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Kremlin cyber goons have been breaking into government and commercial networks for at least a year by exploiting a Zimbra bug with a novel twist on Russia’s usual phishing expeditions: this attack occurs as soon as the victim looks at an email, with no need to even click on a link or open a file. These attacks have been ongoing since July 2025, according to a whopping 27 US, UK, and other international government agencies, which attribute the intrusions to a group they track as Laundry Bear, aka Void Blizzard. “Laundry Bear’s targeting is almost certainly to gather sensitive information for the Russian Federation, with these actors primarily focusing on the covert acquisition of email data,” according to the joint security alert. The Russians’ latest campaign targets CVE-2025-66376, a cross-site scripting (XSS) vulnerability in the Zimbra web-based email and collaboration suite that was patched in November 2025 – but Moscow's attackers began exploiting it long before then. This type of vulnerability allows attackers to inject malicious JavaScript into web pages viewed by the victim. In this case, the phishing bears abused the security hole in the Zimbra Collaboration Suite by sending malware-laden HTML email messages to target Western organizations. Targeted orgs include those in the defense industrial base, federal and local governments, education, energy, law enforcement, media, non-governmental organizations, and technology sectors. Some of the email addresses used in this campaign include ivanka.zurabishvili@proton[.]me, zmul1@buildandconsulting[.]com, garrysmithme@pinmx[.]net, and hostingclient@pinmx[.]net, we’re told. The attack doesn’t require any user interaction other than viewing the malicious email, and once that happens, the attackers get to work exfiltrating a ton of data. This includes the victims’ last 90 days of email communications, email addresses and passwords, the organizations’ email directories such as global address lists, two-factor authentication tokens, and newly created application passcodes. Then the attackers use these stolen credentials to maintain access to the victims’ email, modifying account preferences and collecting authentication information. Laundry Bear stores the stolen goods on an unattributable virtual private server (VPS) running its custom “Flowerbed” collection framework. Flowerbed is a Python project that uses Docker for containerization. “The simplistic Flowerbed codebase has indications that artificial intelligence (AI) played a role in its development,” the government agencies noted. The 31-page security alert includes an extensive indicators of compromise (IOC) section, which organizations should review to identify individuals compromised by the campaign. Also, the agencies recommend minimizing employees’ use of the ZCS webmail client until their organizations update to a patched version that is not vulnerable to CVE-2025-66376. ®

At least 2.2 million vehicles fitted with dealer-installed KARR and SWDS security systems are vulnerable to nearby Bluetooth attacks that can unlock doors or prevent a stopped vehicle from starting, according to researchers at the University of California San Diego. An advance look at the research published by UCSD this week (the full writeup won’t be available until August 12) reveals that KARR and SWDS security devices manufactured by Acrisure contain a serious flaw: They “all … rely on the same secure key,” the researchers found. What that means, according to the researchers, is that anyone who knows the key, has a device with a Bluetooth connection, and can get within five yards of an affected vehicle can unlock it, make the horn honk, flash the headlights, or even prevent it from starting. “Instead of smashing a window to get access to a vehicle, thieves could simply connect remotely via Bluetooth to the device inside the vehicle, and make it unlock car doors,” Jerry Yu, coauthor on the research and UCSD compsci graduate, said in the release. KARR/SWDS devices are installed by dealerships. Along with providing key fob-like functions, they also serve as an antitheft device, allowing dealers and buyers to track cars with the devices installed in the case of theft. According to UCSD, the devices are typically sold as a paid upgrade at dealerships around the US. KARR says its products are available through more than 3,000 dealerships nationwide. Per the researchers, however, those devices remain active even if a buyer declines the service, meaning those who don’t have an active KARR/SWDS contract are still at risk. “Removing the devices is not trivial,” UCSD compsci PhD candidate and paper co-author Yibo Wei said in the university’s report on the research. “You have to open up the dashboard and cut and reconnect the wires that are deeply intertwined with the car’s computers and ignition system.” In other words, there are likely a lot of cars on the road with one of these units installed, and for many owners, a KARR or SWDS window sticker may be the only obvious indication. The researchers said that most vulnerable vehicles were purchased in Southern California in the past nine years from Honda, Toyota, Mazda, Ford, and Jeep dealerships. Secondary market resales, however, mean affected vehicles can be found throughout the US and even as far away as Japan, the team noted. They also discovered a public database that stores information about equipped vehicles, according to UCSD. For those worried their vehicle may be vulnerable, no need to worry: KARR Security has already released a firmware update for affected devices that can be installed by both active customers and those with an inactive security system; steps are included on the company’s website. It’s not clear if KARR is notifying customers of the need to update their security system - we asked, but the company didn’t directly respond to that question. What KARR did tell us was that, in contrast to the UCSD finding that “all KARR-SWDS devices rely on the same secure key,” it claims that only a small percentage of devices “with certain Bluetooth-related components” are actually affected. “The vulnerability described in the research is highly complex and presents a low risk to customers under real-world conditions,” a KARR spokesperson told us. “Nevertheless, we responded promptly and developed a firmware update to address the issue.” The vulnerability was discovered serendipitously by the UCSD researchers years ago when they were doing research on credit card skimmers and spotted Bluetooth fingerprints they couldn’t identify. After figuring out they had spotted car security systems, the team started digging into the devices, and here we are. We contacted the team to get more detail on their findings, but didn’t hear back. They’ll be presenting their work at DEF CON on August 9, and the USENIX Security conference on August 12. ®

It's a bad day to be an Oracle admin: Big Red has just released 1,449 security patches ready to be applied. The patches were released as part of the company's quarterly security fixes, and the record number may partly reflect Oracle's internal push to harness AI for vulnerability detection, which it announced in April. Oracle also manages a huge product portfolio, and the patches span numerous products, so the total shouldn't come as too much of a surprise. Instead, experts speaking to The Register unanimously agreed that any concerns over the number of patches should be reserved for the admins responsible for applying them, rather than for Oracle's code quality. "While a record 1,449 patches sounds alarming, it mostly reflects the massive scale of modern software ecosystems and the industry's shift toward aggressive, automated security scanning," said Dray Agha, senior manager of security operations at Huntress. "Frankly, the real story isn't the sheer volume of bugs, but rather the immense operational strain this puts on enterprise IT teams who must now race to separate the critical threats from the routine fixes without breaking business operations." Others, like Matei Badanoiu, lead security researcher at Pentest-Tools.com, say these bumper batches of security updates are likely to become the norm, owing mainly to AI-assisted bug hunting. Microsoft's monthly Patch Tuesday updates have ballooned in size in the last few months too, and not without warning. July's record 622 CVEs eclipsed June's 206, which at the time was an all-time high, and Microsoft warned just days before that the role of AI in vulnerability detection will make defenders even busier. "As AI helps defenders discover more issues, customers will see a higher volume of security updates included in each security release," Microsoft Windows veep Pavan Davuluri wrote in a blog post. Davuluri noted that Microsoft offers various automated patching tools and encouraged customers to make use of them to ease the ever-increasing burden of applying an unprecedented volume of security fixes. Similarly, Oracle's Integrated Cyber Center wrote in a blog post that customers feeling overwhelmed by the scale of their patching duties should make use of support resources provided by its various teams: My Oracle Support, Technical Account Management, and Customer Success. Big Red's big bet on AI for vulnerability detection has also led to a shakeup in how it delivers patches to customers. Starting in May 2026, Oracle began supplementing its quarterly updates with monthly patch batches for the most critical bugs it finds. Named Critical Security Patch Updates (CSPUs), these will be smaller but more frequent, allowing defenders to stay on top of the most pressing threats. Oracle said: "This approach enables customers to apply critical fixes more quickly on premises, while continuing to support established quarterly patching cycles through cumulative updates." Priority patches Only ten of the 1,449 patches carried a maximum CVSS score of 10.0, all of them affecting Oracle Fusion Middleware. Of these, two were highlighted as particularly dangerous by the Dutch NCSC: CVE-2026-47056 and CVE-2026-60217. Neither vulnerability is cataloged with a Common Weakness Enumeration (CWE) identifier, although both are described as easily exploitable. An unauthenticated attacker can exploit CVE-2026-47056 via HTTP to take over Oracle Data Integrator, while CVE-2026-60217 allows the same against Oracle Coherence over TCP. Urging customers to apply updates as soon as possible, NCSC-NL said: "Depending on the vulnerability, an attacker can execute malicious code, view sensitive data, or take over a system completely. Due to the severity of the vulnerabilities and the lack of authentication, the risk of exploitation is high." Badanoiu, meanwhile, told us that he was especially concerned about CVE-2026-61211 (9.9) and CVE-2026-47040 (9.1) – the two top-rated vulnerabilities affecting Oracle Database Server. "CVE-2026-47040, in Oracle Net Service, leads to an unauthenticated vulnerability through which attackers gain access to any stored data and the risk of persistently crashing the service," he explained. "And CVE-2026-61211, in the DBMS_CLOUD package, carries the highest score in the batch, where a low-privilege attacker can get remote code execution and takeover of Oracle's RDBMS as well as downstream implications for other products that use the database." ®

The US Cybersecurity and Infrastructure Security Agency (CISA) has expanded the scope of its alert on Iranian-affiliated hackers attacking critical infrastructure, including water and energy facilities. The original advisory focused on programmable logic controllers (PLCs) manufactured by Rockwell Automation/Allen-Bradley. The update warns that the activity may also target devices from Schneider Electric, Siemens, "and potentially other branded/manufactured PLCs." The conflict between the US and Iran is well into its fourth month, and authorities have noticed Iranian-affiliated advanced persistent threat (APT) crews targeting PLCs to cause disruption since March. PLCs are used to control and monitor industrial processes. Authorities said the activity resembled earlier attacks on PLCs by CyberAv3ngers (aka the Shahid Kaveh Group) - hackers affiliated with Iran's Islamic Revolutionary Guard Corps (IRGC) Cyber Electronic Command (CEC). The focus is principally related to internet-facing PLCs. CISA noted attackers targeting devices through open ports: "The targeting of ports associated with other OT vendors' protocols suggests these actors are opportunistically targeting devices manufactured by companies other than Rockwell Automation/Allen-Bradley, including Schneider Electric and Siemens. "In one reported instance, the actors utilized Dropbear Secure Shell (SSH) software on victim modems to enable them to gain remote access through port 22." Once in, attackers extract device project files and modify or delete their logic. "Additionally, the changes disabled critical shutdown and alarm logic, allowing systems to enter unsafe conditions without notifying operators of the anomalies," CISA said. The expansion of the advisory's scope to include additional PLCs highlights the importance of being aware of what is accessible. On top of to earlier mitigations that included disconnecting the PLC from the public-facing internet, authorities have suggested organizations consider implementing isolated architectures and controlling network access to PLC devices. It would also be a good idea to check project files running on PLCs for unauthorized changes, make sure service providers are aware of threats targeting PLCs, and ensure default passwords are changed. ®

One click on what looked like an ordinary ChatGPT link could plant an attacker-controlled AI agent inside a company's ChatGPT workspace, according to researchers who uncovered a flaw in OpenAI's workspace agents. Security firm Zenity Labs has dubbed the bug "AgentForger," saying its proof-of-concept showed it was possible to silently create, configure, publish, and schedule a malicious workspace agent inside a victim's ChatGPT account. The technique depended on the victim belonging to a workspace where agents were enabled and having permission to create them. Any connected apps and actions would also have to be allowed by the organization's administrators. Rather than stealing passwords or browser sessions, the technique effectively tricked ChatGPT into building an autonomous assistant that could act through the employee's connected accounts and permissions. If the victim had already connected services such as Outlook, Teams, Slack, SharePoint, or Google Drive, and the workspace allowed the relevant actions, Zenity says the agent could use them too. According to Zenity, that meant it could rummage through corporate data, send messages as the employee, and continue running long after the original phishing email had done its job. The weak spot was ChatGPT's agent builder, the feature used to spin up AI assistants that can work across email, chat, calendars, and other business apps. Zenity found it would accept instructions embedded inside what looked like an ordinary ChatGPT link. One click later, Zenity says, the builder got to work on the attacker's behalf, wiring up the victim's existing connectors, turning off approval prompts, publishing the new agent, and setting it loose on a schedule. From there, the researchers turned the agent into what amounted to a corporate mole. Instead of reaching out to conventional command-and-control infrastructure, it simply checked the victim's inbox for emails from the attacker with "TASK" in the subject line. Each message became a new assignment, whether that meant searching company files, collecting sensitive documents, or sending the results back by email. "This isn't a forged request, it's a forged insider," Michael Bargury, co-founder and CTO of Zenity, told The Register. "With one click, an attacker gets a fully autonomous agent inside your company that has your people’s identity and access, with the guardrails off. Attackers no longer have to break in to steal your data. They can forge an insider to go get it for them. This is an agent trust failure, and existing security controls were never built to see it."
 Zenity's proof-of-concept scenarios included automatically mapping an organization's people and projects by trawling Outlook, Slack, Teams, calendars, and file stores, hunting for passwords and API keys buried in chat messages, and sending convincing phishing messages through the victim's own Teams account. The researchers also demonstrated business email compromise-style lures and other forms of employee impersonation. Zenity reported the issue to OpenAI through Bugcrowd on June 4. According to the researchers, OpenAI acknowledged the report the following day and fixed the vulnerability four days later by removing the URL parameter that enabled the attack before it was publicly disclosed. OpenAI did not immediately respond to The Register's questions. The bug itself may be gone, but as AI agents graduate from answering questions to taking actions across corporate systems, the attack surface starts looking a lot less like software and a lot more like your workforce. ®

Tired of worrying about how you might recover all the precious data stored in your Google account if you somehow lose your devices and forget your email address and phone number? Just give Google a video of your face and AI will recognize you to restore access. Selfie sign-ins are now available for Google accounts, the Chocolate Factory announced on Thursday. This option is restricted to regaining access after email or phone recovery options fail. Going through the process of adding a verification selfie is rather simple: Just follow the steps outlined on Google’s help page for selfie video management to enroll. You need a device with a camera and the ability to move your head from side to side in order to show off your profile, as well as your full-frontal face card. That side-to-side movement is designed to prevent the use of live deepfake videos, as real-time face replacement tends to struggle with profiles. According to Google, if you can’t use any other account recovery method, the company’s system can prompt you to take another selfie video for comparison to the one taken earlier, verifying it's you and letting you back into your account. Why this, why now? This feature announcement from Google raised a number of questions among The Register’s news team. Why now, for starters? Deepfake videos are constantly improving, and it’s likely only a matter of time until a side view can be handled with ease. A Google rep told The Register that it sees a trend toward passkeys and other forms of device-based authentication, which means a lost device often means a lost account. “Users can choose whatever method they prefer, we expect most will prefer the ease of use of passkeys for signing in regularly, and use selfie for times like when they lose their phone or the device with their passkey,” Google said in response to our questions. So it is not like Apple’s Face ID or face unlock on Android, Google confirmed – “they serve different purposes.” That, and it might not even be sufficient to prove you’re you. “Passing a selfie video alone may not always be sufficient to get back into your account,” Google explained in the email. “We evaluate the overall risk based on many factors and may require additional sign-in methods to help make sure it’s actually you signing into your account.” That's because Apple devices with Face ID, and some higher-end Android devices, are equipped with infrared cameras that capture depth maps to match points on a user’s face to a stored 3D map of their appearance. Those are harder to fool. Google’s selfie sign-in system, on the other hand, is essentially relying on plain video, AI, and the hope that deepfakes haven’t become good enough to get around those turn-to-the-side distortions. Unfortunately, facial recognition AI is reliably unreliable. Heck, even Google’s had plenty of run-ins with it over the years, and good facial recognition algorithms are a hot commodity nowadays. Then there's the fact that you’re giving Google a live recording of your face, and that could be quite valuable to the company in other contexts. As Google noted in its announcement, those facial scans are encrypted at rest, are only stored with user consent, and are “used only for helping you sign in, unless you opt to share it for additional purposes.” “You have the option to allow Google to use your video and related data to help ongoing efforts to develop and improve facial recognition, age estimation, and other verification methods,” the company notes on the selfie help page. The option, labeled “Improve Google Services” on the page where users can record a selfie for account recovery purposes, is unselected by default, but we could imagine Google has a vested interest in getting you to click that. ®

Swiss rail manufacturer Stadler Rail says it refused a CHF 10 million ($12.3 million) ransom demand after the Everest ransomware gang compromised one of its suppliers. Stadler will not pay, and based on its account of events, the company appears to have got off lightly. It stated that "no security-relevant data [was] affected" in the breach, which was limited to "technical information from a supplier." According to its announcement, "no relevant personal data was stolen," and the incident had no impact on the functioning of its rolling stock (train and tram carriages) or its global production lines. The attackers accessed the technical data through a "data exchange platform" Stadler used with the unnamed supplier, authenticating with compromised login credentials. "Stadler's IT systems were not compromised and remained intact," the company said. At the time of writing, Stadler does not appear on Everest's data leak site (DLS), nor has the swiped technical data been leaked. Stadler's absence from the extortion group's website is unusual. The typical cyber extortion playbook involves the crooks first notifying victims that data has been stolen and/ or encrypted, then issuing their demand and threat to leak data if the ransom is unpaid. Failure to meet the deadline - or refuse outright, as Stadler did - typically lands the victim organization a spot on the extortionist's DLS. That's often when a second countdown timer begins. Criminals typically offer victims another few days to realize they are not bluffing and will leak the stolen data if a fee isn't paid. If they pay, victims are scrubbed from the DLS. If they don't, their data is leaked. That's the usual playbook. However, for a victim to both refuse to pay a ransom and not appear on the gang's DLS is an oddity. Everest, a Russian-speaking cybercrime group, has operated since circa December 2020 and claimed attacks on sportswear giant Under Armour, Mailchimp, AT&T, and Collins Aerospace, to name just a few. It's dabbled in both encryptionless extortion and double extortion, and has branched out into initial access brokering and recruiting corporate insiders. ®

PWNED Welcome back to PWNED, the weekly column where we focus on security own-goals so you can avoid them. This week’s topic involves serious problems in the healthcare sector, specifically the very human problem of compromised gatekeepers. Have a story about someone leaving a gaping hole in their network? Share it with us at pwned@sitpub.com. Anonymity is available upon request. Our legend of lameness comes courtesy of red teamer Dahvid Schloss, who shared so many great stories with us that we’ve featured his tales a couple of times before. Schloss has made a career out of testing not only network security but also physical security at a wide variety of places. He has learned that if you act as you belong, people will usually treat you like you belong. At one hospital, Schloss was hired to test security by getting access to the records room and trying to steal a specific physical file that his client left there for him to pilfer. The challenge was that the records room had both an electronic lock and a nurse gatekeeper guarding it. Schloss told us that he considered several approaches to get into the records room. He could try picking the lock, cloning a badge, or even stealing the badge of someone who had access. Instead, he decided to try social engineering. Schloss did research on the hospital and he put on a pair of appropriate scrubs and made himself a fake security badge that could not possibly swipe in. Then he knew it was time to turn on the charm with the nurse who was on duty at the records room. And by “turn on the charm,” we mean “diss the doctor.” “Nurses talk a lot of shit. It's the law of the land when it comes to the hospital,” Schloss told us. So he tried to swipe his non-working badge and showed frustration when it didn’t work. Then he walked up to the window where the on-duty nurse was standing and won her over. “I'm doing fine, hon. How you doing,” he told the nurse. “Look, I'm gonna save you the details. But Dr Johnson's being an absolute asshole right now; he didn't pull out his patient records that he was supposed to pull out for trauma. We need these records, and they sent me down here. I'm brand new. I just started yesterday.” Schloss had done his research and picked out the name of an actual doctor on staff. What he couldn’t have known is that the doctor was actually a difficult person to work with. And the duty nurse let him know she was on his side before letting him in. “The nurse goes ‘honey, I know exactly the pain that you're going through,’” Schloss continued. “She goes ‘I got you’ and she opens the door, lets me in.” After Schloss went into the records room and retrieved the file, he hung around and talked to the nurse for another 10 minutes, complaining about how security was incompetent for not activating his badge and letting her complain about what jerks some of the doctors were. He even had a backstory about where he had worked before. She invited him to hang out and go for lunch sometime before he left with the folder. Other hospitals he tested had bad network security practices. He told us about one hospital where he sat down in the waiting room and logged into the guest Wi-Fi network and did a scan. What he found was that all the important devices in the hospital were on VLAN 1, the same network as guest Wi-Fi. All of the data coming out of medical devices like the MRI machine was readily accessible and unencrypted. He said that most medical devices at most hospitals he’s tested do not encrypt data that they send over the network. “So you're getting Social Security numbers just being populated over the network via the MRI machine and you're getting the patient data, the date of birth, all the PII that any organization would lose their shit about,” he said. Schloss said that he thinks hospitals he’s tested prioritize the ability to keep machines running and distributing data quickly over good security hygiene. If someone tried to get data, failed, and had to call IT for help, those precious minutes of delay could cost a life. But even if it's a matter of life and death, do not let someone into a restricted area just because they look and act the part. ®

OPINION OpenAI has acknowledged its models powered the autonomous agents that compromised HuggingFace infrastructure. It might be taken as a convoluted marketing stunt, were it not the perfect advertisement for China-based competition. The company's AI-culpa fits the narrative spun by US rival Anthropic about its Mythos models, which it deemed too dangerous to release except to totally trustworthy corporations and governments. OpenAI says: "The incident makes clear that advanced models can discover and exploit novel attack paths in real-world systems without source-code access. It highlights that advanced cyber capabilities must be developed alongside stronger safeguards and defensive tools." Are we surprised? It's been clear that AI models have the potential to go rogue and damage computers for several years. Academics have repeatedly warned about this possibility - even those affiliated with OpenAI and Anthropic. And anyone who has used AI models for software development has probably seen them code unexpected and perhaps unwanted workarounds to fulfill some directive. On Tuesday, the UK's AI Security Institute published findings about how frontier models all cheat. OpenAI's admission that its models devised a sandbox escape to obtain internet access and found a zero-day flaw to exploit, all to solve a benchmark evaluation problem, may be unprecedented in terms of the scale and prominence of the systems affected. But it's a reenactment of every Claude or Codex prompt in which the model responds to a disallowed command by trying an alternative. We were warned. The compromise of HuggingFace's systems is no more surprising than locking a bear in a supermarket and finding a mess the following day. AI models are billed as artificial intelligence, but when they power agents handling tools in a loop to achieve some objective, it's the equivalent of a brute force attack – the agent will keep trying things until something works or breaks. The surprising part came when HuggingFace sought to employ US frontier models to defend itself. It failed. That should raise eyebrows. "When we started the log analysis, we first used frontier models behind commercial APIs," the AI model-mart said in its blog post last week. "This did not work: the analysis required submitting large volumes of real attack commands, exploit payloads, and C2 artifacts, and these requests were blocked by the providers' safety guardrails, which cannot distinguish an incident responder from an attacker." Stymied by model refusals – which developers have been complaining about for months – HuggingFace had to rely on GLM 5.2, an open-weight AI model made by China-based Z.ai, to conduct its forensic analysis. And it did so on its own infrastructure, so nothing sensitive got sent to a cloud-based model provider. Coincidentally, the leaders of OpenAI and Anthropic have reportedly been warning the US government about the threat posed by increasingly capable Chinese models like Kimi K3 and GLM 5.2. And the US government is said to be mulling possible responses to limit competition from China. That won't work. It's just naïve to think that the US government and a handful of worthy organizations – however that is defined – will be able to enforce a global monopoly on highly capable AI. The infrastructure required to run open weight models that more or less rival the current state of the art is available for a price. And potential consumers of those services are not going to be satisfied with model refusals when there are other options, particularly if they're more cooperative and more affordable. The best course for governments, industry, and the public is to push for AI services that are open and available to all. For that to work, lawmakers around the world need to act fast to set some common ground rules that grapple with AI's impact on jobs, and find a way to compensate those whose work fuels machine learning. Some industry leaders appear to realize that. David Sacks, an external White House adviser and tech investor, recently urged Silicon Valley to rally around openness. "The leading closed labs, already a duopoly in terms of AI model revenue, want the government to eliminate their open source competition," he wrote in a social media post. "They have laid their cards on the table. It is time for the rest of Silicon Valley — the vast majority that still values open competition — to do the same." The fact is that US AI companies have sandboxed themselves into a corner: They've created demand for a product that they can't be relied upon to provide. And when they do make their most capable AI models available, they hobble them and demand terms tailored to serve their vast debt rather than their customers. OpenAI said that it has invited HuggingFace into its trusted access program so the company can use its most capable models. Chinese AI companies, meanwhile, have invited the world. ®

If you're responsible for Linux security, someone just dumped a pile of work onto your desk: 432 Linux kernel CVEs were published across Sunday and Monday this week. Linux watchers at nixCraft pointed out the volume on Monday morning, and it didn’t take long for seasoned sysadmins to start expressing concerns. Jan Schaumann, chief information security architect at Akamai Technologies, took to the OSS-SEC mailing list Tuesday to express concerns over the sheer volume of Linux kernel CVEs published in recent days. Aside from noting that the CVE system isn’t the best way to track security changes, Schaumann also wondered in his post whether there was any good way to deal with so many kernel security issues. “This onslaught really shows it's not feasible to attempt to prioritize individual kernel changes,” Schaumann said. “You might attempt to process this large set of changes by pointing an LLM at the intake and asking it to prioritize them,” he suggested, “but if it spits out a dozen today and another 25 the next, you haven't won much.” Schaumann also suggested waiting to see which ones emerge as serious issues and focusing on those in the weeks to come, or updating one’s entire fleet of Linux machines on a weekly basis. “I sure would like to be able to do [that], but reality keeps getting in my way,” Schaumann said. “I'm not sure what to do here going forward.” In an email to The Register, Schaumann said that individually reviewing vulnerabilities for patching was already difficult enough before things rose to this level, and that automation may be the only option - but it's not a great one. "Automated, regular, and frequent updates that pull in all changes within a given time window of tolerance seem to me the only reasonable approach, but that is very difficult for many large organizations," Schaumann explained. Those orgs often rely on lengthy QA processes, slow and staged development cycles, and may even have contractual requirements for long-term support that make an automated approach an impossible one. The nixCraft team speculated on social media that AI bug reports are a likely reason for all those kernel CVEs, which wouldn’t be without precedent - Linus Torvalds himself said in May that the Linux kernel security mailing list had become “almost entirely unmanageable” due to AI-assisted bug hunting. Nonetheless, Torvalds has described AI as a useful tool for Linux development while still noting it can be a drag for maintainers, both from a workload standpoint and the fact "it keeps finding embarrassing bugs." On that note, it's worth understanding what a Linux kernel CVE actually means - many of the vulnerabilities included in the Sunday-to-Monday batch are small in scope, but they're vulnerabilities nonetheless. As senior Linux maintainer Greg Kroah-Hartman noted in a February blog post, the Linux kernel CVE team follows the CVE Program's definition of a vulnerability: a weakness in a product that can negatively affect a system's confidentiality, integrity, or availability. “At the level that the Linux kernel runs, almost any type of bug that can affect a running system can be classified as a vulnerability,” Kroah-Hartman noted. The kernel team looks at every bugfix that is added to stable kernel releases, he added, and if it fixes an issue that meets that CVE criteria, a CVE is assigned. AI-assisted bug hunting has increased the volume of reports reaching Linux kernel maintainers. We reached out to the Linux kernel team, but didn’t hear back. Kroah-Hartman did tell The Register earlier this year that AI bug reports had become worthwhile in recent months, and he predicted they're likely to keep adding to his workload. Unfortunately for Linux sysadmins, the position in which they find themselves in this current mess isn’t one that’s readily solved. CVEs might be a messy way to track and prioritize security updates, especially when hundreds of them are published over a short period, but without something better, it falls to IT and security teams to determine which vulnerabilities affect their systems and which kernel updates they need to deploy. Hope you’ve got the coffee machine filled up: The onslaught is unlikely to ease if other recent patch cycles are any indication. ®

EXCLUSIVE A Windows information-stealer targeting more than 300 applications comes equipped with a novel surveillance tool: an AI profiler that ranks infected victims so crooks know who to target first. Varonis Threat Labs spotted the new stealer and remote access trojan (RAT), called Dolphin X, for sale on a cybercrime forum, and shared their research exclusively with The Register. The ad for the malware claims it can target upwards of 300 applications and has the ability to bypass browser passwords and steal enterprise credentials, cryptocurrency wallets, .env files, SSH keys, cloud tokens, and DevOps secrets. Dolphin X also promises users a super-sneaky surveillance feature called the AI Profiler. It scores infected users by app usage, browsing history, and installed software, and sends the cybercriminals a daily summary that ranks victims’ based on the likely payoff from an attack. “There's two things that stand out,” Daniel Kelley, a senior threat researcher with Varonis, told The Register. “The first thing is the AI profiler. That's something I've never seen before. And then it’s also the breadth of applications that it steals - and it’s not even just applications. It’s everything, you name it: it will steal files, or credentials, cryptocurrencies. It’s probably one of the biggest stealers I’ve ever seen, and covers the biggest attack surface.” A malware vendor using the alias “Kontraktnik” posted Dolphin X for sale, promising: “You can use it as a stealer, as an HVNC [Hidden Virtual Network Computing], as a DDoS botnet, as a loader.” The crimeware currently only runs under Windows, but “we are working on Debian,” Kontraktnik claimed, adding that the malware also only supports English and Russian. Kelley suspects the developer is Russian-speaking, and told us that the stealer includes an option not to infect any users in the Commonwealth of Independent States (CIS) countries, a common choice among Russian-based ransomware and cybercrime gangs. Kelley and his team obtained and analyzed the malware builder, operator panel and its network traffic, but didn't examine a malware sample. Varonis therefore can’t guarantee that all of the developer’s claims are true. However, “when we looked at the builder, it had everything to suggest the features were legitimate,” he said. “We couldn’t test out the malware itself, but I would say it probably lives up to most of its expectations.” Feedback left on the forum where the malware is sold supports that analysis. As of Tuesday, the sales thread has passed 3,000 views, we’re told, with Kontraktnik closing at least two confirmed deals. Both of these included positive feedback from the buyers. Three-tier subscription model Beyond the 300 + apps it targets, Dolphin X's operator panel lists 329 features across 10 categories. Buyers can subscribe to one of three tiers, each unlocking new features, or buy a lifetime subscription. The minimalist suscription costs about $80 per month, which buys rewriting and altering capabilities across Windows Portable Executable (PE) timestamp, Rich headers, and section padding, along with capabilities allowing the malware to exploit the brittle YARA rules to bypass detection and hash-based blocklists. The middle tier advertises shuffling the import table, which would change the binary's import hash between builds. The top level sub (about $230 per month) claims to rewrite the code’s control flow, substitute instructions, and re-encrypt embedded strings with a new random key each time, thus making stable byte sequences harder to identify. Lifetime subscription cost about $1,140 for basic access, $2,280 for mid-tier malware, or $3,420 for perpetual pro-level Pwnage. “It really lowers the barrier to entry,” Kelley said, adding that in the not-so-distant past, cybercriminals needed a certain level of technical expertise to develop and use different types of malware. “Now it's set up in a way where it's almost like SaaS. Anyone can purchase it. Anyone can take it out of the package and use it.” All of this suggests two takeaways for defenders, according to the security sleuths. First, keep long-lived credentials off disk if possible. “Infostealers are designed to grab everything in one pass, so anything stored locally should be treated as potentially exposed,” the report warns. Second: focus threat detection on behavior - not file signatures - because this and other malwares include capabilities to bypass signature-based detection. “For example, explorer.exe running under a non-default desktop is a strong indicator of an HVNC session, regardless of how the malware binary is packed or what hash it uses,” the authors wrote. Varonis’ threat hunters previously uncovered other AI-powered malware, including an all-in-one phishing kit called Bluekit, and an email attack tool called SpamGPT. “It’s a huge trend,” Kelley said. “Cybercriminals are finding a lot of unique ways to integrate AI, and then they're using it to make their lives a lot easier, which is problematic.” ®

Authorities have long warned organizations not to pay ransoms, and fresh figures underline why: handing over the money doesn't mean the crooks leave you alone. Proofpoint survey data suggests that 58 percent of affected UK organizations paid a ransom. Worse, 22 percent of those who pay get extorted again anyway. The UK broadly tracks the global picture: 54 percent of victim organizations paid, though the rate swings sharply by region, from just 19 percent in Japan to 93 percent in the US. Cybersecurity biz Proofpoint, which published the data on Wednesday, attributes the regional variation to "a combination of regulatory environment, recovery capability, insurance incentive structures, and cultural norms around negotiation." "But the core finding holds everywhere: ransomware creates enough pressure that a significant share of organizations in each of the surveyed markets choose to pay." UK organizations that paid fared somewhat better than the 37 percent global average for repeat extortion. Still, the core lesson stands: paying doesn't reverse an attack. You can't trust a criminal's word. It just restarts a negotiation where the attacker holds every card, including the data, decryption keys, and the threat of publishing what they've stolen. Operation Cronos, law enforcement's LockBit takedown, provided hard proof of what had long been suspected: cybercriminals often retain victim data even after being paid. Before Dmitry Khoroshev's cybercrime empire collapsed, this was an assumption, not evidence-based. Cronos didn't just shutter the then-leading ransomware gang; it undermined the entire premise that paying restores the status quo. Proofpoint found that 2 percent of victims who paid a ransom never recovered their files at all. Earlier this year, Nitrogen's ESXi ransomware victims hit a similar wall after a coding error in the decryptor left some unable to fully restore access, and it was far from an isolated case. Attackers don't need to hold up their end of the bargain to keep the payments coming. The better answer is to build cyber-resilience into the organization itself. A word on AI No 2026 security report is complete without AI. In the UK, 65 percent of surveyed security practitioners said AI had sharpened the attacks that precede ransomware and extortion, most notably malicious links, business email compromise, malicious attachments, and credential harvesting. AI is not yet a key tool in ransomware payloads themselves, despite recent reports suggesting this may soon change. However, it is being used for more convincing phishing lures, sharper impersonation attempts, and faster system reconnaissance once attackers are inside a network. "AI hasn't fundamentally changed ransomware, but it has materially improved the attacks that lead to it," said Ryan Kalember, chief strategy officer at Proofpoint. "Today's attackers are using AI to create highly convincing phishing emails and credential theft campaigns that exploit human trust at scale. "Organizations that continue treating ransomware as an endpoint or recovery problem are missing where these attacks most frequently begin: people, identities and trusted communications." ®

A council worker who "abused" his position to unlawfully access "highly sensitive" personal records of family members and other people known to him has received a suspended sentence after admitting to violating the Computer Misuse Act (CMA). Geoffrey Smith, 31, from Ledbury, was a new Herefordshire Council employee working in the Children and Young People directorate. Over a four-day period, he accessed roughly 490 records and downloaded 94 documents relating to family members and "families known to him." This included data on adults and children, the Information Commissioner's Office (ICO) said. The data accessed included "highly sensitive material" such as medical records, social worker reports, and child and family assessments, the watchdog said. Smith pleaded guilty to an offence under Section 1 of the CMA 1990 relating to "unlawful accessing of personal data held on computers." He was sentenced at Worcester Magistrates' Court on July 17 to two months' imprisonment, suspended for 12 months. Smith was also ordered to complete 120 hours of unpaid work and pay £2,000 in costs plus a £154 victim surcharge. Andy Curry, ICO head of investigations, said: "Smith abused his position as an employee and used his access to Herefordshire Council's systems to view the personal information of people known to him, without any legitimate reason to do so. "The sensitive nature of the records held within a Children and Young People directorate, and Smith's systematic misuse of that information, makes this particularly serious. People have a right to expect that their personal information is kept safe, and that those with access to it will only use it for the purposes for which it was intended." Tough words from the ICO, whose former information commissioner resigned after admitting that his conduct had fallen below the standards expected of public officials. ®

OpenAI has admitted that it was the operator of the autonomous agents that attacked model-mart Hugging Face last week, and that they did so after a research project escaped a sandbox by finding and exploiting a zero-day flaw, then used another zero-day flaw to launch an attack. The attack saw agents achieve “unauthorized access to a limited set of internal datasets and to several credentials” used by Hugging Face, which said its infosec teams observed an autonomous agent framework “executing many thousands of individual actions across a swarm of short-lived sandboxes, with self-migrating command-and-control staged on public services.” “This matches the ‘agentic attacker’ scenario the industry has been forecasting.” On Tuesday, OpenAI admitted it was the attacker and that its models went rogue. “This incident occurred during an internal evaluation which prompts models to pursue advanced exploitation using complex attack paths, in an effort to quantify their cyber capabilities,” the startup confessed. The models that conducted the attack included GPT‑5.6 Sol and what OpenAI described as “an even more capable pre-release model” that like the other involved used “reduced cyber refusals for evaluation purposes.” OpenAI thought its models were “hyperfocused on finding a solution for ExploitGym” – a benchmark that measures how effective AIs are at finding security exploits. OpenAI says it runs these tests “in a highly isolated environment, with network access constrained to the ability to install packages through an internally hosted third-party software that acts as a proxy and cache for package registries.” The company’s models decided not to be bound by those constraints. “The models identified and exploited a zero-day vulnerability in the package registry cache proxy. With this access, our models performed a series of privilege escalation and lateral movement actions in our research testing environment until the models reached a node with Internet access,” OpenAI admitted. “After gaining Internet access, the models inferred that Hugging Face potentially hosted models, datasets and solutions for ExploitGym. Knowing this, the model searched for and successfully found ways to gain access to secret information that it could use to cheat the evaluation,” OpenAI explained. “In one example, the model chained together multiple attack vectors, including using stolen credentials and zero-day vulnerabilities to find a remote code execution path on the Hugging Face servers.” Hugging Face’s assessment of the incident was that it represented the moment at which “Autonomous, AI-driven offensive tooling is no longer theoretical.” OpenAI reached a similar conclusion. “The incident also makes clear that advanced models can discover and exploit novel attack paths in real-world systems without source-code access. It highlights that advanced cyber capabilities must be developed alongside stronger safeguards and defensive tools,” the company wrote, without a trace or hint of contrition about the fact its own safeguards didn’t work. Which rather begs the question: If one of the prime movers of the AI boom can’t get this stuff right, what chance do the rest of us have? OpenAI has done the usual Big Tech thing of apologizing for the mess, and promising that its new guardrails and industry collaborations will hopefully prevent this sort of thing from happening again. History suggests those are very hollow sentiments. ®

Who needs expensive frontier models to find software vulns? Cisco has just released two open-weight models that specialize in finding known bugs in existing codebases. The models, Antares-350M and Antares-1B, are part of Cisco’s new Antares family of security small language models (SLMs), and are now available on Hugging Face - but only to vetted users. “We’re making sure we’re gating that and appropriately granting access,” DJ Sampath, Cisco's senior vice president and general manager of AI software and platform, told The Register. The company is working with academic and nonprofit organizations, as well as smaller and public organizations’ security teams, to ensure they have access to the vulnerability-hunting models. Plus, because both are small models designed to run locally, “you also need the keys to the source code” to scan for and find vulnerabilities, Sampath said. “This means an attacker is going to be able to exploit an endpoint or a service that you have.” It also means that proprietary code never leaves the organization’s machines, compared to cloud-based LLMs that send code to the AI providers’ external servers for processing and analysis. This enables security analysis in environments with strict privacy or compliance requirements, according to the networking and security giant. And yes, it's named after the massive red super-giant star. “It's almost 1,000 times bigger than the sun, even though the sun dominates the sky, and that is the analogy that we're using here for vulnerability detection and localization,” Cisco VP and chief AI scientist Amin Karbasi told The Register. “The impact of vulnerabilities in your codebase is huge, but it might be only a single file or a few lines of code in a million lines of code.” A future, 3-billion-parameter model in the Antares family won’t be released to the public, Karbasi added. “We are completely gating the 3B model to make sure that we responsibly release it to communities that need it,” he said. Small yet mighty Cisco claims that its models perform as well as or better than dozens of larger models in its new benchmark test that measures how efficiently AI models identify security flaws in codebases. Antares-1B outperforms Google’s Gemini 3 Pro and is comparable to Z.ai's GLM-5.2, we’re told, while the yet-to-be-released Antares-3B does a better job at finding vulnerabilities than GLM-5.2 and OpenAI’s GPT-5.5. Plus, we’re told that the small models scan code much faster and at a fraction of the cost of larger, token-gobbling AI systems. “If you look at the performance, in terms of the time it takes to finish 500 repositories, Antares finishes the entire cohort of repositories in 15 minutes, whereas frontier models take five hours,” Karbasi said, adding that this translates to significantly less cost. “It takes like less than $1 whereas frontier models are above $100 into $150 of cost,” he added. The difference, Karbasi explained, is that Cisco took a “fundamentally different approach” to building Antares. “These models have been trained in a very different way,” he said. “Antares is inherently not a chatbot. It is an investigator. It is a search engine. It has to find a very specific thing that might be a needle in a haystack, and it goes and finds that.” This required training the model on several different ways to search for vulnerabilities “because one way of search may not actually be fruitful, then it has to change its strategy, do it another way, and then do it another way,” Karbasi said. “Because it is very nimble and it’s very small, it can actually do a lot of search at the same time, which is very different from bigger models.” Karbasi likened it to a bicycle on a busy London street: “You can go much faster than the biggest truck.” Or, to use Sampath’s favorite analogy for the benefits of using a small, security-focused model to find bugs in code: “Sometimes you don't need a private jet to go to a corner store, right?”®

AI models will do just about anything to complete the task you ask, including cheating to get there, according to new cybersecurity evaluations from the UK government's AI Security Institute (AISI). The group found that leading models often take shortcuts to achieve a particular result and then misrepresent how they obtained that result. And they won't always admit it when asked. "Every model we have tested for this behaviour attempted to cheat," AISI said in a blog post on Tuesday. "Models did not reliably report this behaviour when asked, and often did not reason about it in their chain-of-thought, suggesting that detecting cheating will likely require robust monitoring methods." Infractions included searching the internet for the answer, bypassing sandbox network restrictions, probing the evaluation harness, attacking a system other than the target, and guessing an answer. Cheating in this manner – employing a workaround or gaming a reward function to score better on a benchmark test, for example – has been widely documented by machine learning researchers. It doesn't necessarily imply malicious intent, AISI said, but it's nonetheless troublesome because it can produce misleading assessments of model capabilities. When AISI conducted evaluated five leading models, it found that all of them cheated. The results were as follows: GPT-5.4 cheated 67 times in 475 test runs (14.1 percent). GPT-5.5 cheated 54 times in 475 test runs (11.4 percent). GPT-5.6-Sol cheated 60 times in 475 test runs (12.6 percent). Claude 4.7 Opus cheated 43 times in 475 test runs (9.1 percent). Claude Mythos Preview cheated 37 times in 475 test runs (7.8 percent). Asking models whether they cheated or did anything wrong proved an unreliable auditing mechanism because the models didn't always admit wrongdoing. "In our experiments, models did not consistently acknowledge attempted cheating when asked, and described it as wrong less than 50 percent of the time," said AISI. Existing vetting methods, such as self-reporting and chain-of-thought logs, proved similarly dicey because models don't always report their chain-of-thought. And there were instances where a model would consider whether a proposed action amounted to cheating and then decided to take the action anyway. Given the absence of reliable model cheating detection methods, AISI warns that its current approach – manual review coupled with LLM monitoring – may not be sufficient to catch deception, particularly as models become more sophisticated. "A more fundamental fix would be to train the models not to cheat in the first place – but given this kind of behaviour was reported in frontier models more than a year ago, robustly aligning it away may not be easy," AISI concludes. ®

German authorities say they have neutralized the main infrastructure supporting the Kratos phishing-as-a-service (PhaaS) kit following an operation supported by the US and Indonesia. Officers from Frankfurt am Main's Central Office for Combating Internet Crime (ZIT) and the Federal Criminal Police (BKA) described Kratos as one of the most widespread and dangerous PhaaS kits on the market. In Indonesia, authorities said they arrested the Kratos kit's alleged "developer and technical administrator." The announcement of Kratos's takedown did not mention whether any other individuals are being pursued. According to the ZIT and BKA, Kratos allowed low-skill cybercrims to harvest credentials, including passwords and session cookies, to bypass MFA by providing them with convincing Microsoft-themed phishing pages. Criminals using Kratos phishing pages targeted hundreds of thousands of victims across more than 30 countries, while the operation behind the kit allegedly earned more than €300,000 ($342,000) since 2024. More than 1,800 criminal enterprises are estimated to have used Kratos, which was responsible for around 15,000 phishing campaigns per month. "Each individual campaign had the potential to harm several thousand recipients worldwide," the German authorities said in a statement. The operation neutralized more than 200 servers, according to the ZIT and BKA, although the latter declined to explain how. Methods used in previous takedowns included handing legal warrants to infrastructure providers, such as Kratos's chosen hosting company, and working with ISPs to null-route or sinkhole traffic associated with suspect IP addresses. Dr Benjamin Krause, head of the ZIT at the Frankfurt am Main Public Prosecutor's Office, said, "Our approach of disruptive law enforcement works: In addition to the primary task of identifying and prosecuting the accused, we have once again succeeded in dismantling a criminal online service and thus contributing to greater cybersecurity." Carsten Meywirth, head of the cybercrime department at the BKA, added: "Anyone who steals login credentials online using fake websites shouldn't feel safe. The success against the Kratos phishing kit shows that even highly professional phishing infrastructures can be effectively combated. "This is pioneering work and a clear signal to other cyber actors – phishing will not go unpunished and will be consistently fought by the BKA." Many names, same focus German authorities referred to the PhaaS kit only as Kratos, although open source reporting has tied it to products previously sold under names such as SneakyLog and Sneaky 2FA. Similarly, the ZIT and BKA mentioned only fake Microsoft authentication pages among the templates offered by Kratos. Microsoft, meanwhile, reported earlier this year that SneakyLog had been used to generate phishing campaigns targeting US citizens with fake W-2 tax forms. As recently as July 16, security shops such as Heal Security reported that Kratos offered customers lures themed around various websites, including SharePoint, OneDrive, Microsoft Forms, Canva, Tilda, and more. KnowBe4 added Adobe lures to that list with its own investigation in February, which also raised uncertainty about when the kit first hit the market. Microsoft, which said Kratos was also known as SneakyLog, believes the latter entered the phishing kit market as of early 2025, although KnowBe4 said the first signs of Kratos only emerged in January 2026. Muddying the picture further, KnowBe4 did not mention SneakyLog or Sneaky 2FA as part of Kratos's past. The security shop said instead that it evolved from a previous life as a family of commercial trojans and infostealers. One thing that most open source reports agree on, however, is that the targets of the phishing kit's customers are based primarily in the US and Europe. Microsoft identified manufacturing, retail, and healthcare as the main target industries in the US, while in Europe, industrial organizations, law firms, polytechnic institutions, schools, SMBs, and others have all been attacked, according to ANY.RUN. ®

A data breach at AI music generator platform Suno exposed more than 55 million user accounts, according to Troy Hunt's Have I Been Pwned service, which ingested the files. The dump consisted mostly of email addresses, although phone numbers were also included where users had signed up with them instead, HIBP said. Tens of thousands of Stripe records further revealed data such as names, physical addresses, purchase amounts, as well as partial credit card data, such as card type, expiry date, and the last four digits of the card number. The breakdown from Have I Been Pwned puts a figure on the scale of Suno's data breach for the first time since the news of the slip-up broke last week. The individual who claimed responsibility for breaching Suno also supplied source code apparently dating from 2023 and 2024 that they said showed the company scraping millions of songs and lyrics from services including YouTube Music, Deezer, and Genius to train its AI. Suno has acknowledged training its AI on music available on the open internet, while arguing that doing so constitutes fair use. It did not immediately respond to The Register's request for comment. AI's imposition on the arts has been a persistent topic of ethical and moral debate for years. Major record labels came together to complain about mass data scraping and copyright infringement by AI companies prior to Suno's breach in November 2025. Record labels represented by the Recording Industry Association of America (RIAA) sued Suno and rival Udio in 2024 for allegedly scraping songs en masse without permission of the copyright holders. Among the plaintiffs in the case were Sony Music Entertainment, UMG Recordings, and Warner Records, which represent artists such as Bruce Springsteen, Beyoncé, Taylor Swift, and Dua Lipa. Warner has since settled its litigation with Suno and begun a commercial partnership with the AI company, while Sony and UMG are continuing their claims in court. ®

Fortinet on Tuesday revealed it will use Intel Foundry to fab its sixth-gen Security Processor (SP6), a nice win for Chipzilla's sputtering chipmaking biz. The chips feature dedicated accelerators designed specifically for the security and cryptographic operations required by modern hardware firewalls. The custom chips are one of Fortinet's defining features. Many cybersecurity hardware players build appliances around commodity hardware like x86 and Arm CPUs, but Fortinet prefers custom application-specific integrated circuits (ASICs). The two companies haven't said when the chips will enter production, much less what the SP6's speeds and feeds will entail, though we imagine it'll have a bit more pep than Fortinet's SP5 chips. The SP5 launched in 2023 and boasted support for layer 7 firewalling and IPsec VPN connectivity at speeds exceeding 30 Gbps. Throughput fell when advanced threat protection or SSL inspection was enabled, but Fortinet still claimed a speedy 4.3 Gbps and 3.3 Gbps, respectively. As you might have already figured out, Fortinet's SP line is designed primarily for smaller appliances like SD-WAN gateways, rather than larger datacenter-centric appliances built around its beefier NP and CP-series parts. While Intel couldn't offer much detail on the chip itself, we're told it will use the older Intel 4 process node rather than the leading-edge 18A process tech. Chipzilla also suggested Fortinet will draw on its experience in disaggregated semiconductor design and advanced packaging, which could mean a chiplet architecture with greater scalability. With so little detail, we can only speculate. Intel declined to say which technologies beyond Intel 4 the chip will use. The x86 giant also declined to comment on the availability of the product, noting only that "details regarding the Fortinet Security Processor 6 availability will be announced at a later date." While SP6 won't use the latest chipmaking tech, it will be built in an American fab by an American company, offering a level of supply chain security that remains difficult to find. If you want even remotely leading-edge silicon, Intel, Samsung, and TSMC are your only options. US-based production can still mean settling for a less advanced process, although TSMC's first Arizona fab has already begun churning out 4 nm silicon and Samsung aims to bring its new Texas plant online this year. Fortinet would not be the first to enlist Intel's manufacturing might for sensitive workloads. Under DARPA's HIVE program, the chipmaker built an eight-core, 528-thread processor with 1 TB/s silicon-photonics interconnects specifically to accelerate graph analytics workloads. But it doesn't stop at the DoD. Supply chain security is something Intel has leaned into as it has sought to reinvent itself from an integrated device manufacturer serving mainly itself, and occasionally the US government, into a full-fledged foundry ready to compete with Samsung and, ultimately, TSMC. In mid-2024, Uncle Sam awarded Intel $3 billion to establish a secure enclave for manufacturing chips for government agencies. Since then, the US government has taken a 9.9 percent stake in the American chip biz. ®

French cloud operator OVH has revealed it used its Sydney, Australia, datacenter as the crash test dummy to test a rapid rollout of a fix for the critical Januscape guest-host escape bug in the Linux kernel-based virtual machine (KVM). Januscape, aka CVE-2026-53359, allowed attackers with root access to a guest VM to execute code as root on the host, crash that machine, or take over all other guest VMs. A widespread guest-host escape exploitation is a nightmare scenario, because many major clouds use KVM to slice their servers into virtual machines and then rent those guests to clients. The prospect of attackers accessing one tenant’s VM and using it to crash other guests or an entire host is therefore a terrifying violation of cloud operators’ promise to run customer workloads in splendid isolation. Fixing it was therefore a priority. On Monday, French cloud OVH’s CISO Julien Levrard revealed how the company handled the emergency patch job on tens of thousands of hosts that run approximately a million virtual machines, in a lengthy post that offers an unusually detailed and candid account of how clouds cope with major security incidents. One way to mitigate the bug was to disable nested virtualization by creating a two-line config file on each host running Linux KVM. That wasn’t an option because OVH has no way to see if its tenants need nested virtualization and relies on it to shift VMs to different physical hosts. Nor was applying a live patch palatable, as it could introduce instability. Live migration to patched hosts was another option, but one OVH rejected as the process is slow and the company felt it might take months to move its entire fleet of tenant VMs to a Januscape-free environment. The company therefore decided to backport a Januscape fix into the Debian distribution it uses in production and reboot all hosts, giving customers advance notice but no choice. That meant customers who rely on a single host would experience some downtime, but OVH’s executive committee signed off on this approach for three reasons: The need to patch before attacks; Treating cases individually would mean the OVH cloud would be vulnerable for longer; A desire to protect the greatest number of customers, and tolerate impact on a minority. OVH also decided to stay quiet about the patching plan. “Communicating in more detail during the execution of the mitigation plan, while the infrastructure remained unpatched, would have significantly increased the risk for our customers, potentially leading some to ‘test’ the publicly available exploit,” Levrard wrote. Danger down under To test its patching prowess approach, OVH decided to first fix its Sydney region – one of the company’s smaller regions and one which, thanks to Australia’s east coast being eight hours ahead of France, teams in Europe do the job during their business hours – but at a slow time in Sydney. The company therefore planned to go down under and learn from the experience before deploying the fix more widely. OVH’s plan called for reboots to occur in waves, with a “shutdown threshold” imposed if 15 hosts failed simultaneously in high-density regions, or five boxes in other regions. But those waves weren’t as simple as just going rack by rack. “The main risk for our clients during such an operation is not the reboot itself, but the simultaneous interruption of multiple instances of the same project, ensuring application resilience capable of handling a provider failure,” OVH’s blog on the project explains. “A client who has distributed their workloads across multiple hosts to ensure high availability should not see all of their instances fail over at the same time. The decision was made to go beyond simply adhering to the anti-affinity rules that may have been defined in client deployments.” “Thus, for each client project with instances distributed across multiple hosts, our orchestrators calculate a co-location graph. At no time are two hosts running instances of the same project rebooted in the same window: mutually exclusive waves are defined, and a host must be back online before the next one is launched in the same anti-affinity class.” The patching effort hit a few snags. Some VMs didn’t restart after hypervisor reboot. Some experienced data corruption during forced shutdowns. OpenStack APIs misbehaved, producing hours of HTTP 503 errors and necessitating postponement of one patching wave. At a Canadian site, “API traffic reached 10 times the usual peak, overwhelming the manager and support teams.” Hardware hiccups Some hardware died during the process. “On the first night, approximately 20 to 30 hosts out of 6,000 did not recover on their own,” Levrard revealed, blaming “faulty memory modules, BIOS configuration issues, inactive network interfaces.” Some machines needed new CMOS batteries. The CISO thinks OVH’s approach was “a remarkable feat” as it produced “a very reasonable number of outages and customer impact relative to the scale of the project.” But he thinks the company will need to improve. “Recognizing that the coming months could see further kernel vulnerability disclosures, it seems clear that this emergency procedure will need to be repeated,” he wrote. “We will need to do better next time, both in managing the raw impact of the restarts and in providing customers with advance notice and support during the operations.” The company is therefore conducting a post-mortem analysis it hopes will improve its processes. ®