability Ubuntu Frame, the Core display server for embedded graphical applications, now supports multiple graphical applications on a single display, with configurable layouts, custom client placement, and a new accessibility launcher. A gpu-2604 interface brings graphics acceleration to Core 26 applications through a Snapcraft extension. Devices can stream logs and metrics to the Canonical Observability Stack, which runs on Juju and Kubernetes with Grafana, Loki, and Prometheus deployed in the cloud or on-premises. Snapcraft introduces components, a packaging feature first tested in Ubuntu Core 24 for delivering NVIDIA drivers, allowing maintainers to distribute optional resources such as debug symbols, translations, or extra drivers alongside a main snap.
helpnetsecurity.comMay 19, 2026extracted
KDE gets over €1 million investment to strengthen security and core infrastructure
KDE gets over €1 million investment to strengthen security and core infrastructure European governments and public institutions have been shifting away from proprietary software for years, and the financial infrastructure supporting open-source alternatives is growing to match. Germany’s Sovereign Tech Fund announced today that it is investing more than €1 million in KDE, the open-source project behind the Plasma desktop environment and a broad range of Linux software. The investment will go toward strengthening KDE’s testing infrastructure, security architecture, and the frameworks underpinning its communication services. KDE Linux, the project’s dedicated Linux distribution, is also listed among the targets. What KDE is and why it matters to the fund KDE has operated as a non-profit technology organization for 30 years, producing free and open-source software that runs on Linux, BSD, Windows, macOS, and Haiku. Its output includes Plasma, one of the two dominant desktop environments for Linux systems, along with document viewers, multimedia tools, image editors, and software development libraries. KDE software ships in more than 60 languages. The Sovereign Tech Fund, operated under Germany’s Sovereign Tech Agency, focuses on digital infrastructure that public administrations and enterprises depend on. Fiona Krakenbürger, Technical Director at the Sovereign Tech Agency, cited the desktop’s role as the primary access point for digital services in daily life, from medical appointment booking to workplace software. “We are investing in KDE because it is one of the two major desktop environments used across Linux and plays a key role in how millions of people experience open technology,” Krakenbürger said. Scope of the work KDE charges nothing for its software and carries no shareholder obligations. Its source code is publicly auditable, and organizations can modify and redistribute it without licensing fees or subscription costs. The project does not collect or resell user data and does not use that data to train AI models. The fund’s investment will be directed at making KDE’s core products more reliable and secure at a structural level. The stated goal is to give individuals, businesses, and public agencies a viable path to greater control over their own digital infrastructure. KDE’s patrons include Canonical, Google, SUSE, and The Qt Company, among others. The Sovereign Tech Fund has previously invested in other foundational open-source projects and publishes details of its investments publicly at sovereign.tech.
helpnetsecurity.comMay 13, 2026extracted
Fake Claude Code Page Pushes PowerShell Stealer at Devs
A previously undocumented information stealer has been distributed through fake Claude Code installation pages, hijacking Chromium browsers to bypass App-Bound Encryption and exfiltrate cookies, passwords and payment data from developer workstations. The campaign was detailed on 11 May by Ontinue's Cyber Defense Center, which traced the activity to three operator-controlled domains registered within a six-day window in April 2026. Victims arrived at the lookalike installation page after clicking sponsored search results for "install claude code." The lure page mimicked the layout of legitimate Claude Code documentation but rendered an altered one-line installation command directly in HTML, swapping the canonical Anthropic host for an attacker-controlled domain. The /install.ps1 file at that domain returned a verbatim copy of the genuine installer, making automated URL scanners observe entirely clean PowerShell while the visible command on the page sent victims elsewhere. A Native Helper Designed to Evade Behavioral Rules Once executed, the pasted command fetched a heavily obfuscated PowerShell loader of approximately 600 KB. The loader enumerated Chromium-family browsers, including Chrome, Edge, Brave, Vivaldi, Perplexity Comet and Arc, and reflectively injected a 4608-byte native helper into a live browser process. The helper's sole function is to invoke the browser's IElevator2 COM interface, introduced in Chrome 144, to recover the App-Bound Encryption key. The technique mirrors the approach first documented in Glove Stealer in late 2024, but diverges in design. Ontinue, a provider of AI-powered managed agentic SOC services, noted that the helper exposes no network, file or cryptographic imports. All detection-visible activity, such as SQLite access, archive construction and HTTPS exfiltration, was confined to the PowerShell layer. The split appeared engineered specifically to defeat behavioral rule sets that inspect native binaries in isolation. Developer Workstations as a High-Value Pivot Ontinue's compile-date evidence places the sample's construction within 60 days of the Chrome 144 release in January 2026, indicating an actively maintained development effort tracking upstream Chromium changes. A transcription error in the embedded Edge IElevator2 IID, with two nibbles transposed in the Data3 field, causes the initial call to fail silently and trigger a fallback to the legacy IElevator interface. Ontinue highlighted that the malformed identifier doubles as a high-confidence detection signature. The loader established persistence via a Windows scheduled task that polled the operator's C2 every minute and exited early if the host's region matched an exclusion list covering Iran, Russia and other Commonwealth of Independent States (CIS) members, among others. Vineeta Sangaraju, AI tesearch engineer at Black Duck, said the choice of target is what makes the campaign worth attention. "Developers hold the keys to an organization's most sensitive assets - intellectual property, cloud infrastructure, CI/CD pipelines," she said. "One compromised developer workstation does not stay contained. It pivots into source code repositories, into cloud environments and into downstream software." Ontinue urged defenders to enforce PowerShell Constrained Language Mode, enable script block logging and apply web content filtering against newly registered domains.
infosecurity-magazine.comMay 11, 2026extracted
⚡ Weekly Recap: AI-Powered Phishing, Android Spying Tool, Linux Exploit, GitHub RCE & More
This week, the shadows moved faster than the patches. While most teams were still triaging last month’s alerts, attackers had already turned control panels into kill switches, kernels into open doors, and open-source pipelines into silent delivery systems. The game has shifted from breach to occupation. They’re living inside SaaS sessions, pushing code with trusted commits, and scaling operations like legitimate businesses — except their product is chaos. And the underground is getting uncomfortably professional. Here’s the full weekly cybersecurity recap: ⚡ Threat of the Week cPanel Flaw Comes Under Attack—A critical flaw in cPanel and WebHost Manager (WHM) has come under active exploitation in the wild. The vulnerability, tracked as CVE-2026-41940, could result in an authentication bypass and allow remote attackers to gain elevated control of the control panel. In some cases, the attacks have led to a complete wipe of entire websites and backups. Other attacks have deployed Mirai botnet variants and a ransomware strain called Sorry. Is Your Security Program Built on Compliance Theater or Measurable Maturity? If you can't measure your program's maturity, you can't improve it or defend its budget. The SANS Security Awareness & Culture Maturity Model™️ maps 5 stages of security culture development with concrete indicators, behavioral targets, and alignment to business risk priorities. Download Now — Free ➝ 🔔 Top News Cybercrime Groups Use Vishing for Data Theft and Extortion—Two cybercrime groups tracked as Cordial Spider and Snarky Spider are carrying out "rapid, high-impact attacks" operating almost within the confines of SaaS environments, while leaving minimal traces of their actions. The groups employ voice calls, text messages, and emails, directing targeted employees to phishing pages masquerading as their employer's legitimate single sign-on (SSO) page to capture credentials and provide attackers an entry point into systems, which they exploit for deeper access to victims' SaaS environments. The attacks also use the initial access hooks to remove and set up multi-factor authentication devices under their control and delete emails that would otherwise alert organizations of potential malicious activity. According to CrowdStrike, "These actors use vishing to bypass MFA and move laterally across entire SaaS ecosystems with a single authenticated session, masking their tracks through residential proxy networks to blend in as legitimate home user traffic. This is part of a larger trend of English-speaking ransomware crews that share similar playbooks but are branching off into their own distinct groups." Copy Fail Linux Flaw Exploited—The U.S. Cybersecurity and Infrastructure Security Agency (CISA) added CVE-2026-31431, a vulnerability impacting various Linux distributions, to its Known Exploited Vulnerabilities (KEV) catalog, citing evidence of active exploitation in the wild. It's described as a logic bug in the Linux kernel's authentication cryptographic template that allows an attacker to reliably trigger privilege escalation trivially by means of a 732-byte Python-based exploit. According to Theori and Xint, CVE-2026-31431 was the result of a series of unremarkable updates to the Linux kernel over the years, particularly one update from 2017 that was meant to speed up data encryption. As a result, all major Linux distributions from 2017 are impacted. What complicates matters is that Copy Fail works 100% of the time, unlike most local privilege escalation (LPE) bugs that tend to be probabilistic in nature. More worryingly, it leaves no traces on disk as exploitation occurs in memory and enables container escape from any pod in a Kubernetes cluster. TeamPCP's Supply Chain Attack Spree Continues—TeamPCP's extensive supply chain campaign continued last week, as the cybercriminal group compromised several packages across the npm, PyPI, and Packagist ecosystems in a "Mini Shai-Hulud" attack. TeamPCP has in recent months compromised the packages of several open source software projects, including Trivy, a security scanner maintained by Aqua Security, and KICS, a Checkmarx-developed tool for static code analysis. Amit Genkin, threat researcher at Upwind, said the latest string of attacks represents a shift, where they are not only more frequent but harder to detect because they weaponize legitimate CI/CD pipelines to push out poisoned versions under real identities, allowing the activity to blend in with normal development workflows. "Campaigns like Shai-Hulud take that further by using each compromised pipeline to spread to the next, turning credential theft into a scaling problem across environments," Genkin said. "For teams, the immediate priority is to check for the affected version and rotate any credentials tied to pipelines that may have run it, especially GitHub and cloud tokens. Longer term, this is a signal to reduce how broadly pipeline credentials are scoped and to add visibility into what's actually happening during installs and builds – because if you're relying on traditional scanning or known indicators, this type of activity is easy to miss." New Python Backdoor Enables Comprehensive Data Theft—A newly identified stealthy Python-based backdoor framework dubbed DEEP#DOOR provides attackers with persistent remote command execution and surveillance capabilities on Windows computers. Once active, the backdoor enables shell command execution, file manipulation, system and network reconnaissance, and surveillance operations such as keylogging, clipboard monitoring, screenshot capture, microphone and webcam access, and credentials and SSH key harvesting. Additionally, the malware can shift from data gathering to disruption and system manipulation, as it can overwrite the Master Boot Record, force system crashes, exhaust system resources by spawning numerous processes, and disable Microsoft Defender services. GitHub Flaw Leads to Remote Code Execution—Cybersecurity researchers from Wiz disclosed details of a critical security vulnerability impacting GitHub.com and GitHub Enterprise Server (CVE-2026-3854, CVSS score: 8.7) that could allow an authenticated user to obtain remote code execution with a single "git push" command. The vulnerability was severe enough that Microsoft rolled out a patch within six days of responsible disclosure. On GitHub.com, it allowed remote code execution on shared storage nodes, and on GitHub Enterprise Server, it granted full server compromise, enabling unauthorized access to all hosted repositories and internal secrets. "Exploitation could expose the codebases of nearly all of the world's biggest enterprises, making this one of the most severe SaaS vulnerabilities ever found," a Wiz spokesperson told The Hacker News. VECT 2.0 Ransomware's Flawed Encryption Makes Data Recovery Impossible—VECT 2.0 ransomware has been found to wipe large files instead of merely encrypting them, making recovery impossible, even for the attackers. VECT 2.0 is a ransomware-as-a-service (RaaS) program that first appeared in December 2025. The group quickly grabbed headlines after it announced on BreachForums that it was partnering with TeamPCP, the threat group behind several supply chain attacks, such as Trivy, Checkmarx KICS, LiteLLM, and Telnyx, in March and April 2026. VECT also announced a partnership with BreachForums itself, promising that every registered forum user will become an affiliate and be granted use of the ransomware, negotiation platform, and leak site for operations. Beazley Security, in an analysis of the ransomware, said the VECT 2.0 RaaS panel covers the "full operational lifecycle an affiliate needs from payload generation through to payout." 🔥 Trending CVEs Bugs drop weekly, and the gap between a patch and an exploit is shrinking fast. These are the heavy hitters for the week: high-severity, widely used, or already being poked at in the wild. Check the list, patch what you have, and hit the ones marked urgent first — CVE-2026-41940 (cPanel and WebHost Manager), CVE-2026-31431 aka Copy Fail (Linux Kernel), CVE-2026-42208 (LiteLLM), CVE-2026-3854 (GitHub.com and GitHub Enterprise Server), CVE-2026-32202 (Microsoft Windows Shell), CVE-2026-26268 (Cursor), CVE-2026-35414 (OpenSSH), CVE-2026-6770 (Mozilla Firefox and Tor Browser), CVE-2026-42167 (ProFTPD), CVE-2026-24908, CVE-2026-23627, CVE-2026-24487 (OpenEMR), CVE-2026-6807 (GRASSMARLIN), CVE-2026-7363, CVE-2026-7361, CVE-2026-7344, CVE-2026-7343 (Google Chrome), CVE-2026-7322, CVE-2026-7323, CVE-2026-7324 (Mozilla Firefox), CVE-2026-6100 (CPython), CVE-2026-0204 (SonicWall), CVE-2026-35414 (OpenSSH), CVE-2026-42511 (FreeBSD), CVE-2026-40684, CVE-2026-40685, CVE-2026-40686, CVE-2026-40687 (Exim), CVE-2026-5402, CVE-2026-5403, CVE-2026-5405, CVE-2026-5656 (Wireshark), CVE-2026-42520, CVE-2026-42523, CVE-2026-42524 (Jenkins), CVE-2026-3008 (Notepad++), and CVE-2025-41658, CVE-2025-41659, CVE-2025-41660 (CODESYS). 🎥 Cybersecurity Webinars Learn to Spot Attack Paths Your AppSec Tools Completely Miss → Modern attackers chain tiny flaws across code, pipelines, and cloud into major breaches — while your AppSec tools stay blind. Join this free webinar with Wiz and The Hacker News to uncover the top real-world attack paths and learn exactly how to spot, map, and stop them fast. Practical insights to prioritize real risks and strengthen your entire software lifecycle. How to Match AI Attack Speed with Autonomous Exposure Validation → Struggling with AI attacks moving faster than your team can respond? Join this free webinar from Picus Security & The Hacker News to discover Autonomous Exposure Validation – how to automatically find real risks, test attack paths, and fix them in minutes, not weeks. Practical, no-fluff insights to stay ahead without burnout. Grab your spot now. Learn Latest AI Threats + Practical Ways to Kill Initial Access → Modern attackers are slipping past traditional defenses with AI-powered phishing, encrypted malware, and stealthy “Patient Zero” tactics. Want to stay ahead? Join this free webinar with Zscaler and The Hacker News to uncover the latest threat trends and practical Zero Trust strategies that actually stop initial compromise — before it becomes a full-blown breach. No fluff, just real insights to protect your organization. 📰 Around the Cyber World OpenAI Debuts Advanced Account Security —OpenAI launched Advanced Account Security, a set of opt-in protections for ChatGPT users "designed for people at increased risk of digital attacks, as well as for those who want the strongest account protections available." As part of the new program, the new controls strengthen sign-in protections, tighten account recovery, reduce exposure from compromised sessions, and give users more visibility into account activity. OpenAI has also partnered with Yubico to link two physical security keys, YubiKey C Nano and YubiKey C NFC, to ChatGPT accounts. That said, users can use any other FIDO-compliant security key, or use software-based passkeys for phishing-resistant authentication. Over 8.8K Ransomware Attacks in 2025 —Fortinet said it recorded 7,831 confirmed ransomware victims globally in 2025, skyrocketing from approximately 1,600 identified victims in 2024. "Availability of crime service kits like WormGPT, FraudGPT, and BruteForceAI contributed to this 389% increase year-over-year (YoY)," Fortinet said. "The top three targeted sectors include manufacturing (1,284), business services (824), and retail (682). Geographic concentration includes the U.S. (3,381), Canada (374), and Germany (291)." KidsProtect Android Surveillance Tool Marketed on the Web —A new Android surveillance tool called KidsProtect is being openly advertised on the clear web that gives an operator near-total secret control of a victim’s phone. "It can't be removed without the attacker's permission," Certo said. "From a web-based dashboard, an operator can secretly record calls, stream live audio from the device’s microphone, track GPS location in real time, read SMS messages and notifications from apps including WhatsApp and Viber, log keystrokes, access contacts and photos, and remotely trigger the front and rear cameras." Assessed to be the work of a Greek-speaking developer, it's available on a subscription basis starting from $60, allowing anyone to buy it, rebrand it, and start selling it as their own. New KYCShadow Android Malware Detected —An Android malware masquerading as a bank KYC verification application is being distributed via WhatsApp and primarily targeting users in India. "The application operates as a multi-stage dropper that installs a secondary payload and establishes persistent command-and-control (C2) communication," CYFIRMA said. "It combines native code obfuscation, Firebase-based remote execution, VPN-based traffic manipulation, and WebView-based phishing to systematically harvest sensitive user data." Phishing Campaign Targets Pakistan Orgs —A highly targeted spear-phishing campaign targeting the Punjab Safe Cities Authority and PPIC3 in Pakistan has been found to use legitimate-sounding government infrastructure projects as lures to deliver malware. "The email carried two malicious attachments: a Word document with a VBA macro dropper and a PDF with a fake Adobe Reader lure, both delivering payloads from a BunnyCDN-hosted malicious infrastructure," Joe Security said. "The attack chain establishes persistent remote access by abusing Microsoft's legitimate VS Code tunnel service, with exfiltration notifications sent via a Discord webhook — a sophisticated technique designed to evade network-level detection." Calendly-Themed Phishing Attacks on the Rise —Multiple threat clusters are leveraging Calendly-themed phishing to fingerprint site visitors and steal credentials and other data. "Behind the shared Calendly branding sits a diverse set of phishing kits, including API-driven frameworks, real-time Socket.IO applications, fake CAPTCHA chains, and Telegram-based exfiltration," urlscan said. Fraud Campaigns GovTrapand FEMITBOT Exposed —Threat actors have been observed deploying sophisticated tactics, including fake government portals, SMS phishing, and lookalike domains, to drive financial fraud and credential harvesting as part of an effort called GovTrap. The government impersonation scam mimics official portals with high accuracy, with links to the fake sites distributed via SMS or email. The end goal is to trick users into entering their personal and financial information, or make non-existent payments that are transferred through money mule accounts. The collected payment card details are abused to facilitate fraudulent transactions. Another threat cluster has leveraged FEMITBOT, a malicious infrastructure that abuses Telegram Mini Apps to scale global fraud campaigns and Android malware delivery. "By leveraging Telegram's native features, threat actors create highly convincing fake platforms across crypto, financial services, AI, and streaming sectors," CTM360 said. "Built on a modular, template-driven architecture, FEMITBOT enables rapid deployment, brand impersonation, and campaign optimization using real-time tracking and analytics." New PowerShell Desktop Stealer Spotted —A Pastebin-hosted PowerShell script disguised as "Windows Telemetry Update" comes with capabilities to steal Telegram Desktop session data via Telegram bot API exfiltration. "The script collects host metadata, including username, hostname, and public IP via api.ipify[.]org, then checks for Telegram Desktop and Telegram Desktop Beta tdata directories," Flare said. "If found, it terminates the Telegram process to release file locks, archives session material into 'TEMP\diag.zip,' and uploads the archive to the attacker-controlled operator chat via the Telegram Bot API sendDocument endpoint." Surge in Teams Phishing in 2026 —eSentire said it has observed an increase in Microsoft Teams-based phishing since early 2026, in which threat actors impersonate IT support and help desk personnel to trick users into granting remote access to their devices. "These phishing attacks have often been linked to email bombing, followed by threat actors reaching out to users under the guise of providing assistance to resolve an issue," eSentire said. "The objective of the attack is to trick the user into granting remote access to their device, and once obtained, threat actors will attempt to exfiltrate data and execute additional payloads to establish persistence or deploy ransomware." New KarstoRAT Malware Enables Data Theft —First spotted in early 2026, KarstoRAT is capable of system reconnaissance, audio and webcam monitoring, screenshot capture, key logging, and token theft. It also enables threat actors to download and run additional payloads, which could point to it being used for post-compromise control on infected machines. "KarstoRAT uses a command-and-control (C2) server that has a diverse set of open ports and services, indicating that it has a multi-purpose infrastructure created for C2 communication and payload distribution," LevelBlue said. "Threat actors use a fake Blox Fruits (a popular Roblox game) virtual marketplace as a lure to trick players into downloading malware that will install KarstoRAT into their machines." ClickUp Discloses Email Address Exposure —ClickUp said its client-side feature flag configuration exposed personally identifiable information. This included 893 customer email addresses that were embedded in feature flag targeting rules, along with one flag that improperly referenced a customer’s API token. "The exposure was limited to 893 customer email addresses used in feature flag targeting rules to control which users see specific features during rollouts," it said. "If your email address was among those included in a feature flag configuration, you have been directly contacted." The incident did not expose any other data. Finnish Authorities Arrest Alleged Scattered Spider Member —Finnish authorities arrested 19-year-old Peter Stokes (aka Bouquet), a dual U.S.-Estonian citizen, as he tried to board a flight to Japan. U.S. prosecutors have charged him as a key member of the notorious Scattered Spider hacking group, and he faces multiple counts of wire fraud, conspiracy, and computer intrusion. New Attacks Linked to Versatile Werewolf —The threat actor known as Versatile Werewolf (aka HeartlessSoul) has been linked to campaigns targeting Russian state structures and aviation companies via phishing emails with malicious archive attachments and malvertising campaigns to deliver a JavaScript trojan. The end goal is to obtain confidential data, particularly geospatial information. Alternatively, the threat actor is known to distribute malicious code using the legitimate SourceForge platform through a project called GearUP. Versatile Werewolf is believed to be active since at least September 2025. Some of the attachments have exploded ZDI-CAN-25373 to trigger the infection chain. The malvertising campaign uses fake domains ("battleflight[.]pro") to deliver bogus installers for aviation-related software to launch the same trojan. "The initial infection involves executing PowerShell commands or scripts designed to download a JavaScript loader from C2 servers," Kaspersky said. "This loader, in turn, loads and executes the main JS-RAT and its modules in memory, among which we found tools for data collection and exfiltration, keyloggers, screen capture tools, UAC bypass tools, and other payloads." The company noted that the domain "battleflight[.]pro" resolves to an IP address that also hosts fake domains linked to the GOFFEE APT. "Both groups actively use PowerShell payloads to deliver and execute malicious modules," it added. "GOFFEE also targets the public sector, which suggests the possibility of joint or coordinated campaigns." Cisco Unveils Model Provenance Kit —Cisco unveiled a new open-source tool, named Model Provenance Kit, to help organizations address potential issues associated with the use of third-party AI models. "Much like a DNA test reveals biological origins, the Model Provenance Kit examines both metadata and the actual learned parameters of a model (like a unique genome that comprises a model), to assess whether models share a common origin and identify signs of modification," Cisco said. "This, combined with a constitution that defines provenance linkages, is an important step toward providing evidence-based assurance that the AI you deploy is what it says it is." Abuse of Hugging Face and ClawHub for Malware Delivery —Threat actors are abusing legitimate AI platforms like Hugging Face and ClawHub for malware delivery, once again demonstrating how trust in AI ecosystems are being exploited. Acronis said it identified more than 575 malicious skills across 13 developer accounts that target both Windows and macOS systems with trojans, cryptocurrency miners, and AMOS stealer, a macOS-focused infostealer. "On Hugging Face, attackers leverage repositories to host payloads and act as staging infrastructure within multistep infection chains, distributing malware disguised as legitimate applications," Acronis said. European Authorities Bust Cryptocurrency Fraud Ring —Albanian and Austrian authorities dismantled a cryptocurrency investment fraud ring that caused estimated losses of more than €50 million ($58.5 million) to victims worldwide. The operation, which took place over two years, resulted in the arrest of ten individuals, the search of multiple premises, and the seizure of 891,735 in cash, 443 computers, 238 mobile phones, six laptops, and multiple storage devices. "The criminal network, allegedly operating several call centres in Tirana, Albania, is believed to have caused significant financial damage, totalling at least €50 million," Europol said. "The call centres were professionally set up and organized, resembling legitimate business structures featuring a clear division of roles and hierarchical management." The criminal network is estimated to have involved up to 450 employees across various departments. The scheme involved luring victims to seemingly legitimate online investment platforms through deceptive advertisements on social media or web searches, and coaxing them into making investments under the promise of huge returns. Victims were then assigned retention agents, who masqueraded as investment advisors and used remote access software to gain full control of their devices. "The fraudsters feigned professional expertise and employed psychological pressure to persuade victims to make additional investments, falsely claiming they would be profitable," Europol said. "In truth, the funds were never invested but were instead channelled into an intricate international money-laundering scheme, ultimately disappearing into the hands of the criminal organisation." In some cases, the fraudsters reached out to the victims again and offered help with recovering their stolen funds, only to demand a €500 entry fee and defraud them a second time. Flaws in EnOcean's SmartServer —Two security flaws have been disclosed in EnOcean's SmartServer IoT platform that affect version 4.60.009 and prior. According to Claroty: "CVE-2026-20761 allows remote attackers to send malicious, crafted LON IP-852 messages that result in arbitrary command execution on devices. CVE-2026-22885 allows remote attackers to send malicious, crafted IP-852 messages that bypass ASLR memory protections and leak memory." Successful exploitation of the flaws results in attackers obtaining control over building management and building automation systems running affected versions of this platform and legacy i.LON devices. Patches have been released for both vulnerabilities. Google Announces Android Credential Manager Update —Google has announced a new update to Android's Credential Manager that allows apps to automatically verify a user's personal Gmail address without requiring one-time passwords (OTPs) or email verification links. "Google now issues a cryptographically verified email credential directly to Android devices," the company said. "For users, this completely removes the need to manually verify their email through external channels. For developers, the API securely delivers these verified user claims for any scenario, whether you are building an account creation flow, a recovery process, or a high-risk step-up authentication." Nearly 8.8K Secrets Leaked Online —According to Truffle Security, 8,792 verified, unique secrets have been leaked online through web-based development environments. The tokens were found across 22 million public projects hosted on Cloud Development Environments (CDEs) such as CodePen, CodeSandbox, JSFiddle, and StackBlitz. Is There More to the Xygeni Compromise? —Multiple connections have been found between the compromise of the Xygeni vulnerability scanner on GitHub and a proxy botnet of hacked ASUS and TP-Link routers. Some of the TP-Link consumer routers have been compromised with Microsocks to unroll them to a residential proxy network. "These routers were also running a custom command-and-control beacon that was named ShadowLink," Ctrl-Alt-Intel said. "When we analysed the ShadowLink protocol, we found it was identical, down to a shared authentication secret, to the backdoor planted in the Xygeni GitHub Action used for that supply chain attack." Brazilian Anti-DDoS Firm Behind DDoS Attacks on ISPs —Huge Networks, a Brazilian tech company that specializes in protecting networks from distributed denial-of-service (DDoS) attacks, has been enabling a botnet responsible for massive DDoS attacks against other internet service providers (ISPs) in the country, according to KrebsOnSecurity. The company has since said the malicious activity resulted from an intrusion first detected in January 2026 and claimed it was likely the work of a competitor. Canonical Target of Sustained DDoS Attack —Canonical disclosed its web infrastructure came under a "sustained, cross-border attack," knocking Ubuntu servers offline for several hours. A pro-Iranian hacktivist group known as the Islamic Cyber Resistance in Iraq, aka 313 Team, claimed responsibility for the attack on Telegram. The websites have since become operational. Last month, the group also disrupted access to the decentralized social media platform Bluesky. New Phishing Kit Bluekit Detailed —A new phishing kit named Bluekit is offering more than 40 templates targeting popular services and includes basic artificial intelligence (AI)-powered features for generating campaign drafts. Available templates can be used to target email accounts (Outlook, Hotmail, Gmail, Yahoo, ProtonMail), cloud and enterprise services (iCloud and Zoho), developer platforms (GitHub), and cryptocurrency services (Ledger). What makes the kit stand out is the presence of an AI Assistant panel that supports multiple models, including Llama, GPT-4.1, Claude, Gemini, and DeepSeek, to help criminals draft phishing emails. It also has support for two-factor authentication, geolocation emulation, antibot cloaking, notifications, spoofing capabilities, voice cloning, and a mail sender. The development once again reinforces the broader trend of crimeware services integrating AI to streamline and scale their operations. Bluekit is the second kit to integrate AI features in as many months. In April 2026, Abnormal Security shed light on a cybercrime platform called ATHR that uses AI vishing agents, credential harvesting panels, and built-in phishing mailers to execute and scale telephone-oriented attack delivery (TOAD) attacks. North Korea Calls U.S. Cyber Threat Claims a Fabrication — North Korea's foreign ministry rejected U.S. accusations that the country poses a cyber threat, stating the U.S. was spreading false information about a non-existent cyber threat from North Korea for political purposes, per Reuters. The ministry said it "would actively take all necessary measures for defending the interests of the state and protecting the rights and interests of its citizens in cyberspace." 🔧 Cybersecurity Tools Model Provenance Kit → It is a free open-source Python tool from Cisco AI Defense that helps identify if a machine learning model is based on a known base model (like Llama, Mistral, GPT, etc.). It analyzes architecture, tokenizer, and weights to quickly compare two models or check against a database of ~150 popular base models. AutoFyn → It is an open-source tool from SignalPilot Labs that runs Claude AI in self-improving loops to optimize measurable goals. Give it a GitHub repo, a clear task (like security hardening, bug fixing, or performance optimization), and a time budget — it works in sandboxed rounds, tracks progress with real evaluations, learns from failures, and delivers improved code via PRs. Disclaimer: This is strictly for research and learning. It hasn't been through a formal security audit, so don't just blindly drop it into production. Read the code, break it in a sandbox first, and make sure whatever you’re doing stays on the right side of the law. Conclusion Stay sharp out there. The pace of attacks is accelerating, and the margin for delay is shrinking. Patch what you can today, verify your supply chains, tighten SaaS access, and treat every “routine” login or pipeline run as potentially hostile. Small habits now will save major headaches later. Until next Monday. Keep your defenses tight and your eyes open. The threats won’t wait — neither should we. See you in the next recap.
thehackernews.comMay 4, 2026extracted
The 2026 World Cup scam economy is already running before the first whistle
The FIFA World Cup 2026 is scheduled to begin June 11 across the US, Canada, and Mexico. The web is filling with sites impersonating ticket vendors, telecoms, sticker publishers, toy manufacturers, immigration services, and crypto projects, all linked to the World Cup brand. Together, they map out four recurring patterns of fraud and risk targeting fans. What World Cup fans need to know If you’re planning anything around the 2026 World Cup, whether it’s buying a ticket or merchandise, booking a flight, applying for a US visa, or speculating on “World Cup” crypto, expect a surge in scams and other risky World Cup-related activity. The good news is the patterns are obvious once you know what to look for: Countdown timers that reset when you reload the page Prices 80–90% below retail The word “official” used without a clear link to the brand behind it Crypto tokens claiming to be “official” World Cup products Your headline rule for the next two months: If a site uses the World Cup or a known brand to get your money, stop and verify it from the official source before you do anything else. How these World Cup scams work The path to these scam sites is almost always the same: a fan searches for something on search engines or social media (for example, “World Cup 2026 jersey,” “buy Panini sticker album,” “visa to attend the World Cup,” “FIFA World Cup token”) and lands one of the hundreds of sites set up to exploit that demand. Often the route there runs through an ad network. That might involve a sponsored search result, a banner on an unrelated site, or a redirect chain that sends the victim to a different domain than the one they clicked. (Note that tools like Malwarebytes Browser Guard can block malicious ads, scam domains, and redirect chains before the page loads.) The branding on the destination site is consistent with the legitimate company. There are testimonials and satisfied-customer counts, so nothing looks immediately wrong. Urgency tricks like “Only a few items left” and the countdown timer are there to prevent you from looking too closely or investigating too deeply. We’ve found these sites group naturally into four categories: crypto, travel, merchandise, and predictors. The sites in each category have their own tells, but they’re united by brand parasitism: borrowing authority from FIFA, the host nations, or a real licensee like LEGO or Panini. Crypto The most crowded category is crypto, and the biggest risk comes from sites that claim or imply official links to the World Cup. One site marketed its token as “the official community token celebrating the FIFA World Cup 2026,” advertising a “Mega Airdrop,” a 7-billion-token total supply, and a participant counter pinned to the symbolic number 48 (the count of qualified national teams). Another shows FIFA’s official mascot, using tournament branding to sell an unlicensed token. None of the sites we examined are connected to FIFA. FIFA does have a real digital-collectibles ecosystem—the FIFA Collect NFT marketplace, the Right-to-Buy ticket NFTs, and the FIFA Rivals game on the Mythos chain—all of which sit on FIFA-controlled infrastructure and are documented at FIFA’s own domains. None of the sites we examined sit inside that ecosystem. The real partners for 2026 are documented and easy to verify. “World Cup token” is not one of them. We found multiple sites using FIFA branding to create a false sense of legitimacy. But there’s a real risk you’ll receive nothing, receive something you can’t sell, or sign a transaction that gives the operator access to your wallet. Some sites don’t pretend to be official, but still carry risk to World Cup fans. One Solana-based token branded itself the “World Cup Rug Index,” with the tagline “Every match is a market. Every loss is a rug,” and a contract ending in “pump,” the signature of pump.fun launches. In crypto, a “rug” is when early holders sell and the price collapses, leaving later buyers with losses. These projects are not scams in the sense of pretending to be something they’re not. They are openly speculative. The risk is in the structure: early buyers can sell into demand from later buyers, who are left holding the losses. This is different from the fake “World Cup tokens” above. Those rely on FIFA branding to create a false sense of legitimacy. These rely on momentum, where most participants arrive late. Travel The most dangerous category is the “World Cup visa.” One site, WC2026 Visa, advertised a “Visa to the World Cup 2026 US” for $270 per person, with a “98% Success Rate,” a countdown to June 11, and the standard reassuring trio: “Secure Process,” “Fast Processing,” “18+ only.” There is no such product. The US Department of State has stated this directly: there is no special tournament visa. Foreign visitors traveling to the United States for the World Cup must use the same B1/B2 visitor visa, or the Visa Waiver Program with an ESTA authorisation, that any other tourist would. The only tournament-specific visa programme is FIFA PASS (the Priority Appointment Scheduling System), a routing mechanism that gives ticket holders earlier interview slots at US consulates. It doesn’t bypass the interview, it doesn’t issue a visa, it doesn’t cost $270, and access to it begins with buying a ticket directly from FIFA. A site advertising a dedicated “World Cup visa” tricks people into believing they’re going down an official immigration pathway. Any personal data harvested in the process, such as passport details, date of birth, travel plans, and in some flows a payment instrument, gives the operator all the data they need for identity theft. Fans should only apply through .gov sites in the US, .gc.ca in Canada, and .gob.mx in Mexico. Travel portals aggregating tickets, flights, and hotels, and eSIM sites selling connectivity for the tournament are not inherently fraudulent and are often real businesses. But any site invoking the World Cup deserves the same scrutiny: who actually fulfils this product, what is the refund policy in writing, and is this domain legitimately connected to a known brand or partner? Merchandise The merchandise category is where the impersonation gets most aggressive, because there are real licensees to imitate. LEGO’s partnership with FIFA is genuine, announced in late 2025. It debuted with the LEGO Editions FIFA World Cup Official Trophy, joined in 2026 by player sets featuring Messi, Ronaldo, Mbappé, and Vinicius Jr. A whole cluster of LEGO-styled scam storefronts now prices the trophy set at €29.99, marked down from €299.99, an 83–90% discount. LEGO does not discount its premium licensed sets by 90%. Related to those storefronts is the “LEGO FIFA World Cup 2026 Quiz Challenge” pattern, promising “exclusive edition rewards” for fans who complete a quiz. Quiz-funnel scams are a long-running affiliate-marketing genre, and the typical mechanic is to harvest contact information and push the user toward a subscription billing flow disguised as a shipping fee for the “prize.” LEGO does not run quiz funnels. Its real World Cup activity runs through LEGO.com and physical LEGO stores. Counterfeit jersey storefronts have been a fixture of the open web for years, and the World Cup cycle multiplies them. Typical examples: a site branded simply “JERSEY 2026 World Cup” selling a Portugal home shirt with a “BUY 2, PAY FOR 1” overlay, a 30-day countdown, and a Trustpilot-shaped widget claiming over ten thousand satisfied customers; or a retro-jersey storefront offering Germany and Argentina shirts at $24.90 each. Search demand spikes during a World Cup year and counterfeit storefronts spin up to meet it; many will be offline shortly after the tournament ends. Then there is the Panini-styled storefront pattern: pages advertising the official 2026 sticker album under headers like “ONE-TIME PURCHASE BY NIF” (NIF being the Portuguese personal tax identifier, a phrase that appears nowhere in legitimate Panini commerce). These pages combine sub-ten-minute countdowns, inventory counters (“There are still 127 Units”), and country-specific scarcity claims (“Only 5,000 units available for Portugal!”). The high-pressure funnel and unusual NIF framing point to localised affiliate or look-alike storefronts, not Panini’s own commerce flow, which runs through paninistore.com and licensed retail. These are not Panini storefronts. They are look-alike commerce flows using Panini’s brand to sell through high-pressure funnels. Whether the product arrives or not, the user is not buying from the company they think they are. Predictions and prize pools “WorldCup Predictor” sites present a prize pool that supposedly grows with every prediction, and ask users to select a champion team from flag tiles. You are paying for entries into a pooled outcome tied to the tournament. These sites are not pretending to be something they’re not. The risk is that they operate without clear oversight. There is no visible licensing, no clear jurisdiction, and no way to verify from the front end whether payouts are enforced or even guaranteed. Licensed sportsbooks and regulated platforms typically do not present themselves this way. They identify their licensing authority, provide responsible gambling tools, and use verified payment processors. A “Login to play” button, a flag picker, and a floating prize pool are not the same thing. What FIFA, the brands, and the platforms could be doing better Many of these sites would not exist, or would be far shorter-lived, if a few things changed upstream. Brand owners with active 2026 partnerships—LEGO, Panini, the national federations, the kit manufacturers—could reduce confusion by publishing a single canonical page each, well before kickoff, listing authorized retailers and the exact SKUs and prices of their World Cup products. Someone trying to verify whether a €29.99 LEGO trophy is real should not have to triangulate between Brickset, LEGO’s newsroom, and a third-party blog. FIFA’s own licensing communications have improved compared with past tournaments, and the LEGO and Panini announcements were clearly disclosed on inside.fifa.com. But the gap between “FIFA has announced a partnership” and “here are the only sites authorized to sell on FIFA’s behalf” remains wide. Closing it would make impersonation much harder. Search engines and ad networks carry a large share of the structural responsibility. Visa-impersonation pages are precisely the kind of sites that surface through paid search ads against terms like “world cup visa,” and platforms have the data to detect and block them at scale. What to do if you may have been caught Every World Cup cycle generates its own scam economy. 2018 had fake ticket marketplaces; 2022 leaned on phishing around Qatar’s Hayya system; 2026 is building around meme coins and visa impersonation. What’s different this time is the speed: sites can be spun up, monetized, and abandoned within weeks, and AI-generated copy, mascot art, and product images have stripped away many of the visual cues people used to rely on. This cycle’s scam economy moves fast, but the basics still work: treat unsolicited “World Cup” links with suspicion, type official domains yourself, and ignore pressure from countdown timers. If you think you’ve been caught: If you entered card details: Contact your card issuer immediately and request a refund for an unauthorized or non-delivered transaction. If you submitted personal or passport data: Treat it as compromised. Monitor your credit, place a fraud alert if available, and watch for targeted phishing. If you connected your crypto wallet or signed a transaction: Revoke permissions, move remaining assets to a new wallet, and stop using the old one for anything valuable. If you bought goods that weren’t delivered: Keep your order confirmation, URL, and payment record. Report it to your national consumer protection body (FTC in the US, Action Fraud in the UK, or your local equivalent). Always verify through official channels. That’s FIFA.com for tickets, paniniamerica.net or paninistore.com for stickers, LEGO.com for LEGO Editions sets, and official government sites for visas. Remember, legitimate sources do not rely on countdown timers. Stop threats before they can do any harm. Malwarebytes Browser Guard blocks phishing pages and malicious sites automatically. Free, one click to install. Add it to your browser →
malwarebytes.comMay 4, 2026extracted
Pro-Iran crew turns DDoS into shakedown as Ubuntu.com stays down
SAAS Salesforce partners not seeing meaningful revenue from Agentforce AI platform, report saysShow us the money ai and ml AI companies are burning books, advocates complain to FTCFahrenheit 203, the temperature GPUs stop gorging on literature DEVOPS Go updates may delight diehard gophers but displease AI overlordsv 1.27 expands generics to support methods EDGE AND IOT Waymo has designed a robocar chip to stay ahead of Tesla5 nm ML accelerators promise 1,000+ TOPS, ultra-low latency SYSTEMS AMD inches closer to its goal of making AI suck less ... energyHouse of Zen claims latest systems already 4x more efficient than two years ago Security Russians are posing as Signal support to launch phishing attacksPLUS: US takes down Iranian propaganda sites; Marketing company asks 'Why Do We Have Your Information?' And more! Security Microsoft patches failed to fix on-prem SharePoint, which is now under zero-day attackPLUS: China upgrades smartphone surveillance tools; Ring eases anti-snooping stance; and more Black Hat and DEF CON DEF CON Franklin project enlists hackers to harden critical infrastructureVoting village reports have been so successful, says Jeff Moss, that the whole of DEF CON will now be included Security EQT buys majority share in Swiss cybersecurity biz AcronisWent at equivalent of $3.5B+ valuation for entire firm, though portion sold not specified Malware Month Ten years since the first corp ransomware, Mikko Hyppönen sees no end in sightOn the plus side, infosec's a good bet for a long, stable career FOSS smashed one Microsoft monopoly. After 20 years of failure, it's time to smash anotherWord up GNOME can look like Windows – and Flashback can do it without extensionsNew 'Simple-taskbar' is an option, but there's a simpler, stabler way A moment of silence, please, for the final release of Debian on x86-32New Debian versions hit FOSSland in the form of 13.6 and 12.15 Baddies caught exploiting extensions bugs with perfect 10 scores on vulnerable Joomla websitesFlaws in iCagenda, Balbooa Forms extensions can impact open source CMS that powers a million sites worldwide Frame: A new X11 server – implemented directly in assemblyJoins yserver, Phoenix, and of course XLibre – and outlier Arcan Cinnamon 6.8 will support Wayland – if you want itNext version of Linux Mint’s desktop has both kinds of display server
go.theregister.comMay 1, 2026extracted
SAP-Related npm Packages Compromised in Credential-Stealing Supply Chain Attack
Cybersecurity researchers are sounding the alarm about a new supply chain attack campaign targeting SAP-related npm Packages with credential-stealing malware. According to reports from Aikido Security, Onapsis, OX Security, SafeDep, Socket, StepSecurity, and Google-owned Wiz, the campaign – calling itself the Mini Shai-Hulud – has affected the following packages associated with SAP's JavaScript and cloud application development ecosystem - [email protected] @cap-js/[email protected] @cap-js/[email protected] @cap-js/[email protected] "The affected versions introduced new installation-time behavior that was not previously part of these packages' expected functionality," Socket said. "The compromised releases added a preinstall script that acts as a runtime bootstrapper, downloading a platform-specific Bun ZIP from GitHub Releases, extracting it, and immediately executing the extracted Bun binary." "The implementation also follows HTTP redirects without validating the destination and uses PowerShell with -ExecutionPolicy Bypass on Windows, increasing the risk for affected developer and CI/CD environments." Wiz noted that the malicious packages match several features present in previous TeamPCP operations, indicating that the same threat actor is likely behind the latest campaign. The suspicious versions were published on April 29, 2026, between 09:55 UTC and 12:14 UTC. The poisoned packages introduce a new package.json preinstall hook that runs a file named "setup.mjs," which acts as a loader for the Bun JavaScript runtime to execute the credential stealer and propagation framework ("execution.js"). According to Aikido, the malware is designed to harvest local developer credentials, GitHub and npm tokens, GitHub Actions secrets, and cloud secrets from AWS, Azure, GCP, and Kubernetes. The stolen data is encrypted and exfiltrated to public GitHub repositories created on the victim's own account with the description "A Mini Shai-Hulud has Appeared." As of writing, there are more than 1,100 repositories with descriptions. In addition, the 11.6 MB payload comes with capabilities to self-propagate through developer and release workflows, specifically using the GitHub and npm tokens to inject a malicious GitHub Actions workflow into the victim's repositories to steal repository secrets and publish poisoned versions of the npm packages to the registry. However, the latest incident bears significant differences from prior Shai-Hulud waves - All exfiltrated data is encrypted with AES-256-GCM and encapsulates the key using RSA-4096 with a public key embedded in the payload, effectively making it decipherable only to the attacker. It exits on Russian-locale systems. The payload commits itself into every accessible GitHub repository by injecting a ".claude/settings.json" file that abuses Claude Code's SessionStart hook and a ".vscode/tasks.json" file with "runOn": "folderOpen" setting so that any attempt to open the infected repository in Microsoft Visual Studio Code (VS Code) or Claude Code causes the malware to be executed. "This is one of the first supply chain attacks to target AI coding agent configurations as a persistence and propagation vector," StepSecurity said. Wiz also pointed out that the check for Russian locale was detected in the recent Checkmarx and Bitwarden compromises, adding the attack uses a TeamPCP-linked shared RSA public key used to encrypt the exfiltrated secrets. "The SAP operation adds the ability to steal credentials from multiple browsers (Chrome, Safari, Edge, Brave, Chromium) and exfiltrate any passwords found there," Wiz researchers noted. "This feature was not present in any of the previous operations. GitHub based exfiltration to Dune themed repos was the fallback C2 method for the Bitwarden CLI operation, but is now the primary option." Further analysis into the root cause has revealed that the attackers compromised RoshniNaveenaS's account for the three "@cap-js" packages, followed by pushing a modified workflow to a non-main branch and using the extracted npm OIDC token to publish the malicious packages without provenance. As for mbt, it's suspected to involve the compromise of the "cloudmtabot" static npm token through an as-yet-undetermined channel. "The cds-dbs team migrated to npm OIDC trusted publishing in November 2025," SafeDep said. "Under this setup, GitHub Actions can request a short-lived npm token without storing any long-lived secrets in the repository. The attacker reproduced this exchange manually in a CI step and printed the resulting token." "The critical configuration gap: npm’s OIDC trusted publisher configuration for @cap-js/sqlite trusted any workflow in cap-js/cds-dbs, not just the canonical release-please.yml on main. A branch push could exchange an OIDC token on behalf of the package if the workflow had id-token: write permission and the environment: npm reference." In response to the incident, the maintainers of the packages have released new safe versions that supersede the compromised releases - sqlite: v2.4.0, v2.3.0 postgres: v2.3.0, v2.2.2 hana: v2.8.0, v2.7.2 db-service: v2.10.1 mbt: v1.2.49 "This campaign illustrates once again how GitHub is becoming the C2 infrastructure of choice for data exfiltration," OX Security researchers Moshe Siman Tov Bustan and Nir Zadok said. "Blocking github.com is not a realistic option for most development teams, and tracing exfiltration back to a specific threat actor domain becomes nearly impossible when GitHub is the delivery mechanism."
thehackernews.comApr 29, 2026extracted
NVIDIA puts GPU orchestration in community hands
NVIDIA puts GPU orchestration in community hands GPU-accelerated AI workloads now run on Kubernetes in the large majority of enterprise environments. Managing those workloads at scale has required specialized tooling that, until now, remained under vendor control. NVIDIA moved to change that at KubeCon Europe in Amsterdam this week, donating its Dynamic Resource Allocation (DRA) Driver for GPUs to the Cloud Native Computing Foundation (CNCF). The transfer shifts ownership of the driver from NVIDIA to the broader Kubernetes project community. Developers across companies will now be able to contribute directly to the codebase, propose changes, and influence the direction of GPU scheduling in Kubernetes without routing requests through a single vendor. What the driver does The DRA Driver for GPUs sits between Kubernetes and the underlying GPU hardware, handling how compute resources get allocated to containerized workloads. The donated version supports several capabilities relevant to large-scale AI infrastructure: GPU sharing through NVIDIA Multi-Process Service and Multi-Instance GPU technologies, native support for multi-node NVLink interconnects used in Grace Blackwell systems, dynamic reconfiguration of hardware resources during runtime, and fine-grained requests for specific memory settings or interconnect arrangements. Confidential containers for AI workloads Alongside the DRA donation, NVIDIA announced GPU support for Kata Containers, developed in collaboration with the CNCF’s Confidential Containers community. Kata Containers are lightweight virtual machines that act like containers, providing stronger workload isolation than standard container runtimes. Adding GPU support to Kata extends hardware acceleration into that isolated environment, which allows AI workloads to run with additional protections around data confidentiality. Organizations looking to implement confidential computing for sensitive inference or training jobs gain a path to do so within the existing Kubernetes ecosystem. Industry backing The DRA donation comes with participation from several large cloud and infrastructure vendors. Amazon Web Services, Broadcom, Canonical, Google Cloud, Microsoft, Nutanix, Red Hat, and SUSE are collaborating with NVIDIA on the effort. Chris Aniszczyk, CTO of CNCF, commented on the significance of the move: “NVIDIA’s deep collaboration with the Kubernetes and CNCF community to upstream the NVIDIA DRA Driver for GPUs marks a major milestone for open source Kubernetes and AI infrastructure. By aligning its hardware innovations with upstream Kubernetes and AI conformance efforts, NVIDIA is making high-performance GPU orchestration seamless and accessible to all.” Red Hat CTO Chris Wright connected the donation to enterprise AI strategy, noting that open source brings standardization to the infrastructure components that fuel production AI workloads. Ricardo Rocha, lead of platforms infrastructure at CERN, pointed to the value for scientific computing, where community-driven tooling helps organizations process petabytes of data across both traditional and machine learning workloads. Additional open source projects Several other projects tied to AI infrastructure security and agent management were noted at KubeCon. NVIDIA OpenShell, announced at GTC last week, is a runtime for running autonomous agents with fine-grained programmable policy controls. It integrates natively with Linux, eBPF, and Kubernetes, and is designed to allow operators to define security and privacy boundaries for agentic workloads at a granular level. NVSentinel, a GPU fault remediation system, and AI Cluster Runtime, an agentic AI framework, were also announced at GTC. On the orchestration side, NVIDIA released Grove, an open source Kubernetes API for managing AI workloads across GPU clusters. Grove lets developers define complex inference systems in a single declarative resource and is being integrated with the llm-d inference stack for use across the Kubernetes community. Grove extends the Dynamo 1.0 ecosystem, which NVIDIA released earlier. Security relevance The combination of confidential container support, OpenShell policy controls, and GPU-level workload isolation addresses a gap that security teams have tracked in GPU-accelerated Kubernetes environments: the absence of hardware-backed isolation for AI inference jobs handling sensitive data. Kata Containers with GPU support gives operators a mechanism to enforce stronger boundaries around workloads at the hardware level, using existing Kubernetes primitives. OpenShell adds a layer of programmable controls for agentic workloads, where runtime behavior can be harder to constrain through conventional access management policies. Together, these tools extend security tooling into areas of the AI stack that standard container security controls have not previously reached.
helpnetsecurity.comMar 24, 2026extracted
Samba 4.24.0 ships Kerberos hardening and a CVE fix for domain encryption defaults
Samba 4.24.0 ships Kerberos hardening and a CVE fix for domain encryption defaults Samba 4.24.0 arrived carrying a set of Kerberos security changes aimed at Active Directory deployments. The release fixes a vulnerability, extends audit coverage for sensitive AD attributes, and introduces configuration options to counter two related Kerberos impersonation techniques. A CVE drives the encryption default change The most directly security-relevant change in 4.24.0 is a shift in default encryption types for Kerberos. The kdc default domain supported enctypes parameter now defaults to AES-128 and AES-256 (specifically aes128-cts-hmac-sha1-96 aes256-cts-hmac-sha1-96) on domains running at the 2008 functional level or above. This change addresses CVE-2026-20833. Kerberos canonicalization controls Two new KDC configuration options target the “dollar ticket” attack, a technique in which an attacker who can create arbitrary machine accounts obtains Kerberos tickets for Unix user accounts by mimicking their names with an appended dollar sign. The option kdc require canonicalization lets administrators require that clients explicitly request principal name canonicalization. Clients that do not request it will have their AS_REQ requests rejected as if the account were unknown. The default is no for backward compatibility. Windows clients request canonicalization by default, so the release notes recommend setting this to yes in Windows-heavy environments. For environments where requiring canonicalization is not possible, the option kdc name match implicit dollar without canonicalization can be set to no. This disables the KDC behavior of appending a dollar sign to unmatched names for clients that did not request canonicalization. The release notes include a recommended KDC configuration table: strong certificate binding enforcement set to full, kdc always include pac set to yes, and kdc require canonicalization set to yes. PAC always included Samba 4.24.0 changes the KDC to ignore the PA-PAC-REQUEST value sent by clients and include a Privilege Attribute Certificate (PAC) in all responses by default. The prior behavior, where the KDC honored client requests to omit the PAC, can be restored by setting kdc always generate pac = no. The KDC also now sends services the canonicalized client name from the PAC, using the sAMAccountName, rather than trusting the cname field. This applies to the Heimdal KDC only; the MIT KDC is unaffected. The prior behavior is available via krb5 acceptor report canonical client name = no. PKINIT key trust and certificate mapping Samba AD domain controllers using the embedded Heimdal KDC now support Windows Hello for Business Key-Trust logons. This implements PKINIT authentication with self-signed keys, storing public key details in the msDS-KeyCredentialLink attribute. Two new samba-tool subcommands support this: keytrust for setting and viewing public key details on user and computer accounts, and generate-csr for generating certificate signing requests that include the Object SID extension (OID 1.3.6.1.4.1.311.25.2). Certificate-based authentication now follows Microsoft KB5014754 enforcement. The default mode (full) permits only strong certificate mappings. The compatibility mode allows weak mappings where the certificate predates the user account. A none setting allows any mappings. Certificates containing the Object SID extension qualify as strong mappings under KB5014754. Updates to the msDS-KeyCredentialLink attribute are validated against the rules in MS-ADTS 3.1.1.5.3.1.1.6. Authentication attribute audit logging The dsdb_password_audit and dsdb_password_json_audit debug classes now log changes to five AD attributes: altSecurityIdentities, dNSHostName, msDS-AdditionalDnsHostName, msDS-KeyCredentialLink, and servicePrincipalName. In JSON logs, changes to these attributes appear with the action field set to Auth info change. The release notes describe these attributes as not secret but relied upon in certain authentication paths, where unauthorized changes could indicate surreptitious activity. Remote password management compatibility Samba AD now recognizes the password policy hints control used by Microsoft Entra ID self-service password reset (SSPR) and Keycloak. Previously, Samba rejected password resets that used this control. The change means that password resets originating from Entra ID or Keycloak will be evaluated against on-premises password policies, including history and age checks, in the same way a local password change would be. Storage and I/O additions On the file system side, the vfs_streams_xattr module gains the ability to shard a single stream across multiple extended attributes. The streams_xattr:max xattrs per stream parameter accepts values above 1, with a limit of 16, allowing streams up to 1 MB on file systems like XFS where per-attribute size is capped at 64 KB. A new VFS module, vfs_aio_ratelimit, lets administrators set throughput ceilings on asynchronous I/O operations, expressed in either operations per second or bytes per second. The module uses a token-based algorithm to track real-time load and injects millisecond delays when operations exceed the defined threshold. The ceph_new VFS module adds support for CephFS FSCrypt, enabling per-share data and file name encryption. Key retrieval uses the Keybridge protocol, an RPC mechanism based on Varlink that communicates over a UNIX socket. A KMIP-compatible Keybridge server is available through the sambacc project.
helpnetsecurity.comMar 19, 2026extracted
Open, Closed and Broken: Prompt Fuzzing Finds LLMs Still Fragile Across Open and Closed Models
Unit 42 researchers have developed a genetic algorithm-inspired prompt fuzzing method to automatically generate variants of disallowed requests that preserved their original meaning. This method also measures guardrail fragility under systematic rephrasing. Our research uncovered guardrail weaknesses, with evasion rates ranging from low single digits to high levels in specific keyword and/or model combinations. The key difference from prior single-prompt jailbreak examples is scalability. Small failure rates become reliable when attackers can automate at volume. Prompt jailbreaking is a text-based adversarial input threat against large language model (LLM)-powered generative AI (GenAI) applications, especially chatbots and chat-shaped workflows. Attackers craft inputs that manipulate the model into bypassing guardrails, producing disallowed content or otherwise operating outside of intended scopes. This matters to any organization embedding GenAI into customer support, employee copilots, developer tooling or knowledge assistants. Because the primary attack surface is untrusted natural language, failures can translate into safety incidents, compliance exposure and reputational damage. We recommend the following: Treating LLMs as non-security boundaries Defining scope Applying layered controls Validating outputs Continuously testing GenAI with adversarial fuzzing and red-teaming Palo Alto Networks customers are better protected against the threats discussed in this article through the following products and services: If you think you might have been compromised or have an urgent matter, contact the Unit 42 Incident Response team. Since the first large-scale LLM deployments in 2020, GenAI has moved from experimentation to production. LLM-backed features now appear in customer support, developer tooling, enterprise knowledge search and end‑user productivity applications. Market forecasts vary, but they consistently point to rapid growth in both GenAI and the broader AI ecosystem. A major reason for this adoption is that many GenAI systems implement a chatbot-style interface, even when a product is not branded as a chatbot. Users provide natural language inputs. The end product combines input with system instructions, retrieved context and tool outputs into a prompt. The product's backend model generates a response. This interactive model is straightforward yet powerful, but it also means the primary attack surface is untrusted text. Because LLMs can generate responses, production systems using LLMs require guardrails to reduce unsafe, non-compliant or out-of-scope behavior. In practice, guardrails are multi-layered. These layers consist of content moderation and classification, model-side alignment and refusal behavior. For example, the Azure implementation of OpenAI content filtering includes filtering against areas such as hate and fairness-related harm, sexual content, violence and self-harm. Cloud providers have also added safeguards aimed specifically at LLM misuse patterns. For example, Microsoft’s Prompt Shields is one such method to prevent prompt-injection-style attacks. Despite years of investment in these defenses, prompt jailbreaking and prompt injection remain one of the most well-known and actively discussed attack classes against LLM applications. OWASP lists prompt injection as the top risk category for LLM applications in 2025. Academic work has also shown that simple, crafted inputs can cause goal hijacking or prompt leaking in LLM-based systems. More recently, the U.K. National Cyber Security Center has argued that prompt injection differs materially from SQL injection and may be harder to fix in a definitive way. This is because LLMs do not enforce a clean separation between instructions and data within prompts. This raises a practical question. After roughly five years of rapid iteration in alignment and safety engineering, how fragile are current open and closed models when an attacker systematically rewrites a disallowed request without changing its meaning? We have approached answering this question by using a well-established security concept in software testing: fuzzing. Starting from a malicious prompt, we generate meaning-preserving variants that alter surface form, such as wording, structure and framing, while retaining the malicious intent. We then measure whether these variants can evade guardrails across both open-weight models and proprietary closed-source models. The goal is defensive: to make robustness measurable and comparable, and to highlight where existing controls remain brittle under realistic and automated variation. Two types of background knowledge are necessary to understand our approach to this research: fuzzing and prompt hacking. For prompt-hacking taxonomy and techniques, refer to our previous publications, such as our report on securing GenAI against adversarial prompt attacks. In software security and quality engineering, fuzzing is an automated testing technique used to uncover defects and security weaknesses by presenting a target with large volumes of atypical inputs. These inputs may be invalid, malformed, unexpected or randomly generated. The system is then monitored for anomalous behavior and failure modes such as: Crashes Information disclosure Memory corruption Memory leaks Service disruption Unexpected state transitions A challenge in fuzzing is effective test case generation. Purely random input generation is simple but often inefficient, especially for targets that require structured inputs or have complex parsing and control-flow logic. As a result, modern fuzzers increasingly rely on feedback-driven input generation, where mutations are guided by signals from prior executions. This includes feedback on code coverage, error conditions or other behavioral indicators. The goal is to adaptively explore execution paths that are more likely to surface vulnerabilities. One widely used strategy for such adaptive generation is a genetic algorithm [PDF], a class of evolutionary optimization methods inspired by natural selection. In genetic algorithm terminology, each candidate input is represented as a chromosome composed of genes, which refer to features or components of the input. A fitness function scores candidates based on how well they achieve a target objective. Examples of targeted objectives include reaching new execution paths or triggering abnormal behavior. Over successive generations, higher-fitness candidates are preferentially retained and transformed through operators such as mutation and crossover, producing progressively more effective test inputs. Here are the four steps of a genetic algorithm: Initialization: A population of randomly generated chromosomes (sequences of genes) is created. This population evolves over multiple iterations, known as generations. Selection: In each generation, the fitness of each individual is evaluated. In the context of fuzzing, fitness is an objective function of the optimization problem. A more fit individual will have a higher chance of being selected. In the context of LLM fuzzing, a more effective word or sequence of words will have a higher probability of the LLM accepting it as a prompt. Mutation and crossover: The next step is to create a second generation of population based on the selected samples through a combination of genetic operations of mutation and crossover. Termination: Repeat the process until an optimal solution is found or the limit is reached. For this research, we applied the concept of a genetic algorithm to design an algorithm for generating evasive prompts to fuzz LLMs. Figure 1 shows the workflow comparison of a standard genetic algorithm and an LLM-based genetic algorithm. This diagram labels the individual steps for a better understanding, and it illustrates how we can adapt the standard genetic algorithm for LLMs. Using the LLM-based workflow genetic algorithm in Figure 1, we can better understand how to use a genetic algorithm technique for prompt evasion. For example, let's say we want to generate an evasive prompt based on a harmful question like “how to build a bomb.” If we directly input the original question to an LLM, the LLM will likely refuse to answer for security reasons. Instead, we can leverage the following steps to generate evasive prompts that contain the same questions, but which can evade the LLMs successfully. Initialization: Based on the sensitive questions, we will prepare three lists of words. - Keyword: This represents the keyword in the question, which is a noun in most cases. In this example, the keyword will be “bomb.” - Relative word: This represents the action in the question, which is a verb in most cases. Examples include “build,” “list the ingredients of” and “components of.” - Phrases: This is a list of commonly used phrases in English that do not have specific meanings or relations to the particular questions. The purpose is to use the phrase list to disrupt the LLMs' ability to accurately interpret the question. Example phrases include “Has anyone,” “Is it” and “Do you think.” Selection and mutation: We combine the steps of selection with mutation and crossover in this one step for easy explanation. For every iteration, we choose one operation out of the six options on the output of the previous iterations. We can define the probability of each operation being chosen. We repeat the process for N iterations. The options of operations are listed below. - Prepend a phrase: Randomly choose and prepend a phrase to the output of the last iteration - Append a phrase: Randomly choose and append a phrase to the output of the last iteration - Add a linefeed: Add a line feed at the end of the output of the last iteration - Repeat the keyword: Randomly choose and repeat the keyword, placing it at the end of the output of the last iteration - Add a relative word: Randomly choose and put a relative word at the end of the output of the last iteration - Remove a word: Remove a random word from the output of the last iteration Termination: After N iterations are reached, we submit the generated prompts to LLMs and test whether they can successfully evade them. We take the LLM output and calculate its “fitness” the same way as the standard genetic algorithm. We can use the number of negative tones in the fitness function as an example. If needed, we can repeat the mutation process multiple times until a successful evasion is achieved. In our experiments, we found that 100 iterations are enough to find some successful evasions. We tested different models with harmful questions of how to build four types of explosives: bomb, napalm, ordnance and torpedo. We applied the fuzzing algorithm to generate 100 fuzzed versions of each question. For every iteration, we limited the maximum number of mutation operations to 50 times. With the 100 generated prompts per question, we tested each of them against three types of models. All the tested models were released in 2024 and 2025, and they were the most popular and advanced models when building GenAI applications. We conducted all tests through API calls. The four tested models were: One closed-source pretrained model that provides answers to the prompts Two open-source pretrained models that provide answers to the prompts One open-source content-filter model that provides binary classification to the prompts We tested the fuzzed prompts against the four models with the prompts using different keywords, including bomb, napalm, ordnance and torpedo. Table 1 shows the success rate of these evasive prompts. The value means the percentage of successful evasion. For example, 10/100 means 10 out of 100 generated prompts could evade the model content filter. Table 1. Experiment results on different keywords and LLM models. In terms of the definition of successful evasion, we look at the LLM responses to see if it contains information about the ingredients of the explosive. If yes, we consider it as a successful evasion. Particularly for the content filter model, which provided binary classification, 11/100 means that 11 out of 100 fuzzed malicious prompts are classified as benign, representing false negative cases. Figures 2 and 3 show an example of prompt input and the associated output of successful evasion. Across both proprietary and open-weight targets, we observed non-uniform robustness across both categories, rather than a clear “closed is safer than open” split. The closed-source pretrained model showed moderate evasion for several keywords (e.g., 5/100 for bomb, 16/100 for napalm, 8/100 for ordnance), and a sharp failure mode on torpedo (90/100). This indicates that even mature proprietary systems can exhibit keyword-specific weak spots under fuzzing. On the open-weight side, the results were bimodal: One pretrained model remained relatively resistant across all keywords (1–4/100), while another was substantially more fragile (20/100–75/100 depending on keyword). The open-source content filter target was the weakest overall, classifying 97–99% of fuzzed prompts as benign across all keywords, suggesting that this style of filtering is particularly brittle under meaning-preserving surface variations. Taken together, the results suggest that the model licensing (closed source vs. open source) is not a reliable indicator for guardrail strength. Robustness depends more on the specific model tuning and safety stack, and it must be validated empirically across diverse prompts and keywords. Across the four weapon-related seed keywords, evasion rates were strongly keyword-dependent, with a large variance even among semantically similar terms. For the closed-source pretrained model, “torpedo” produced an outlier 90/100 successful evasion rate, compared to 5/100 for bomb, 16/100 for napalm, and 8/100 for ordnance, indicating uneven guardrail sensitivity across adjacent keywords. Open-source pretrained model 1 was comparatively more consistent and lower-risk across all keywords (1–4/100). In contrast, open-source pretrained model 2 showed substantially higher fragility overall, particularly for napalm (63/100) and torpedo (75/100), with non-trivial rates for bomb (20/100) and ordnance (24/100). Most notably, the content filter model labeled the vast majority of fuzzed variants as benign across all keywords (97–99/100), suggesting the filter’s decision boundary is highly susceptible to surface-form variation. Overall, these results reinforce that robustness cannot be inferred from testing only a single canonical keyword. Coverage across related terms materially changes the measured risk. When we began this work in 2024, we evaluated the same model family on an earlier release — approximately four versions before the current one — and we observed comparable evasion rates. This is not a controlled longitudinal study, but it suggests that over the past two years, model capability has improved substantially. Robustness to prompt-based evasion may not have improved at the same pace, at least for the type of attacks evaluated in this research. We now discuss why this evasion method remains realistic, even without testing an end-to-end production system. Our experiments focused primarily on pretrained models and a separate content-filtered variant, rather than complete end-to-end applications with retrieval, tool constraints, rate limits and layered safety middleware. That limitation is important, but it does not make the results unrealistic. In practice, many real deployments still expose scenarios where the base model’s behavior dominates, for example: Self-hosted open-weight deployments with minimal safety wrapping Internal tools where policy enforcement is assumed rather than verified Misconfigurations where safety middleware is bypassed or inconsistently applied Situations where the content filter is treated as the primary control and the rest of the stack is permissive The content-filtered model showing higher successful evasion raises a critical design question. Why does an additional safety layer appear less robust under systematic input variation? One plausible explanation is that filters tuned to catch common language patterns can be brittle under natural-language rephrasing. Regardless of root cause, the result reinforces a core principle, which is that guardrails must be evaluated as a system under adversarial variation, not assumed to be effective because they work on canonical examples. Blocking clearly harmful categories (e.g., weapon construction) is difficult, but often more tractable than enforcing a product’s business scope. This is partly because the presence of harmful words, such as the term “ordnance” in our testing, aids detection. Many production GenAI applications are not general assistants. They are chatbot-like frontends for a narrow capability, like translating text, summarizing documents, querying internal knowledge or drafting code. In those systems, attackers do not need to elicit obviously harmful content to cause damage. Instead, they can push the model out of scope, such as coercing a translation tool into generating unrelated guidance. Because out-of-scope prompts may be benign in isolation, category moderation against pure harm is not enough. This gap can become a larger real-world risk than the obvious harmful prompt case, especially when models are connected to data sources or tools. The broader takeaway is that security for LLM applications cannot rely on a single layer, including prompt instructions, a classifier or model refusals. If a small budget fuzzer can find bypasses, then production systems should assume that motivated attackers will also find them. To build a question-answering LLM application that is more resilient to prompt hacking attacks, the following design practices are worth treating as baseline: Define and enforce application scope. Specify what the system is allowed to do and not do in terms of domains, tasks and tool access. Narrow-scope assistants are typically easier to defend than general-purpose assistants because policy enforcement can be explicit and testable. Use robust, multi-signal content controls. Keyword-only filtering is insufficient given the flexibility of natural language. Choose layered controls that combine semantic classification, policy rules and context-aware checks. Evaluate them under paraphrase and adversarial variation, not just fixed test prompts. Treat user input as untrusted and isolate it from privileged instructions. Avoid directly concatenating raw user text into high-privilege instruction channels. Use structured prompting patterns that clearly separate data from instructions, and design prompts so that untrusted content cannot easily override system intent. Validate outputs against scope and policy. Apply post generation validation to ensure the response stays within the allowed task boundary. If the output violates scope or policy, block or regenerate with stricter constraints. Monitor and log for misuse signals. Track anomalous patterns such as repeated probing, high variance prompt attempts and repeated near boundary failures. Instrumentation is essential both for detection and for improving defenses over time. Apply standard security controls around the system. Strong authentication and authorization, rate limiting, least privilege tool permissions and secure backend isolation remain critical, especially when the model can access internal data or perform actions. From a practitioner perspective, the most actionable next step is to operationalize this kind of testing as continuous regression. This involves running fuzzing-based adversarial evaluations when models, prompts or filters change. From a research perspective, results like these suggest the need for guardrails that are more robust to meaning-preserving variation. They also underscore the need for clearer evaluation standards that measure not just refusal rate, but boundary fragility and failure modes under automation. This work shows that prompt jailbreaking remains a practical risk even after several years of safety engineering progress. By adapting a genetic algorithm-based fuzzing approach to generate meaning-preserving prompt variants, we were able to trigger policy-violating outcomes against both closed-source and open-weight pretrained models. We did so using only a single disallowed seed request and a small number of runs. Importantly, the observed success rates are operationally meaningful. Once attackers can automate probing, even low-probability failures can be found reliably at scale. The results also highlight an additional concern. A standalone content filter model showed a higher evasion success rate in our testing, raising questions about how filters are trained, what patterns they generalize to and how they behave under systematic paraphrasing. The broader implication is that guardrails should be treated as probabilistic controls that require continuous adversarial evaluation, not as definitive security boundaries. For production GenAI systems, resilience depends on security-by-design. This includes: Clearly defining application scope Enforcing that scope through layered controls Isolating untrusted input from privileged instructions Validating model outputs Monitoring for probing behavior These findings reinforce the idea that the harder long-term challenge might not be only harmful content detection, but robust scope enforcement for domain-specific applications. This is especially fraught when models are connected to tools, data and real workflows. Palo Alto Networks Prisma AIRS provides inline inspection and enforcement for prompts and responses to help block prompt injection, data leakage and unsafe outputs. The Unit 42 AI Security Assessment can help empower safe AI use and development. If you think you may have been compromised or have an urgent matter, get in touch with the Unit 42 Incident Response team or call: North America: Toll Free: +1 (866) 486-4842 (866.4.UNIT42) UK: +44.20.3743.3660 Europe and Middle East: +31.20.299.3130 Asia: +65.6983.8730 Japan: +81.50.1790.0200 Australia: +61.2.4062.7950 India: 000 800 050 45107 South Korea: +82.080.467.8774 Palo Alto Networks has shared these findings with our fellow Cyber Threat Alliance (CTA) members. CTA members use this intelligence to rapidly deploy protections to their customers and to systematically disrupt malicious cyber actors. Learn more about the Cyber Threat Alliance.
unit42.paloaltonetworks.comMar 17, 2026extracted
Internet Infrastructure TLD .arpa Abused in Phishing Attacks
A threat actor has been abusing the internet infrastructure top-level domain (TLD) .arpa to host phishing content on domains that should not resolve to IP addresses, Infoblox reports. The .arpa TLD is designed to map IP addresses to domains, providing reverse DNS records, and should not host web content, as other TLDs do. As part of the newly uncovered campaign, however, a threat actor has been abusing DNS record management controls of certain providers to add IP address records for .arpa domains and serve phishing content to victims. Impersonating major brands, the phishing emails display an image hiding an embedded hyperlink designed to take the victim to the malicious website after a series of redirects. The links use a reverse DNS string instead of a standard domain name, but the actual domain is hidden from the victim’s view to avoid raising suspicion. As part of the .arpa phishing campaign, the threat actor has exploited a vulnerability at DNS providers that allowed them to claim ownership of .arpa domains. “To make this attack work, the threat actor acquires some IPv6 address space, for which they are delegated control of the corresponding .arpa subdomain. Then, instead of adding the expected PTR records, they create A records for the reverse DNS names,” Infoblox explains. These records were created through Cloudflare and Hurricane Electric, but other DNS providers also allow the configuration. While .arpa domains are typically trusted and the domain names unlikely to be blocked, the threat actor further made the reverse DNS domains difficult to identify and block by prepending them with randomly generated subdomains, creating unique Fully Qualified Domain Names (FQDNs) that were then used to build phishing email HTMLs. The identified reverse DNS FQDNs resolved to two IP addresses belonging to Cloudflare’s edge network, essentially hiding the location of the malicious content. Infoblox also discovered that the threat actor hijacked the Canonical Name (CNAME) records of known education, government, media, retail, and telecommunication entities and abused subdomains of their legitimate domains in their phishing attacks. “We also saw a few cases of domain shadowing, in which an actor-controlled subdomain is created, typically through credential theft. The lure images are unrelated to the hijacked domains. As with the IPv6 reverse domains, victims are unlikely to ever notice them,” Infoblox notes. The company observed hijacked CNAMEs being constantly abused in phishing attacks since September 2025, some in more than 100 different email runs per day. Some of the domains have been abused for years, and the toolkit used in this campaign has been used by multiple threat actors since 2017. Related: Tycoon 2FA Phishing Platform Dismantled in Global Takedown Related: LastPass Warns of New Phishing Campaign Related: ‘Stanley’ Malware Toolkit Enables Phishing via Website Spoofing
securityweek.comMar 9, 2026extracted
Malicious Go Crypto Module Steals Passwords, Deploys Rekoobe Backdoor
Cybersecurity researchers have disclosed details of a malicious Go module that's designed to harvest passwords, create persistent access via SSH, and deliver a Linux backdoor named Rekoobe. The Go module, github[.]com/xinfeisoft/crypto, impersonates the legitimate "golang.org/x/crypto" codebase, but injects malicious code that's responsible for exfiltrating secrets entered via terminal password prompts to a remote endpoint, fetches a shell script in response, and executes it. "This activity fits namespace confusion and impersonation of the legitimate golang.org/x/crypto subrepository (and its GitHub mirror github.com/golang/crypto)," Socket security researcher Kirill Boychenko said. "The legitimate project identifies go.googlesource.com/crypto as canonical and treats GitHub as a mirror, a distinction the threat actor abuses to make github.com/xinfeisoft/crypto look routine in dependency graphs." Specifically, the backdoor has been placed within the "ssh/terminal/terminal.go" file, so that every time a victim application invokes ReadPassword() – a function supposedly meant to read input like passwords from a terminal – it causes those interactive secrets to be captured. The main responsibility of the downloaded script is to function as a Linux stager, appending a threat actor's SSH key to the "/home/ubuntu/.ssh/authorized_keys" file, set iptables default policies to ACCEPT in an attempt to loosen firewall restrictions, and retrieve additional payloads from an external server while disguising them with the .mp5 extension. Of the two payloads, one is a helper that tests internet connectivity and attempts to communicate with an IP address ("154.84.63[.]184") over TCP port 443. The program likely functions as a recon or loader, Socket noted. The second downloaded payload has been assessed to be Rekoobe, a known Linux trojan that has been detected in the wild since at least 2015. The backdoor is capable of receiving commands from an attacker-controlled server to download more payloads, steal files, and execute a reverse shell. As recently as August 2023, Rekoobe has been put to use by Chinese nation-state groups like APT31. While the package still remains listed on pkg.go.dev, the Go security team has taken steps to block the library as malicious. "This campaign will likely repeat because the pattern is low-effort and high-impact: a lookalike module that hooks a high-value boundary (ReadPassword), uses GitHub Raw as a rotating pointer, then pivots into curl | sh staging and Linux payload delivery," Boychenko said. "Defenders should anticipate similar supply chain attacks targeting other 'credential edge' libraries (SSH helpers, CLI auth prompts, database connectors) and more indirection through hosting surfaces to rotate infrastructure without republishing code."
thehackernews.comFeb 27, 2026extracted
Clawdbot’s rename to Moltbot sparks impersonation campaign
After the viral AI assistant Clawdbot was forced to rename to Moltbot due to a trademark dispute, opportunists moved quickly. Within days, typosquat domains and a cloned GitHub repository appeared—impersonating the project’s creator and positioning infrastructure for a potential supply-chain attack. The code is clean. The infrastructure is not. With the GitHub downloads and star rating rapidly rising, we took a deep dive into how fake domains target viral open source projects. The background: Why was Clawdbot renamed? In early 2026, Peter Steinberger’s Clawdbot became one of the fastest-growing open source projects on GitHub. The self-hosted assistant—described as “Claude with hands”—allowed users to control their computer through WhatsApp, Telegram, Discord, and similar platforms. Anthropic later objected to the name. Steinberger complied and rebranded the project to Moltbot (“molt” being what lobsters do when they shed their shell). During the rename, both the GitHub organization and X (formerly Twitter) handle were briefly released before being reclaimed. Attackers monitoring the transition grabbed them within seconds. “Had to rename our accounts for trademark stuff and messed up the GitHub rename and the X rename got snatched by crypto shills.” — Peter Steinberger That brief gap was enough. Impersonation infrastructure emerged While investigating a suspicious repository, I uncovered a coordinated set of assets designed to impersonate Moltbot. Domains moltbot[.]you clawbot[.]ai clawdbot[.]you Repository github[.]com/gstarwd/clawbot — a cloned repository using a typosquatted variant of the former Clawdbot project name Website A polished marketing site featuring: professional design closely matching the real project SEO optimization and structured metadata download buttons, tutorials, and FAQs claims of 61,500+ GitHub stars lifted from the real repository Evidence of impersonation False attribution: The site’s schema.org metadata falsely claims authorship by Peter Steinberger, linking directly to his real GitHub and X profiles. This is explicit identity misrepresentation. Misdirection to an unauthorized repository: “View on GitHub” links send users to gstarwd/clawbot, not the official moltbot/moltbot repository. Stolen credibility:The site prominently advertises tens of thousands of stars that belong to the real project. The clone has virtually none (although at the time of writing, that number is steadily rising). Mixing legitimate and fraudulent links: Some links point to real assets, such as official documentation or legitimate binaries. Others redirect to impersonation infrastructure. This selective legitimacy defeats casual verification and appears deliberate. Full SEO optimization: Canonical tags, Open Graph metadata, Twitter cards, and analytics are all present—clearly intended to rank the impersonation site ahead of legitimate project resources. The ironic security warning: The impersonation site even warns users about scams involving fake cryptocurrency tokens—while itself impersonating the project. Code analysis: Clean by design I performed a static audit of the gstarwd/clawbot repository: no malicious npm scripts no credential exfiltration no obfuscation or payload staging no cryptomining no suspicious network activity The code is functionally identical to the legitimate project, which is not reassuring. The threat model The absence of malware is the strategy. Nothing here suggests an opportunistic malware campaign. Instead, the setup points to early preparation for a supply-chain attack. The likely chain of events: A user searches for “clawbot GitHub” or “moltbot download” and finds moltbot[.]you or gstarwd/clawbot. The code looks legitimate and passes a security audit. The user installs the project and configures it, adding API keys and messaging tokens. Trust is established. At a later point, a routine update is pulled through npm update or git pull. A malicious payload is delivered into an installation the user already trusts. An attacker can then harvest: Anthropic API keys OpenAI API keys WhatsApp session credentials Telegram bot tokens Discord OAuth tokens Slack credentials Signal identity keys full conversation histories command execution access on the compromised machine What’s malicious, and what isn’t Clearly malicious false attribution to a real individual misrepresentation of popularity metrics deliberate redirection to an unauthorized repository Deceptive but not yet malware typosquat domains SEO manipulation cloned repositories with clean code Not present (yet) active malware data exfiltration cryptomining Clean code today lowers suspicion tomorrow. A familiar pattern This follows a well-known pattern in open source supply-chain attacks. A user searches for a popular project and lands on a convincing-looking site or cloned repository. The code appears legitimate and passes a security audit. They install the project and configure it, adding API keys or messaging tokens so it can work as intended. Trust is established. Later, a routine update arrives through a standard npm update or git pull. That update introduces a malicious payload into an installation the user already trusts. From there, an attacker can harvest credentials, conversation data, and potentially execute commands on the compromised system. No exploit is required. The entire chain relies on trust rather than technical vulnerabilities. How to stay safe Impersonation infrastructure like this is designed to look legitimate long before anything malicious appears. By the time a harmful update arrives—if it arrives at all—the software may already be widely installed and trusted. That’s why basic source verification still matters, especially when popular projects rename or move quickly. Advice for users Verify GitHub organization ownership Bookmark official repositories directly Treat renamed projects as higher risk during transitions Advice for maintainers Pre-register likely typosquat domains before public renames Coordinate renames and handle changes carefully Monitor for cloned repositories and impersonation sites Pro tip: Malwarebytes customers are protected. Malwarebytes is actively blocking all known indicators of compromise (IOCs) associated with this impersonation infrastructure, preventing users from accessing the fraudulent domains and related assets identified in this investigation. From reporting threats to removing them. Cybersecurity risks should never spread beyond a headline. Keep threats off your devices by downloading Malwarebytes today.
malwarebytes.comJan 29, 2026extracted
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