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Cybercriminals are moving away from mass phishing campaigns
Cybercriminals are moving away from mass phishing campaigns Phishing activity declined by roughly 20% in both 2024 and 2025, according to research from Zscaler’s ThreatLabz team. The drop followed years of growth that pushed phishing activity above 2 billion hits in 2023. “Phishing volume measured by blocked emails is no longer a reliable proxy for phishing risk.” Researchers found greater use of targeted phishing campaigns designed to resemble routine business communications. The services sector recorded a 65.5% year-over-year increase in phishing activity, making it the most targeted industry in the dataset. Encrypted attack hits by industry (Source: Zscaler) Billing notices, onboarding documents, renewals, support requests, and document-sharing workflows appeared frequently in campaigns targeting the sector. One campaign cited by Zscaler used tax-themed lures and legitimate services such as OneDrive to target more than 29,000 users across 10,000 services organizations. Microsoft and Google topped the list of brands most frequently impersonated in phishing campaigns. Credentials tied to those platforms often provide access to multiple business services through a single account. A Microsoft 365 login can unlock email, files, Teams, SharePoint, OneDrive, and connected SaaS applications. Access to one account can expose a much larger portion of an organization’s environment. AI site builders are becoming part of phishing operations ThreatLabz identified 413,524 AI-generated website instances and classified 37,447 of them as malicious. The activity was associated with platforms including Manus AI, Blackbox AI, Anything AI, Bolt AI, Vercel v0, and Framer AI. Unattributed AI tooling accounted for the largest share of observed activity, followed by Manus AI and Blackbox AI. Researchers documented phishing pages, fake applications, and brand impersonation sites created through these services. One case involved a counterfeit Coinbase Wallet website generated with an AI application builder. The site promoted a fake browser extension and was hosted on a legitimate platform. Researchers noted that branding from the AI platform remained embedded in parts of the page metadata. “What used to require a developer, a template kit, and time now often takes little more than a prompt and a few iterations.” More phishing activity is hidden inside encrypted traffic More than 95% of phishing activity observed by Zscaler was delivered over encrypted channels. Researchers also found that 87% of all malicious activity blocked during 2025 was delivered over HTTPS. Credential theft, session abuse, and redirects increasingly occur through the same encrypted connections employees use to access cloud applications and business services. “What makes this shift more dangerous is where compromise actually happens: in the browser, over HTTPS.” Attackers are bypassing MFA in real time ThreatLabz identified phishing kits that combine adversary-in-the-middle (AiTM) and browser-in-the-middle (BiTM) techniques to intercept login sessions and capture credentials, MFA codes, and session tokens in real time. BlackForce, a phishing-as-a-service platform cited by ThreatLabz, was among the examples. The kit captures credentials, MFA codes, and session information during the login process, turning a single click into a session-level compromise. Attack surface discovery is happening at scale Between October 2025 and March 2026, external decoys deployed in customer environments recorded 89.9 million hostile interactions from 1.37 million unique attacker IP addresses. Attackers were probing exposed services and looking for assets that could provide a path into an organization. Researchers described reconnaissance efforts focused on exposed assets, leaked credentials, misconfigured applications, and forgotten subdomains. Cloud infrastructure is fueling scanning activity ThreatLabz observed more than 121,000 AWS-hosted IP addresses probing customer environments. Public cloud platforms accounted for a significant share of the attacker infrastructure observed in the dataset. Researchers said cloud-hosted infrastructure can be provisioned quickly, used for reconnaissance, and replaced when it is blocked or detected. Zscaler expects phishing campaigns to become more automated in 2026, with AI agents targeting other AI agents, attacks moving between email, messaging apps, SMS, and voice channels, and attackers focusing on active sessions and identities instead of credentials alone.
helpnetsecurity.comJun 12, 2026extracted
Everybody Is Vibe Coding But Nobody Told the Security Team
In February 2025, Andrej Karpathy coined the term “vibe coding” to describe a new way of building software: rapid, AI-assisted development where users ‘fully give in to the vibes, embrace exponentials, and forget that the code even exists’.” Fast forward to 2026, and Anthropic CEO now predicts that 90% of code will be written by AI in 3-6 months. According to one survey, 84% of developers globally are using or planning to use AI coding tools in their workflow, up from 76% in 2024. Of those, 51% of professional developers use AI tools daily. The marketing manager, the operations lead, the finance team — all of them are building working applications, connecting them to production systems, and deploying them. Mostly without involving IT, and often never involving security. Security Challenges With Vibe Coding Apps Recent research from Veracode shows 45% of AI-generated code contains OWASP Top 10 vulnerabilities. AI models have improved dramatically at generating code that compiles and runs – but the security of that code is not always sound. The reason is straightforward: AI optimizes for functionality, not security. Researchers at RedAccess recently analyzed thousands of vibe-coded applications built on Lovable, Replit, Base44, and Netlify. They found more than 5,000 with virtually no security or authentication. Around 40% exposed sensitive data — medical information, financial records, corporate strategy documents, detailed customer conversation logs. Among verified exposures: a shipping company app detailing vessel port arrivals; an internal health company application listing active UK clinical trials. Many of these applications are indexed by Google. As relayed in the report– no exploitation was required; this was research on exposed applications with public URLs. This lack of security control extends to the AI agents themselves, whether assisting a professional developer or a non-developer. A software company, PocketOS, reported that its Cursor AI coding agent deleted its entire production database and “all volume-level backups” in nine seconds. Replit’s AI agent deleted 1,206 executive records and 1,196 company records while under explicit code-freeze instructions — then admitted: “Yes. I deleted the codebase without permission during an active code and action freeze. This was a catastrophic error in judgment.” It then told the user a rollback would not work. That turned out to be false. A New Shadow AI Problem For two years, the security industry has discussed shadow AI as a behavior problem — employees pasting sensitive data into ChatGPT on personal accounts. That problem is bounded: the exposure lives in the inference layer, and there are tools that are focused on detecting it. Vibe coding brings a different shadow AI problem. The employee is not sending data somewhere. They are building something — a live application connected to your CRM, your database, your ticketing system — and deploying it publicly. Your security stack – with insights distributed across multiple data silos – was never designed to find it. Organizations running mature secure web gateways, CASB, or DNS logging can detect employee access to vibe-coding platforms. But detecting access is not the same as inventorying what was deployed, what data it holds, or whether it requires authentication. For example – while a CASB can detect that an employee accessed Replit, it cannot inventory what was deployed, what data it holds, or if it requires a login. These apps live in the “visibility gap” between network security and AppSec, often because they are deployed directly to third-party platforms and bypass the organization’s traditional CI/CD pipelines or cloud environments that AppSec tools are designed to monitor. What Should Security Leaders Do? Similar to the initial reaction with shadow IT, the instinct is to prohibit vibe coding tools. That instinct is wrong. AI-driven development is not something organizations can or should block. But it must be governed. The question is what governance actually means in practice when the tools move faster than any policy framework. Here are some best practices security leaders can act on now: Discover before you govern. You cannot govern what you cannot find. Before writing policy, answer the question: do applications built by your employees on Lovable, Replit, Base44, or Netlify currently exist and are they reachable from the open internet? Run discovery scans across major vibe-coding platform domains. Review your cybersecurity stack. As with most cybersecurity best practices, there are several tools that can help with securing vibe coding applications and the applications developed: - Browser security provides unique visibility into vibe coding applications– identify where the employee describes the application, uploads data, connects production integrations, and deploys. - Add vibe-coding domains Lovable, Replit, Base44, Bolt, Netlify to your DLP policy as monitored destinations. This does not stop employees from building. It ensures that when sensitive data moves through these channels, you have a record. - Implement OAuth and API key governance to detect when production credentials are connected to unregistered applications Extend application security to non-developer-built applications. Mandate human-in-the-loop reviews for critical functions built by non-developers. Treat prompts as source code requiring auditability. Establish ownership and lifecycle rules for every vibe coded application deployed within the organization — including named owners and data classification. Enforce infrastructure-level controls on AI agents, not just instructions. A Replit incident demonstrated that telling an AI agent not to modify production data is not the same as preventing it from doing so. Read-only database connections for AI agent access, enforced at the infrastructure level, are not optional. Agents need the same access controls as any other actor in your environment. The Clock Is Ticking While authorities like the UK’s NCSC, the EU, and CISA urge the development of long-term safeguards for secure-by-design AI tooling, the immediate reality is far more pressing. There is likely a live application connected to your production database—accessible to anyone with a URL—that your security team hasn’t found yet. It’s time to start looking. Related: Vibe Coding’s Real Problem Isn’t Bugs—It’s Judgment Related: Vibe Coding: When Everyone’s a Developer, Who Secures the Code?
securityweek.comJun 8, 2026extracted
Agentic AI Is Transforming Defense, But Only Secure IT Infrastructure Will Maximize It
Over the past several weeks, the cybersecurity community has been reminded how quickly frontier and agentic AI in defense networks can challenge our assumptions. When Anthropic's Claude Mythos model was made available to a limited set of organizations as a technical preview, it was reported that an unauthorized group claimed that it had gained access within hours. The incident, if true, was more than a possible breach. It was a warning. The potential impact of advanced AI on U.S. defense and intelligence networks is significant. As the U.S. government moves to deploy AI capabilities on classified networks, the opportunity is clear: advanced AI can help accelerate decision superiority for American forces. But the risks are expanding just as quickly, particularly as agentic AI begins to operate across sensitive networks, data environments, and mission workflows. AI adoption is not simply about deploying powerful models. It requires the right security, governance, and resilient infrastructure around them. AI is only as trustworthy as the data it uses, the networks it touches, and the controls that determine who and what can access it. In classified environments, that challenge is compounded by the need to move information securely across classification levels, compartments, coalition boundaries, and operational environments. For AI to rapidly deliver the expected decision advantage, three important areas must be considered: 1. What is entering the model? Training data and commercial models must move quickly but securely into classified environments. Without proper inspection, even the strongest AI model can become a liability by processing stale information or ingesting 'poisoned' content that leads to compromised assessments. 2. Who and what can access the AI? Cleared analysts, coalition partners, edge operators, and AI integration teams will all require governed access that enforces security boundaries without inadvertently 'collapsing' networks together. 3. Where is the AI agent reaching back out? Every model call to a database, mission system, or coalition partner must preserve the integrity of the classification layer. If AI is going to compress operational timelines, the security boundary cannot become the first point of failure. AI Mission Advantage Starts with Secure Infrastructure All of this depends on the network layers beneath the models. Everfox is enabling defense and intelligence agencies to keep pace with revolutionary changes in AI without compromising mission speed and security. Our technologies provide a secure network fabric built on cross domain capabilities and hardware-enforced protection that is purpose-built for classified environments and the tactical edge, all so AI can be securely and confidently deployed at mission scale. AI introduces risk across every layer: system components, integrations, downstream outputs, and mission workflows. As defense and intelligence organizations accelerate adoption, AI tools will increasingly operate across domains, compartments, and operational theaters. In these environments, trusted infrastructure, strict access controls, and strong data governance are not optional. They are mission critical. Sensitive data must be able to move securely across classification boundaries, with threats and policy violations identified before they ever reach a model. If we want to deploy AI responsibly at scale, we have to build security in from the start, not bolt it on after the technology is already embedded in mission operations. Frontier AI will be an important engine of future mission advantage. But without a secure network fabric to carry it, even the best models cannot be trusted to operate where and when they matter most. Note: This article is written and contributed by Dave Wajsgras - Chairman and CEO of Everfox.
thehackernews.comJun 4, 2026extracted
Top 5 Things CISOs Need to Do Today to Secure AI Agents
By Itamar Apelblat, Co-Founder and CEO, Token Security Agentic AI represents a once-in-a-generation shift in how organizations operate. AI agents are not copilots. They are not better chatbots. They are autonomous actors that plan, decide, and act. Increasingly, they will write code, move data, execute transactions, provision infrastructure, and interact with customers often without a human in the loop. They will also operate continuously, across systems, at machine speed. This transformation is already unlocking enormous business value. But, it will only succeed if it is secured properly. And today, most organizations are not prepared. The prevailing approach to AI security focuses on guardrails such as prompt filtering, output controls, and behavior monitoring. That thinking is flawed. Guardrails attempt to constrain behavior after access has already been granted. But once an AI agent has credentials and connectivity, a single misstep can cause data exfiltration, destructive actions, or cascading failures across interconnected systems. If you want to secure AI agents without slowing innovation, they need to rethink the control plane. Identity, not prompts, not networks, not vendor assurances, is the only scalable foundation for securing and governing autonomous systems. For a deeper explanation of why identity is becoming the foundation for AI security, see Securing Agentic AI: Why Everything Starts with Identity. Here are the five most important actions CISOs should take today to ensure AI agent security: 1. Treat AI Agents as First-Class Identities The moment an AI agent connects to production systems, APIs, cloud roles, SaaS platforms, or infrastructure, it stops being an experiment and becomes an identity. Every AI agent uses identities, often many of them: API tokens, OAuth grants, service accounts, cloud roles, secrets, and access keys. Yet in most organizations, these identities are invisible, unmanaged, and poorly governed. You must mandate that every AI agent is treated as a first-class digital identity: It must have a clear owner It must be authenticated Its permissions must be explicitly defined Its activity must be logged and monitored If you don’t know which identities your agents are using, you don’t control them. 2. Shift from Guardrails to Access Control Guardrails assume that AI can be safely constrained by rules. But AI agents are non-deterministic and adaptive. With an unlimited number of possible prompts and interactions, bypass is not a question of if it will happen, but when. Even if prompt controls worked 99% of the time, 1% of infinity is still infinity. Security must move down the stack to where real control exists: access. You need to ask these questions: What systems can this agent reach? What data can it read? What actions can it execute? Under what conditions? For how long? Once access is tightly scoped, behavior becomes far less dangerous. Identity-based access control is the containment layer for autonomous software. Network controls are too coarse. Prompt filters are too weak. AI platform assurances are not enough. Identity is the only control plane that spans every system an agent touches. AI agents create, use, and rotate identities at machine speed, outpacing traditional IAM controls. Token Security helps teams manage the full lifecycle of AI agent identities, reduce risk, and maintain governance and audit readiness without sacrificing speed. Request a Tech Demo 3. Eliminate Shadow AI by Gaining Identity Visibility Shadow AI is not primarily a tooling problem. It is an identity problem. Developers, IT admins, and business users are already creating AI agents that connect to business-critical systems, leverage APIs, retrieve data, and trigger workflows. These agents don’t announce themselves. They simply start acting. When security teams lack visibility into these identities, Zero Trust collapses. Unknown agents become trusted by default because their credentials are valid. You must prioritize: Continuous discovery of machine and non-human identities. Identification of agent-related tokens, service accounts, and OAuth grants. Mapping which agents have access to which systems. If you can’t see it, you can’t secure it. And in the AI era, what you can’t see is often autonomous. 4. Secure Based on Intent, Not Just Static Permissions AI agents are goal-oriented. Two identical agents with identical permissions can behave very differently depending on their objective. This introduces a missing dimension in traditional access models: intent. To secure AI agents effectively, organizations must answer: What is this agent meant to accomplish? What actions are required to achieve that goal? Which actions are outside its purpose? An agent created to summarize support tickets should not be able to export the full customer database. An infrastructure optimization agent should not be able to modify IAM policies. Intent defines acceptable behavior. This breaks the dangerous assumption that agents can simply inherit human permissions. An agent acting “on behalf of” a highly privileged engineer should not automatically gain every permission that engineer has. Security for AI agents is not about predicting behavior. It is about enforcing intent through tightly scoped identity and access controls. 5. Implement Full AI Agent Lifecycle Governance Security failures rarely happen at the moment of creation. They happen over time. Access accumulates. Ownership becomes unclear. Credentials persist. Agents are modified, repurposed, and eventually abandoned, often silently. AI agents compress this lifecycle dramatically. What used to unfold over months can now happen in hours or even more rapidly. You must ensure lifecycle governance for every agent: Who owns it today? What access does it currently have? Is that access still aligned to its intent? When should secrets be rotated, access reviewed, or the agent decommissioned? Without continuous lifecycle control, risk compounds invisibly. If you cannot answer these questions at any given moment, you do not control your AI agents. New frameworks for AI agent identity lifecycle governance are emerging to address exactly this challenge, download Token’s new AI Agent Identity Lifecycle Management ebook for more information. Secure AI Is Scalable AI Agentic AI is inevitable and it is overwhelmingly positive for business. The value lies in autonomous access that allows agents to act across systems at scale and machine speed. But, autonomy without identity control is chaos. Organizations that bolt AI onto legacy, human-centric identity models will either overprivilege agents or slow innovation to a halt. Organizations that ignore identity will eventually lose control. The path forward is not to slow down AI. It is to secure it properly. Identity is the only scalable control plane for agentic AI. Lifecycle governance is non-negotiable. And security must enable, not obstruct, innovation. The companies that win in the coming decade will be those that leverage AI to transform their business while remaining secure. The key to doing that is identity. If you’d like to see how Token security is tackling agentic AI identity at scale, book a demo with our technical team. Sponsored and written by Token Security.
bleepingcomputer.comMar 17, 2026extracted
Switzerland built a secure alternative to BGP. The rest of the world hasn't noticed yet
FEATURE BGP, the Border Gateway Protocol, was not designed to be secure. It was designed to work – to route packets between the thousands of autonomous systems that make up the internet, quickly and at scale. For four decades, it has done exactly that. It has also, throughout those four decades, been exploited, misconfigured, and abused in ways that were predictable from the start. Route hijacks reroute traffic through hostile networks. Route leaks knock services offline. Nation-state cyber crews weaponize BGP to intercept communications at scale. These are not theoretical threats. They are documented, recurring events, and they remain possible today for one simple reason: BGP has no native way to verify that a network claiming to own a block of addresses actually does. A series of patches and extensions like Resource Public Key Infrastructure (RPKI), BGPsec, and RPKI-based Route Origin Authorization (ROA) have been layered over the original protocol in an attempt to address the worst of these vulnerabilities. They help at the margins. They do not solve the underlying problem. There is, however, a system that does, or at least claims to. SCION, which stands for Scalability, Control, and Isolation On Next-Generation Networks, is an internet routing architecture developed at ETH Zürich. Unlike the patches applied to BGP, SCION does not attempt to retrofit security onto a 40-year-old foundation. It replaces the foundation entirely. That redesign is the life's work of Adrian Perrig, professor of computer science at ETH Zürich and the principal architect of SCION. The boat full of holes Perrig has been worrying about internet security since 1991, when he first worked with Cisco routers before starting his bachelor's degree at EPFL. He has spent most of the intervening years trying to make the internet more secure. Eventually, he concluded it was the wrong approach. "You cannot bolt on security," says Perrig. "You cannot get to a truly secure global network unless you actually change the design. It's like saying you want to go to the Moon, so let's put rocket boosters on an airplane. No, you have to design the vehicle differently." Perrig launched SCION in 2009 after gaining tenure and the freedom to pursue something most of his colleagues told him was career suicide. His core frustration was simple: the same vulnerabilities had been documented since the 1980s, and nobody had tried to fix them at the architectural level. "The best security companies in the world are still being exploited through them," he says. "There has not even been an attempt to address them properly." Kevin Curran, a cybersecurity professor at Ulster University who has been teaching computer networks for 27 years, offers an independent assessment that lands in the same place. The internet, he says, was built without security in mind, and what followed was a succession of workarounds. "What we have had over 40 years is a series of Band-Aids," says Curran. "Nothing has come close to addressing the need for truly secure paths across an adversarial network." Perrig's metaphor for the current state of internet security is a boat full of holes: people run around with buckets, throwing water out and plugging gaps, but the hull remains compromised. Security today, he argues, works the same way: patches get applied, vulnerabilities get closed, and new ones open up elsewhere. SCION, in his framing, is a fundamentally redesigned vessel. Water might splash in from outside, but it doesn't pour through structural gaps. A different kind of routing To understand what SCION actually does differently, it helps to understand what BGP gets wrong. In today's internet, there is no cryptographic chain of custody for a packet's journey from source to destination. And if a network somewhere along the path fails, the rerouting process – which involves detecting the failure, finding a new path, establishing a new session, and reconciling in-flight transactions – can take minutes. SCION addresses this problem through three interlocking mechanisms. The first is multi-path routing. Where today's internet offers a single path between two points, SCION establishes tens or even hundreds of parallel paths simultaneously. If one fails, the system reroutes within milliseconds. Perrig is precise about the threshold: "Human reaction time for auditory stimulus is roughly 150 milliseconds, and for visual, it's 250 milliseconds. When outages are on the order of milliseconds, the human brain cannot notice it. That's how fast SCION switches." The second mechanism is isolation domains – ISDs in SCION terminology. Rather than relying on a small number of global trust anchors, or a sprawling ecosystem of over a thousand certificate authorities that all must be trusted simultaneously, SCION lets countries, regions, or organizations define their own local trust roots. An error or compromise in one isolation domain cannot propagate to another. Perrig offers a concrete historical example: an entity in Australia made a configuration mistake that caused ATMs across France, Norway, and continental Europe to fail simultaneously. That kind of cascading failure is structurally impossible in a SCION network. The third mechanism is cryptographic path validation. Every router along a SCION path provides a cryptographic signature. Packets cannot be silently rerouted through a network that wasn't part of the agreed path. The sender and receiver specify which paths they want to use, and those choices are enforced at the protocol level. Curran, who has no stake in SCION's commercial success, independently validates these technical claims. The isolated domains and cryptographic signing, he says, are the core of what makes the protocol meaningful: "A genuine attempt to give senders and receivers control over the path their data takes, rather than leaving it to intermediate routers whose behavior cannot be verified." 220 billion francs a day Fritz Steinmann has spent 30 years as a network engineer in the Swiss financial sector. Since 2009, he has worked for SIX Group, the operator of the Swiss Stock Exchange, Swiss securities clearing, and – critically – the interbank payment infrastructure used by around 120 Swiss financial institutions. In 2015, his management asked him to develop a replacement strategy for Finance IPNet, the 20-year-old MPLS network that connected those institutions. "Interbank clearing in Switzerland is around 220 billion Swiss francs per day," Steinmann says. "So it's not an option to fail, yet I had to give up, because there was no alternative." The options were unappealing. The public internet was not acceptable to Swiss banks for transaction settlement. SD-WAN required either a single operator – politically impossible given the multiple carriers already involved – or proprietary vendor lock-in that no one wanted. Steinmann first encountered SCION in 2017 through a partnership between SIX and ETH Zürich. He approached it with the skepticism of someone who had seen academic network projects fail to survive contact with operational reality. "Academia and industry usually don't fit so well together," he says. "They do great things but then usability is the challenge. However, what Adrian told us was really an eye-opener. It was the first time somebody had something that did not just make sense from an academic point of view, but where I immediately also saw real-world applications." The Swiss National Bank (SNB) had already been using SCION for some internal use cases. Given that SCION was being asked to carry payments settled between commercial banks and the central bank, this was a significant signal. In 2019, SIX and SNB joined forces to design what would become the Secure Swiss Finance Network (SSFN). It would take two years of security assessments, governance design, and testing before the network was ready. Building the SSFN turned out to be as much a governance project as a technology project. The network needed to admit banks, exclude miscreants, and handle the issuance of short-lived certificates, valid for three days to allow rapid revocation if a participant is expelled. It also needed to operate its own certificate authority (CA). No commercial CA was willing to take on the risk. The challenge wasn't technical, Steinmann explains. It was about process. How do you verify that UBS is actually UBS? How do you quantify the liability if you get it wrong? No existing CA had answers, so SIX built its own and has been running it in production for five years now. SCION's Trust Root Configuration – the mechanism for encoding which entities are permitted to participate and under what conditions – embeds the governance decisions of the network's voting members into the cryptographic foundation itself. The rules about who can join, and when they can be expelled, are not policies in a database. They are enforced by the protocol. Steinmann notes, with some satisfaction, that enforcement has already been exercised. Performance metrics, when they arrived in testing, exceeded expectations. When a carrier failed, the old Finance IPNet required a sequence of steps – detection, failover, path discovery, reconnection, authentication, session re-establishment, transaction reconciliation – that could take three to four minutes in total. During SSFN testing, Steinmann conducted a carrier shutdown exercise. He had asked his team to stand by before shutting down one of the network providers. Before he could give the signal, his colleague reported back: Oh, I already did it. I thought you had given the go-ahead. "We didn't notice a thing," Steinmann says. "Failover had been below one millisecond. Applications had no awareness that the underlying network topology had changed entirely." The SSFN went live in November 2021. In September 2024, Finance IPNet began its sunset. The old infrastructure, which had run for 20 years, is being phased out. The foundation nobody wants to renew So SCION works. The evidence is not a vendor whitepaper or a lab proof of concept. It is 220 billion Swiss francs settled daily on infrastructure that replaced a network Swiss banks trusted for two decades, with the predecessor in the process of being phased out. Then why, nearly nine years after first production deployment, has it not spread beyond Switzerland at scale? The barriers are several, and they compound each other. The first is standardization. BGP is an IETF standard. SCION is not. An IETF Independent Stream RFC is in progress – a formally published informational document that sits outside the IETF standardization track. Full standardization through the IETF working group process has not yet begun. For large organizations, that distinction matters. Deploying a protocol before it is standardized means accepting the risk that implementations diverge, that the eventual standard requires costly changes, or that the protocol never achieves the critical mass that would make standardization meaningful. The second is the chicken-and-egg problem inherent in any network technology. Nobody wants to be first. The pain of running traditional networks – the latency spikes, the route hijacks, the three-minute failover windows – is, as Steinmann puts it, known and bearable. Organizations have adapted to it. "We have gotten a bit numb," he says. "We are OK with the way it works, and not really thrilled to see the advantages of a new foundation." The third barrier is vendor concentration. A single company, Anapaya – a spin-off of ETH Zürich that packages SCION into deployable network products for carriers and enterprises – currently provides the only commercial implementation. Steinmann is frank about the catch-22 this creates. Cisco has told him directly that if SCION isn't a $20 billion business, they're not interested. But it cannot become a $20 billion business without companies like Cisco. The fourth barrier is the most fundamental, and the one Steinmann returns to repeatedly. Infrastructure renewal is psychologically different from other kinds of technology adoption. Nobody notices when it works. Everyone notices when it fails. And the effort of replacing something that is, by most metrics, still functioning is almost impossible to justify to a board focused on the house rather than its foundations. "When was the last time you renewed your house foundation?" Steinmann asks. "You don't. You would tear down the house first. But what we're doing here is renewing the foundation without tearing down the house." Perrig's view of adoption timelines is optimistic. He believes that within three to five years, SCION will be embedded in the fundamental network libraries used by thousands of applications – meaning developers won't need to think about it, it will just be there. ISPs in Benelux are already offering SCION connectivity. Some customers are switching providers specifically because their current ISP doesn't offer it. Perrig describes a self-reinforcing flywheel beginning to turn. "Two years ago I wouldn't have said this confidently," he says. "Now I can see it. I'm confident in five years, but hopefully three." Steinmann is more measured. He credits Perrig's optimism as necessary – without it, the project would never have reached this point – but does not share the timeline. "He's endlessly optimistic, which is necessary," says Steinmann. "But I have my doubts, because of the slowness of adoption and the willingness of people to experiment. The willingness to adopt something new that is unknown is just not there." Curran, approaching SCION from the outside, offers what may be the most useful framing. The technology is sound, its architecture addresses real weaknesses, and whether SCION itself becomes the dominant protocol or seeds a closely related successor matters less than the direction of travel. What would accelerate adoption, he suggests, is not incremental evidence but a sufficiently dramatic failure of the existing infrastructure. "If we see nation-states doing attacks which reroute traffic and take down national infrastructure – acts of war at the low level in the network, something where SCION would have provided the solution – then it will quickly be adopted," Curran says. "We have to see how state-sponsored attacks work in the next year or so. That would be the prime mover." Sovereignty, optionality, and the risk of the same coin SCION is increasingly discussed in the context of European digital sovereignty. Its architecture has obvious relevance to that project. Isolation domains allow countries or regions to define their own trust roots, independent of US-based certificate authorities. The theoretical kill switch that a hostile state actor might pull on conventional internet routing does not exist in a well-designed SCION deployment. Perrig is deliberately careful with the sovereignty framing. He prefers the term optionality – the freedom to choose which paths to use, which trust roots to rely on, which networks to connect to – and resists the political weight that comes with sovereignty language. He is not wrong to be careful. The sovereignty framing overpromises what network architecture alone can deliver. Steinmann uses the sovereignty language directly, but without prompting introduces the caveat that most sovereignty advocates leave out. "Yes, it is a sovereign alternative, there is no central kill switch beyond your own jurisdiction's capabilities," he says. "But the same controllability could be misused by totalitarian approaches to government. It's then fully controllable. It will help reduce dependencies on allies who might turn evil. But it could also be misused as a weapon against a free internet. That's the drawback, and I won't judge what's better." Curran adds a constraint that is architectural rather than political: any network that wants to have value must interconnect globally. A sovereign SCION deployment that cannot route traffic to the rest of the internet is not a useful network. The technology enables meaningful control over path and trust, but it does not deliver sovereignty automatically or completely – and it doesn't pretend to. What SCION does offer – and what Switzerland has demonstrated in production – is a network in which operators know precisely whom they are trusting, where their traffic is going, and what the conditions are for participation. That is a form of control the public internet does not provide, regardless of what sovereignty framework you attach to it. The question nobody has answered The gap between what SCION can do and what it is currently used for is not, at its core, a technical problem. The technology has been validated under conditions most infrastructure operators will never face. The governance framework required to run it has been designed, tested, and operated at scale. The old network it replaced has been turned off. Not paused. Turned off. What has not happened is the leap from Switzerland to the rest of the world. SCION's deployment model – build the governance first, get the key parties committed, define the trust roots, enforce the rules – is precisely the kind of process that works in Switzerland and struggles almost everywhere else. Whether standardization, the European digital sovereignty agenda, or a sufficiently serious BGP incident changes that calculation remains, for now, an open question. Steinmann's final point was simple: nobody thinks about foundations until they crack. He is right that nobody renews a house foundation without being forced to. He is also right that it can be done without tearing the house down. Whether that is a reason to act now, or to wait until the structure starts to shift, is a decision the rest of the world has not yet made. ®
go.theregister.comMar 17, 2026extracted
RecordPoint MCP Server standardizes and secures AI access to compliant data
RecordPoint MCP Server standardizes and secures AI access to compliant data RecordPoint has unveiled its model context protocol (MCP) server, giving enterprises a secure, standardized way to expose governed data to external AI agents and platforms. The RecordPoint MCP Server allows any AI system, copilot, agent, or custom LLM app to safely access governed, compliant data from the RecordPoint platform without custom integrations or elevated permissions. By standardizing how AI systems discover and use governed resources, the RecordPoint MCP Server eliminates data fragmentation and accelerates AI adoption. It is the safest, most future-proof way to deliver compliant, governed data into any AI environment. RecordPoint Head of Product Joseph Pearce said, “If you’re building AI agents, deploying AI platforms, or scaling AI adoption across the enterprise, the RecordPoint MCP Server gives you the governed data connectivity you need without the security and compliance headaches.” “You don’t have to wait 18 months to clean up your SharePoint, Google Drive, or file shares. You can safely expose them today.” Enterprises working with AI today face a challenge: to get the most out of their AI tools, they need to provide them with data. But giving them governed, compliant data introduces serious risks: compliance teams lack visibility and control over what they can access, current integrations are proprietary, inconsistent, or insecure, and a lack of standardization slows AI transformation. The RecordPoint MCP Server brings governed enterprise data into the MCP ecosystem. With this capability, enterprises can connect any AI system to their governed records, allowing AI to interpret, reason over, and take compliant action on trusted information. “Most governance vendors are still figuring out how to bolt AI onto their existing architectures. But every bespoke AI integration becomes another pathway auditors will ask you to explain,” Joseph Pearce said. The RecordPoint platform was built from the ground up to focus on the data, allowing it to handle the complexity of modern data estates. The RecordPoint MCP Server replaces the sprawl with a standardized, permissioned, and auditable way for AI systems to access governed records, so highly regulated customers can move faster from pilot to production without relaxing controls or granting elevated access. “This MCP Server is a standard interface for AI systems to tap into to receive compliant, governed data, regardless of where you are on your governance journey,” RecordPoint Head of Product Joseph Pearce said. Every bespoke AI integration becomes another pathway auditors will ask you to explain. The RecordPoint MCP Server replaces that sprawl with a standardized, permissioned, and auditable way for AI systems to access governed records, so highly regulated customers can move faster from pilot to production without relaxing controls or granting elevated access. Key capabilities of the RecordPoint MCP Server: Governed data exposure without leaking sensitive content Permissioned and auditable AI access Seamless integration with any AI agent or platform
helpnetsecurity.comMar 3, 2026extracted
Signal’s Post-Quantum Cryptographic Implementation
Signal’s Post-Quantum Cryptographic Implementation Signal has just rolled out its quantum-safe cryptographic implementation. Ars Technica has a really good article with details: Ultimately, the architects settled on a creative solution. Rather than bolt KEM onto the existing double ratchet, they allowed it to remain more or less the same as it had been. Then they used the new quantum-safe ratchet to implement a parallel secure messaging system. Now, when the protocol encrypts a message, it sources encryption keys from both the classic Double Ratchet and the new ratchet. It then mixes the two keys together (using a cryptographic key derivation function) to get a new encryption key that has all of the security of the classical Double Ratchet but now has quantum security, too. The Signal engineers have given this third ratchet the formal name: Sparse Post Quantum Ratchet, or SPQR for short. The third ratchet was designed in collaboration with PQShield, AIST, and New York University. The developers presented the erasure-code-based chunking and the high-level Triple Ratchet design at the Eurocrypt 2025 conference. At the Usenix 25 conference, they discussed the six options they considered for adding quantum-safe forward secrecy and post-compromise security and why SPQR and one other stood out. Presentations at the NIST PQC Standardization Conference and the Cryptographic Applications Workshop explain the details of chunking, the design challenges, and how the protocol had to be adapted to use the standardized ML-KEM. Jacomme further observed: The final thing interesting for the triple ratchet is that it nicely combines the best of both worlds. Between two users, you have a classical DH-based ratchet going on one side, and fully independently, a KEM-based ratchet is going on. Then, whenever you need to encrypt something, you get a key from both, and mix it up to get the actual encryption key. So, even if one ratchet is fully broken, be it because there is now a quantum computer, or because somebody manages to break either elliptic curves or ML-KEM, or because the implementation of one is flawed, or…, the Signal message will still be protected by the second ratchet. In a sense, this update can be seen, of course simplifying, as doubling the security of the ratchet part of Signal, and is a cool thing even for people that don’t care about quantum computers. Also read this post on X.
schneier.comOct 29, 2025extracted
Majority of Organizations Ship Vulnerable Code, Study Finds
As AI-generated code becomes more mainstream, a new study by Checkmarx reveals that 81% of organizations knowingly ship vulnerable code. According to a study of 1500 CISOs, AppSec managers and developers, half of respondents already use AI security code assistances and 34% admitted that more than 60% of their code is AI generated. This is despite AI-generated code often containing known vulnerabilities by default. The findings are part of a Checkmarx study titled Future of Application Security in the Era of AI published on 14 August, 2025. The study surveyed professionals from Europe, North America and Asia-Pacific. Regionally, 32% of European respondents said their organization often deploys code with known vulnerabilities, compared with 24% of those in North America. The findings highlighted that 98% of respondents experienced a breach stemming from vulnerable code in the past year, a sharp rise from 91% in 2024. Checkmarx noted that the growing adoption of AI coding assistants is eroding developer ownership and expanding the attack surface. Within the next 12 to 18 months, 32% of respondents expect Application Programming Interface (API) breaches via shadow APIs or business logic attacks. Code Development Lacks Security Governance Fewer than half of respondents reported deploying foundational security tools, such as mature application security tools like dynamic application security testing (DAST) or infrastructure‑as‑code scanning. Meanwhile, only half of organizations surveyed actively use core DevSecOps tools and just 51% of North American organizations report adopting DevSecOps. “The velocity of AI‑assisted development means security can no longer be a bolt‑on practice. It has to be embedded from code to cloud,” said Eran Kinsbruner, vice president of portfolio marketing at Checkmarx. “Our research shows that developers are already letting AI write much of their code, yet most organizations lack governance around these tools. Combine that with the fact that 81% knowingly ship vulnerable code and you have a perfect storm. It’s only a matter of time before a crisis is at hand.” To overcome the issues identified in the report, Checkmarx encourages organizations to operationalize security tooling that focuses on prevention. The application security firm also noted that policies for AI usage need to be established. Currently, governance is lagging in this area despite AI-generated code becoming mainstream. Agentic AI can also be used to automatically analyze and fix issues in real-time. “AI generated code will continue to proliferate; secure software will be the competitive differentiator in the coming years,” Kinsbruner said. The release of this report follows Checkmarx’s announcement of general availability of its Developer Assist agent, with extensions to top AI-native Integrated Development Environments (IDE) including Windsurf by Cognition, Cursor and GitHub Copilot.
infosecurity-magazine.comAug 15, 2025extracted