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A critical flaw in GitLab's AI Gateway could let a logged-in user with Duo Agent Platform access run commands on the gateway under certain conditions, GitLab  said in an advisory . The gateway is the service that connects a GitLab instance to AI models, and only organizations that host their own gateway need to act. The flaw is fixed in gateway versions 19.2.4, 19.3.2, and 19.4.1. The flaw is tracked as  CVE-2026-90970 . GitLab disclosed it on October 2 and rated it critical, with a CVSS score of 9.9 out of 10. GitLab runs AI Gateways for its customers and has already fixed them. Customers on GitLab.com, GitLab Dedicated, and self-managed instances that use a GitLab-hosted gateway do not need to act, the company said. Self-managed customers can instead  host their own gateway , an option GitLab offers for keeping AI request and response data inside the customer's own environment. GitLab strongly recommends that those customers update immediately. It sent that gui...

OpenAI has parted ways with three members of its safety team after they leaked private information in violation of company policies, The Wall Street Journal reported . "We have parted ways with three individuals for violating our policies on accessing and handling sensitive company information," a spokesperson for the company was quoted as saying. "Our investigation confirmed that these individuals mishandled sensitive information outside established company procedures, violating our policies and breaking the trust essential to our work." The impacted employees are Jasmine Wang , Tomek Korbak , and Mikita Balesni , the Journal reported, citing people familiar with the matter. The three researchers have all previously expressed concerns about the pace of artificial intelligence (AI) development. It's said that the individuals shared confidential information with a third-party AI-safety organization. The name of the organization was not disclosed. According...

The quarterly board meeting is two weeks out. The security team is pulling exports from the identity provider, the cloud posture tool, the vulnerability scanner, the SIEM and the EDR console. Someone is building a spreadsheet to reconcile them. Someone else is turning that spreadsheet into slides. Then a board member asks three questions: How secure is the organization, overall? What is the actual financial exposure? Is the security posture better than it was last quarter? Most security leaders cannot answer any of them with confidence. Not because the data doesn't exist, but because it lives in a dozen tools that don't share context. A new guide to confident board reporting for CISOs takes on exactly this problem. This article walks through why traditional reporting fails and what a better model looks like. Boards Have Stopped Trusting Activity Metrics For years, security reporting has run on counts. Vulnerabilities found. Patches applied. Alerts closed. P...

This week, the useful words are boring ones: inspect, cache, compile, store, trust. Each sounds harmless. Each can become an attack path when a system does a little more than people expect. A model check can run code. A cache can mix up requests. A public secret can stay useful for years. That is the lesson running through the list. Attackers do not always need a brilliant new trick. They can hide commands in public infrastructure, reuse old flaws, abuse weak defaults, or let automation stitch together a rough path that still works. Faster tools are changing the pace, but basic mistakes are still doing plenty of the work. So the interesting question this week is not “what broke?” It is “what did we assume was safe because it looked ordinary?” The full list has answers. The threats change every week. Subscribe, and we’ll alert you when each new ThreatsDay Bulletin is out.

Every security leader at a bank, insurer, or asset manager has had a version of this conversation: Security wants to eliminate a class of vulnerabilities. Engineering explains what it would take to upgrade the platform where they live. Somebody prices out the regression testing. Somebody else raises the change-freeze calendar. The finding gets an exception, a compensating control, and a date eighteen months out on the roadmap to address it. Nobody in that conversation is being unreasonable. Financial services carry more legacy software than almost any other industry for a few reasons: decades of accumulated infrastructure, regulatory obligations that reward stability, and applications where an hour of downtime is unacceptable. In that environment, minimizing change is risk management. Every dependency bump, every base image swap, every migration is a chance to break something that clears trades or moves money. So the instinct to stick to the status quo has been sound. The problem...

OpenAI on Wednesday said it identified and disrupted a coordinated distillation campaign that was designed to illicitly extract protected reasoning from its artificial intelligence (AI) models. A "core cluster of the activity," going back to the first week of July, has been attributed to individuals associated with Moonshot AI, a Chinese AI company based in Beijing. It did not cite any technical evidence to back this assessment, likely owing to security reasons. "The operators did not break our encryption, compromise a database, or gain direct access to stored user conversations," OpenAI said . "Instead, they manipulated model interactions so that protected reasoning could be reproduced in forms visible to the requester in a coordinated, scaled manner that violated our terms of service." The activity is said to have begun on July 1, 2026, initially at a low volume before it spiked on July 24 and 25, 2026, to 16,000 attempted requests using a relevan...

Google on Wednesday announced its latest frontier artificial intelligence (AI) model, Gemini 4 Argon , that it said is being rolled out to a set of trusted cyber defenders through its Fairwind Program. "It delivers frontier performance in complex workflows across real-world software engineering, enterprise knowledge work like legal and finance, and cybersecurity defense," Koray Kavukcuoglu, senior vice president of Google DeepMind and Chief AI Architect at Google, said . The development comes nearly a month after the tech giant unveiled Gemini 3.8 Flash Cyber , which it described as the most capable cybersecurity model. Like similar models from rivals Anthropic and OpenAI, Argon is assessed to be highly capable at autonomously finding, validating, and patching critical software vulnerabilities. This includes a previously unknown critical vulnerability exposing sensitive personal information across healthcare software used by hospitals worldwide. Google did not reveal...

Threat actors are abusing ChatGPT Custom GPTs to disguise them as legitimate product offerings and direct unsuspecting victims to malicious sites that employ ClickFix lures to deliver malware. Huntress, which observed the activity in late September 2026, said it marks the abuse of yet another feature in trusted artificial intelligence (AI) platforms. Prior campaigns have weaponized shared conversations with AI chatbots and malicious Claude Artifacts to distribute stealer malware and remote access trojans (RATs). Custom GPTs refer to a personalized version of ChatGPT that, as the name implies, allows users to define custom instructions, upload reference files, and enable specific skills to handle unique tasks without any coding. They are hosted on the legitimate ChatGPT website with the Custom GPT name at the top. "In the incidents we saw, victims interacted with an attacker-created Custom GPT, which was programmed to respond to their prompts with a message that includ...

AI coding agents asked to share screenshots of code changes for review have put internal company images in public GitHub repositories, security company Glow said. Its researchers found more than 13,000 internal images from developers at over 300 organizations, including customer billing records and screens of features not yet released. In most cases, they sat under developers' personal accounts, where anyone could download them but company security teams did not see them. The affected organizations include one of the world's largest tech companies, a leading AI lab, a major enterprise software provider, and a Fortune 500 travel company. Glow began contacting them on September 9,  published its findings  on September 29, and says others are likely affected too. In one case, a developer at a manufacturer with more than 100,000 employees asked an agent to check a fix to an internal billing screen. The agent created a public repository in the developer's personal GitHub ...

A malicious MCP server could trick an application built on the official  MCP Python SDK  into handing over the OAuth credentials it uses to log in to a real service, the SDK's maintainers said in a security advisory. Affected versions sent the client secret, the authorization code, and the PKCE proof key to a token endpoint the attacker controlled. The fix is in versions 1.30.0 and 2.2.0. The Model Context Protocol (MCP) is an open standard for connecting AI applications to outside tools and data, and this package is its official Python SDK for building MCP servers and clients. With the stolen credentials, the attacker can request a valid access token from the real login service. Cycode, the security firm that reported the flaw , demonstrated that full exchange in a test and says the resulting token carries whatever permissions the app was granted. The client secret is long-lived, so it keeps working until it is changed. The flaw is rated high (7.5) for the two prov...

OpenAI on Monday shelved plans to release GPT-6.1 Astra, a next-generation artificial intelligence (AI) model that was planned for an October launch, after it failed internal safety and alignment audits. The development was first reported by The Wall Street Journal. The move "marks a rare case of a major AI developer ditching a new release because of safety concerns," the news publication said. The ChatGPT maker said it made the decision to scrap its GPT-6.1 Astra model release after testing raised questions about whether it can follow user instructions without deviating from expected behavior. The Journal reported that the model exhibited higher levels of deception than its predecessor during evaluation, and failed to disclose what actions it had carried out. In some cases, it went ahead without seeking permission or attempted to use outside tools in scenarios where doing so could be deemed unsafe. "While (GPT-6.1 Astra) improved on axes such as model laziness...

OpenAI said it has made the decision to pause training of its most powerful models after one of its agents during reinforcement learning (RL) training contacted an external chatbot by exploiting a loophole in its internet-access restrictions. "An agent attempting to complete a search-based training task queried a public chatbot service through a gap in our internet-access restrictions: insufficient DNS filtering in its training sandbox," OpenAI said . "Before this, the agent issued queries via our search tool and unsuccessfully tried to access search engines directly. Note that all internet access apart from the DNS resolver in this report hit our offline webcache and therefore did not access the live internet." OpenAI said it has since added blocking controls at two independent layers to prevent this access in the first place. It also said its misalignment monitoring system detected the behavior within 15 minutes and it was acknowledged by a human reviewer...

What is IAM for AI agents? AI agents authenticate, invoke tools, and act across enterprise systems with delegated authority. IAM for AI Agents is the identity-control architecture that governs those actors. This guide covers the limits of conventional provisioning, the components that matter, how to evaluate framework choices, and what runtime evidence proves an agent behaved as intended. Identity and access management (IAM) for AI agents treats each agent as a non-human identity with a human owner, a defined purpose, scoped authorization, an expiration, and continuous monitoring. The complication is architectural. IAM platforms express intended access, while applications and infrastructure reveal what the agent actually executed. Between the two sits identity dark matter: the agents, credentials, application-local accounts, and authentication paths that central identity data never reports. A framework that cannot observe that surface produces policy intent, not assurance. Wh...

RatHat's operators build and publish the Android banking trojan and control infected phones from a web console, according to security company Cleafy. Cleafy has  traced nearly 100 deployments  of that console since April 2026. It said this fits a malware-as-a-service model, in which each customer runs a separate copy. The console stores what the malware collects from each phone, including text messages and passwords entered into fake login screens overlaid on banking apps. Its latest version asks Google's Gemini AI model to estimate each victim's bank balance from those messages and sorts the phones into high-value and mid-value groups. Nothing in the samples Cleafy analyzed uses the model to move money. Its role is "deciding which victims are worth an operator's time," the company said. One Console, Three Versions The malware on victims' phones has changed little since late 2025, Cleafy said. The console behind it has been replaced. Samples f...

A domain used as harmless placeholder text showed up in roughly 1,700 repositories. Then somebody registered it and started serving malicious lures. That is the kind of week this was: forgotten assumptions turning into live attack surface. Elsewhere, weak service accounts, old bugs, exposed systems, phishing kits, and strangely easy exploit paths kept doing useful work for attackers. Nothing exotic. Mostly things nobody expected to matter anymore. Here’s the full recap of what mattered this week. ⚡ Threat of the Week Citrix Warns of Actively Exploited NetScaler ADC and Gateway Flaws — Citrix released patches to address multiple vulnerabilities, including CVE-2026-88771 and CVE-2026-88772, that have come under active exploitation. CVE-2026-88771 is an improper input validation vulnerability that could allow an unauthenticated attacker to execute arbitrary commands, while successful exploitation of CVE-2026-88772 could allow for remote code execution or denial-of-service. CISA...

AI agents are moving into production faster than security teams can govern them. They are connecting to apps, handling data, calling APIs, and acting across business systems—often without the same controls applied to human users. According to Okta’s Global CISO Insights 2026 report, only 47% of CISOs are confident they can identify every AI agent in their environment. Even among those who feel confident about visibility, roughly 80% still worry that excessive access may be going unreviewed. That is the real problem: seeing an agent is not the same as controlling what it can do. Join Matt Immler , Regional CSO at Okta, for a practical session on how to bring AI agents under stronger identity governance before excessive access becomes harder to contain.

Cybersecurity researchers have disclosed details of a new botnet malware called Carbonato that's targeting exposed Docker daemons to deploy an open-source artificial intelligence (AI) agent framework called Hermes Agent . "The implant installs the framework unchanged, then overwrites its SOUL.md persona file," ThreatDown said . "The 39-line prompt directs it to execute tasks received through Telegram, maintain persistence, and collect credentials." At a high level, the botnet breaks into Docker daemons exposed without authentication on port 2375 and scans neighboring networks every five minutes to propagate further. On each host, it installs Hermes Agent with instructions to follow operators' Telegram commands. The cybersecurity company said it found the operation through an unauthenticated Docker registry that's been publicly accessible since May 2026. The staged data has been found to include details of the botnet and a separate campaign that d...

The way we talk about AI agents is shifting, and the way we implement them requires an even more fundamental shift. While earlier discourse focused on how quickly organizations could stand up agents and how much productivity they could promise, a string of recent incidents, including a widely discussed intrusion at Hugging Face during an evaluation of OpenAI agents, has spurred organizations to examine whether speed has outpaced the ability to secure what gets deployed . Security teams are increasingly asking what an agent can reach once it's running, and whether anyone would notice before it mattered. However tempting it may be to jump directly into enforcement controls and detections, you need to look before you leap. Research from Veeam reveals that 70% of organizations admit that AI workflows are already in contact with sensitive corporate data without full oversight in place, and 67% report that IT cannot fully track the autonomous workflows that employees are building. Sh...

Security leaders keep debating whether AI will produce an entirely new class of cyberattack. The nearer change is quieter and already visible: AI has made a failed attack cheap to retry. The routine version looks like this. An attacker lands on a low-privilege cloud account, and the first try at privilege escalation goes nowhere. That dead end used to cost hours of documentation reading, permission checks, and script debugging, and plenty of operators simply got stuck. With a model in the loop, the error gets explained, the script gets fixed, and a fresh enumeration path is under test within minutes. No step in that sequence is a new capability. Together they strip time, skill, and cost out of the unglamorous middle of an intrusion, the research and troubleshooting that sit between intent and outcome. What the threat reporting shows The public record traces the arc. In early 2025, Google's Threat Intelligence Group found state-backed actors treating generative AI as a prod...

This week, the dangerous stuff keeps arriving dressed as something boring. An update. A login box. A search answer. A coding tool. A link you have clicked a hundred times before. That is the thread running through the pile. Trusted paths get poisoned. Old bugs find new jobs. AI tools leak more than expected. Fake prompts look real enough. And some attacks barely need an exploit at all — just one weak setting or one person doing what the screen tells them. Nothing here looks especially dramatic. That is what makes it useful. The threats change every week. Subscribe, and we’ll alert you when each new ThreatsDay Bulletin is out.