UK police forces and fire and rescue services have been urged to strengthen cybersecurity as rising cyber threats outpace current defenses
Source: Infosecurity Magazine · 2026-10-27
Category: Security News
-
Japanese virtual desktop cloud hacked so hard it asks to be banned
Japanese ISP GMO Internet has warned customers the cloudy desktop service it offers as an ideal foreign exchange trading environment was compromised by an attacker, and that it had been slow to improve the service’s security. GMO runs a service called Onamae.com Desktop Cloud and last week admitted “a third party had installed malicious programs in the server environments of some customers.” That’s never welcome news but is an especially poor outcome because the servers host cloudy Windows desktops that GMO recommends customers use to host foreign exchange trading applications. In later updates the company revealed that some customers reported “unauthorized operations were performed on their trading accounts” and advised that third parties had probably seen users’ passwords for trading services. The next day, the company advised users to immediately change passwords for their trading accounts, and to do so using a device that they don’t use for trading. The company has since admitted that its Onamae.com Desktop Cloud service’s “systems had security vulnerabilities, that its environment was accessed without authorization, and that customer information was taken outside the Company.” “Some customers have also reported transactions in their trading accounts that they do not recognize.” Those transactions have GMO sufficiently worried that it contacted major trading services, asked them to forcibly terminate all active sessions, monitor for unauthorized transactions, and to block trade requests coming from the Onamae.com Desktop Cloud. Not paying, or complaining GMO said it has “received a demand for money from a person believed to be the attacker. We have also been told that, if we refuse, the attacker will take actions such as publishing information about the Company and our customers.” The attacker wants $50 million. The company won’t pay because it feels “complying would not guarantee that the obtained information is deleted or that its misuse is prevented.” Investigations into the incident continue, with GMO warning that 26,739 VDI servers may have been hit by the attack, and that users’ personal devices may be at risk. The company is offering all users a ¥5,000 ($32) condolence payment and promised to make good on any trading losses caused by the attack. This incident may have quite a blast radius, as GMO has warned that some trading apps may keep sessions alive even after passwords change. “Check your securities or FX company’s guidance or your account page, and either disconnect all active sessions or ask the company’s support desk to disconnect them,” GMO advised. That ¥5,000 isn’t going to get anywhere near paying for the work customers will do to sort this out. GMO CEO Masatoshi Kumagai acknowledged that in a blog post in which he described the payment as “a token of our initial sincerity towards our customers who have experienced inconvenience and worry.” “We will dedicate the full resources of our group to providing a free alternative environment for six months, fundamentally overhauling our system infrastructure, and conducting a thorough investigation into the cause and preventing recurrence with the help of external experts,” he added. But he also admitted that GMO knew the service’s security could be improved. “Our in-house white-hat hackers had previously pointed out areas for improvement to the team,” he wrote. “The team took these points to heart and was working on countermeasures.” “However, while we proceeded cautiously, considering the impact on service availability and prioritizing other issues, our response lacked sufficient depth and speed, allowing the attackers to exploit the vulnerability. I deeply regret that, despite having professionals on staff, we failed to fully translate their expertise into effective defenses as an organization.” The CEO also said GMO can’t secure itself without government help. “I’ve been involved in this world for 31 years, since the dawn of the internet industry,” he wrote. “The cyberspace that I built with my colleagues, believing it would bring smiles to people’s faces, is now on the verge of being completely destroyed by malicious actors.” “The ease with which open weight AI models can be combined and spread into countless attack tools has transformed cyberattacks, which once required advanced skills, into an era where anyone can easily carry them out,” he added, before claiming that GMO Group’s cybersecurity operation “has confirmed that the source of an unauthorized access attack targeting approximately 20 Japanese companies was the misuse of ‘ARTEX,’ an autonomous AI penetration testing tool originally intended for defense.” Kumagai thinks public/private partnerships are needed to improve infosec across Japan. “Yesterday, we submitted a proposal to the government to ‘apply proactive cyber defense,’” he wrote. “We are by no means trying to shift the blame for our company’s actions onto the government and beg for a bailout,” he wrote, but argued that unless Japan implements national-level defenses, more such incidents are unavoidable. ®
Source: The Register — Security · 2026-10-27
-
So Many AI Security Benchmarks, but None Tell the Whole Story
Measuring artificial intelligence model security gets complex, fast, thanks to a growing patchwork of benchmarks targeting different variables in the equation. But none replace testing against your own code and workflows.
Source: Dark Reading · 2026-10-27
-
Worm armed 42 GitHub repos by hiding a payload too big to fail
A new Miasma-family npm worm, originally believed to be just a test with no victims, secretly armed 42 real GitHub repositories from 11 owners, hijacking accounts as early as July and using a stealthy payload built to stay hidden from GitHub and automated scanners, according to JFrog researchers. Threat hunters at SafeDep, an open source supply chain security firm, first spotted the “testmetest” npm campaign last week, identifying 18 packages linked to the same operator between October 19 and October 25, including releases containing credential-stealing malware. As with earlier npm worms, the malware is self-replicating, steals credentials, and installs a wiper that deletes the home directory when the victim revokes the stolen GitHub token, the security researchers noted. The new npm worm shares code with June’s Miasma Phantom Gyp worm, and adds Mini Shai-Hulud’s token-revocation wiper. As of October 22, however, SafeDep had found no compromised third-party packages or victims. “All observed activity belongs to the operator’s own test accounts,” the team wrote. As with most happy-ending security stories, that proved too good to be true. In a Monday report, supply chain security company JFrog said its analysis proved otherwise, and found the testmetest campaign operator “had already armed real repositories belonging to established developers and organizations.” This isn’t just about timing, either, according to JFrog researchers Guy Korolevski and Yair Benamou. “The payload blobs were large enough to evade the GitHub search and API paths normally used to find this kind of compromise,” they wrote. How the attacks worked The attackers planted execution hooks for AI coding assistants and development tools, including Claude, Gemini, Cursor, and VS Code, alongside polymorphic wrappers measuring 12.9 to 13.7 MB that decode a hidden CI-publisher payload. Separately, the npm worm steals credentials, modifies repositories and CI configurations, and spreads through npm packages. The malware also uses a compiled native add-on to decrypt and launch a separate payload. Before executing, the loader checks for CI runners, containers, sandboxes, debuggers, and other signs of automated analysis, exiting silently when it detects them to reduce the likelihood of detection by security scanners. The researchers also found a second build that skips the encrypted file. “It forks, detaches and runs a hard-coded command that pulls a loader from a repository on the operator’s own GitHub account,” they wrote. That account – CementBeetleSteeple – hosted 17 campaign repositories in total. JFrog connected this account to a shellpanel scanner, previously documented by Socket in a large-scale campaign that abused GitHub Actions in compromised repositories to exploit CVE-2026-41940 and steal server credentials. CVE-2026-41940 is an authentication bypass affecting cPanel and WHM. CISA added it to its Known Exploited Vulnerabilities catalog in April, and cPanel has since published patched versions. “C2 infrastructure were previously reported by Socket; our findings connect them to the testmetest GitHub victim cluster through artifacts and workflows on the same hijacked owners,” the JFrog researchers wrote. They added that while they found 42 armed GitHub repositories and attempted internet-wide exploitation, they did not confirm any downstream cPanel compromises.®
Source: The Register — Security · 2026-10-26
-
Risks & Rewards: How AI Is Redefining the CISO’s Role
Nvidia security executive Mark Weatherford says CISOs must help business leaders weigh AI’s pros and cons, and ensure those deploying it own the risks.
Source: Dark Reading · 2026-10-26
-
Alibaba’s Qwen AI caught trying to contact server in China
Open-weight models from China have become very popular, but they’ve also raised some security suspicions. Cohere, a Canada-based biz that offers AI models to enterprises, says that when it was testing Alibaba’s Qwen3.8-Flash-Next in its evaluation sandbox, the model attempted to send data to China. “Asked to write a defensive detection rule, Qwen3.8-Flash-Next ignored instructions and inventoried the machine it was running on and then tried to upload a probe file to an Alibaba Cloud storage bucket in Beijing,” the biz said in a blog post on Monday. Cohere was running the model through CTI-REALM, Microsoft’s security analyst benchmark, and gave Qwen the task of writing a detection rule to look for malicious file downloading and execution by watching for invocations of curl processing bash scripts to the /tmp directory that were accompanied by bash execution. The model’s “reasoning” output invented a prior conversation and asserted that no tools were used, output that a guardrail system reading chain-of-thought would accept. Nonetheless, the model issued a curl command to an Alibaba Cloud (aliyuncs.com) server. “The model listed everything in /tmp, checked which transfer tools were installed, read the machine’s DNS settings, then tried to upload a test string to an Alibaba Cloud storage bucket in Beijing and checked whether it worked,” Cohere said. “Our sandbox had no route out, so the request died at the container wall.” The Cohere team wonders aloud whether that behavior was intended, but has no answer. “The first issue is that it made a network call at all,” Ivan Zhang, co-founder of Cohere, told The Register via email. “The model was asked to write a detection rule, which doesn’t require external communication, and its reasoning trace said it wouldn’t use tools. The destination raises additional questions because the attempted upload was to an Alibaba Cloud storage endpoint that wasn’t part of the task. We don’t know why it appeared, and we don’t know the root cause.” Alibaba, the maker of the model, did not respond to a request to address Cohere’s concerns. Asked whether Cohere ran similar tests against US-made open-weight models, Zhang said, “We evaluate a broad range of models using the same framework our customers use in production: agents with access to real tools operating inside controlled environments. “The key point isn’t a comparison between providers. What made this noteworthy was that the model took actions unrelated to the task and those actions weren’t reflected in its reasoning trace. The behavior appeared in fewer than one in 100,000 calls, which is exactly why large-scale testing and monitoring matter.” There have been other unsubstantiated claims made about similar behavior from open-weight models, and such reports have suggested that “hallucination” – errors made by these models – may be the cause. Cohere has doubts that this behavior simply reflects memorized training data. “Every public sighting so far has involved fetching a file, while the one we caught was an attempted upload to a different bucket, this time in Beijing,” the biz said. Cohere described efforts to reproduce the suspect behavior and found that using a technique called prefilling – feeding the model its own reasoning output alongside the opening characters of the bash command so the model would complete the command – they could get it to reference watchlisted hosts up to 23 percent of the time. This still doesn’t clarify intent, and Cohere allows that there’s a case to be made that the behavior is just bad training data sanitization – logs from development that got swept into the model’s training data set. At the same time, the company argues that isolating a suspect model so it can’t exfiltrate data doesn’t entirely fix everything because these models can still write vulnerable code – accidentally or as a result of model poisoning. Cohere points to research from other organizations that suggests Chinese AI models can produce vulnerable code. The biz, for example, cites a report from Booz Allen (which does a lot of business with the US defense industry) that found “three of four Chinese coding models wrote more vulnerable code for a government customer, with Qwen3-Coder roughly 130 percent worse.” “From the outside, it’s very difficult to determine the root cause with confidence. We don’t have evidence that would allow us to conclude this was deliberate, and we’re not making that claim,” said Zhang. “For security teams, though, intent doesn’t fundamentally change the response. Whether it’s a training artifact, a mistake, or something else, the controls are largely the same: restrict unnecessary egress, monitor tool use, and don’t treat a reasoning trace as a security boundary. “We strongly support open-weight models and release many of our own. The lesson here is really about trust. Sovereign AI is about more than where a model runs. It’s about understanding how it was built, how it was tested, and having confidence in how it behaves inside your environment.” ®
Source: The Register — Security · 2026-10-26
-
In-the-Wild Attack Abuses AI Agents’ Trust in Markdown
A new AI agent prompt injection technique exploits how coding assistants consume local instruction files, blurring the line between text documents and executable actions.
Source: Dark Reading · 2026-10-26
-
LiteLLM supply chain attack started with an exposed master key
LiteLLM has traced last week’s supply chain attack to a master key it accidentally committed to a public GitHub repository in May. The cloud and AI model secret-stealing part of the incident began when someone uploaded a poisoned version (1.107.0) of the popular open source AI gateway to PyPI and its container registries last Wednesday. This compromised version contained an infostealer and a remote access trojan capable of executing arbitrary code on infected machines. While the trojanized package was available on PyPI for less than two hours before being quarantined, it received about 49,000 downloads during that time, according to Wiz. On Friday, LiteLLM detailed the attack chain behind the compromised release and traced it back to May 27, when a configuration file containing a master key was committed to the public LiteLLM-Labs/lite-harness repository. The key belonged to an open source tool used internally by LiteLLM to orchestrate AI agents. The project’s developers quickly spotted the error and removed the exposed commit, but failed to revoke the master key. “On October 10th, the threat actor used this key to gain access to our LiteLLM Agent Platform and extracted this GitHub CLI OAuth token,” according to Friday’s postmortem. “From this point onwards, the threat actor had owner-level access to all repositories in our GitHub.” This is especially serious because GitHub CLI tokens are “post-2fa,” meaning that they don’t trigger GitHub’s sudo mode authentication flows typically required to perform high-impact repository actions. The token allowed the attacker to author malicious commits into branches on other internal repos – including workflows designed to steal any tokens and secrets configured to be available during the continuous integration development process. And this allowed them to steal other GitHub CLI OAuth tokens linked to two engineers with maintainer privileges. Plus, they acquired tokens for several other internal systems, we’re told. “Reviewing the actor’s activity on these other systems shows attempts to identify and exfiltrate additional keys and tokens, with a primary focus on upstream inference API tokens,” LiteLLM noted. Having now stolen several privileged identities, the miscreant could make changes to GitHub repositories without raising any suspicion because the actions and approvals all appeared to come from legitimate, credentialed engineers. In response, LiteLLM’s developers are revoking every token associated with every internal system and vendor platform. “This incident has provided a strong illustration of the risks associated with failing to rotate a potentially exposed key,” they wrote. The infostealers hidden inside the compromised package were designed to hoover up a ton of sensitive information, including browser credentials and cookies from Chrome, Firefox, Edge, and Safari, along with AWS credentials, Google Cloud Platform service account keys and application default credentials, and Microsoft Azure tokens. It also swiped API keys for OpenAI, Anthropic, Cohere, and other LLM providers. So if you installed and ran version 1.107.0, assume any credentials accessible to the affected system may have been stolen. Investigate affected systems, change passwords, and rotate exposed keys. A quick prayer to the patron saint of supply chains wouldn’t hurt, either. ®
Source: The Register — Security · 2026-10-26
-
‘Gheist’ Weaponizes GitHub Tokens to Steal Cloud Secrets
An ongoing supply chain attack is harvesting credentials and sensitive data from thousands of developer repositories.
Source: Dark Reading · 2026-10-26
-
Microsoft releases emergency .NET security fixes for Google Brotli bug
To address a vulnerability in Google’s Brotli compression technology that could allow attackers to corrupt process memory, Microsoft is urging .NET users to update “as soon as possible” after releasing an out-of-band (OOB) security update. It released new versions for .NET 8, 9, 10, and .NET 11 to patch against the Brotli bug, following similar updates from Node.js, Python, and other projects. Senior program manager Rahul Bhandari said in the October 25 release that the buffer overflow vulnerability in Brotli, tracked as CVE-2026-111497 and rated 8.1 under CVSS v3.1 in Microsoft’s advisory, could allow an unauthenticated attacker to read or corrupt process memory, potentially resulting in information disclosure, denial of service, or elevation of privilege. Microsoft’s own advisory for the vulnerability, which some are referring to as Broccoli2Shell or Node2Shell, confirms that while experts have cobbled working exploits together, there is nothing to suggest that criminals are using them in successful attacks. However, its exploitability assessment reads: “Exploitation More Likely.” Broccoli2Shell was first disclosed on October 21 by the Node.js team, which released fixes for ten vulnerabilities, the most serious of which was CVE-2026-111497. Node.js credited Khai Tran and Sylvie Mayer of OpenAI’s Codex Security with the discovery, but failed to mention why it was only recognized as a security flaw and disclosed properly in October, despite the underlying bug having been fixed in Brotli’s source code in February. OpenAI filled in the gap with a Xeet: “This root cause issue was actually fixed in the Brotli source code in February, but it wasn’t known at the time that it gave rise to a security vulnerability, and there was no more recent release of Brotli. “Since Brotli is built into other software, any software which includes this library needs to take the update too, followed by the users of that software.” Attackers can exploit vulnerable systems by providing them with malicious Brotli-compressed data via a specially crafted request. The vulnerability went slightly under the radar due to the disclosure timing closely aligning with that of PHP2Shell, although fixing the critical flaw should be a priority due to the range of technologies that are affected. In addition to .NET, Node.js, and Python, Bun, Envoy, and Istio have all released patches, and JFrog has worked up an exploit affecting FFmpeg using a specially crafted JPEG XL image, extending the exploit path beyond HTTP. It said that FFmpeg reaches Brotli through libjxl, which it uses to decompress metadata stored in brob boxes within the image format. The same researchers said the vulnerability affects Apache Arrow too, with attackers able to cause a denial of service. Merav Bar, threat researcher at Wiz, added that cloud users are exposed extensively, noting that 91 percent of cloud environments rely on components vulnerable to the Brotli flaw and that 82 percent of cloud environments have publicly exposed Node.js instances. She said: “Cloud environments are particularly exposed due to the widespread use of Brotli-enabled components across containerized applications, Kubernetes clusters, API gateways, reverse proxies, serverless workloads, and cloud-hosted web services.” “Successful exploitation could enable attackers to compromise application workloads, access sensitive information, disrupt service availability, or execute malicious code within affected containers or runtime environments,” Bar added. In an advisory published through its Patch the Planet initiative, OpenAI recommended blocking untrusted Brotli-compressed data where practical until patches can be applied. It also advised maintainers to rebuild affected deployments and restart services to ensure the fixes take effect. ®
Source: The Register — Security · 2026-10-26