Microsoft has identified seven new failure modes in agentic AI systems, in addition to those it identified last year in its first Taxonomy of Failure Modes in Agentic AI Systems.

Four things contributed to the growing list of ways agentic AI can go wrong: the speed at which the technology went mainstream, the growing maturity of the Model Context Protocol (MCP) ecosystem, the rise of computer-use agents, and finally the gathering of more empirical evidence as researchers obtained more real-life findings.

The seven new failure modes it has identified are:

• Agentic Supply Chain Compromise —agent behavior can be affected by natural language rather than malicious code;
• Goal Hijacking — adversarial instructions appear aligned with legitimate task completion, while silently redirecting the agent’s terminal goal;
• Inter-Agent Trust Escalation —a compromised agent asserts false identity or inflates claimed permissions to an orchestrator;
• Computer Use Agent (CUA) Visual Attack — agents operating through graphical interfaces can be manipulated through content that carries adversarial instructions for the agent;
• Session Context Contamination —an adversary introduces data that biases the agent’s reasoning in subsequent steps, without triggering safety controls at any individual step;
• MCP / Plugin Abuse — an update on the original taxonomy’s coverage of function compromise around MCP and plugin protocols, specifically attack surfaces specific to those protocols;
• Capability / Architecture Disclosure —an agent reveals internal implementation details such as tool names and schemas, system-prompt structure, memory interfaces, or consent/human-in-the-loop trigger logic.

Microsoft advises security teams using these definitions to influence their planning to inventory their your supply chain, generating a software bill of materials (SBOM) for every deployed agent, to verify agent identity cryptographically, not positionally, by issuing attestable credentials at provisioning, to add the seven new failure modes to their red-team coverage matrix, and to audit the human-in-the-loop user experience as a security control.

The team behind RubyGems, a package hosting site for Ruby developers, has added a new feature to bundler, a tool for managing Ruby packages (or ‘gems’) to protect developers against the recent wave of software supply chain attacks: A cooling-off period before recently updated packages are installed on their systems.

Recent attacks on software repositories have focused on stealing developer credentials in order to introduce malicious code into the packages they create, which then steals more developers’ credentials when they install the malicious updates, and so on. Users of the repositories are vulnerable if they download an affected package during the short interval between it being interfered with and the malicious additions being discovered and removed.

To counteract this, RubyGems team has added a new cooldown argument to Bundler that takes ignores gems until they have been published for a specified number of days. This provides an additional layer of defense against malicious package releases as it gives others an opportunity to identify any malicious code they contain before installation.

The cooldown system works by checking the timestamp of any new versions of gems. Any new additions to the source will have to come from older versions, any new additions will be delayed until they are validated.

In situations where waiting is unhelpful — for instance when a known-good package is released to patch a dangerous security flaw — the delay can be overridden.

AI governance is an ongoing game of catch-up for enterprises. Model updates and iterations are rolling out at a rapid clip, often making governance frameworks obsolete before they’re battle-tested.

To evolve beyond this paradigm, OpenAI is introducing Active sessions. This new ChatGPT security feature allows users to review and log out of one or more sessions through a simple interface. The feature is now available across all ChatGPT accounts and workspace types, including personal and managed workspaces. Experts call it an important development for the model provider, which currently has 1 billion monthly active users.

Previously, organizations often had limited visibility into where users were logged in, and simply relied on password resets or broad account actions to force re-authentication, noted Ensar Seker, CISO at SOCRadar. “Granular session control is a more efficient and less disruptive approach. From a governance perspective, session transparency improves accountability and supports investigations,” he explained.

A holistic view across session activity

Active sessions allows admins to see known browser and app sessions across ChatGPT, Codex, and API Platform. Specifically, they are able to view device and browser information, approximate location, sign-in date and time, whether a device is trusted, and whether the session is current.

To access the feature, users can go to ‘Settings’ > ‘Security’ > ‘Active sessions.’ They can then log out of specific sessions and remove devices from trusted services. They also have the ability to log out of all sessions (thus ending sessions across devices), however, this action can take up to 30 minutes to complete.

However, OpenAI emphasizes that session details may be “approximate or incomplete,” and that the feature has limits. It does not show or manage connected apps or third-party app sessions, sign-ins through third-party services, Codex CLI sessions, or recently signed-out sessions.

Further, Active sessions cannot be used with accounts linked to an enterprise’s single sign-on (SSO), including security assertion markup language (SAML) and OpenID Connect (OIDC).

Better late than never

While Active sessions is an important security and governance development, experts note that the feature is basic, and was a long time coming.

“The reality of OpenAI offering the ability to end active sessions on ChatGPT by administrators is that it’s something that exists in lots of platforms,” said David Shipley of Beauceron Security. “They should’ve had it sooner, but better late than never.”

From a security standpoint, he noted, OpenAI could do a better job policing ChatGPT to prevent it being used by threat actors to host malware, which is the latest threat to enterprises.

SOCRadar’s Seker also pointed out that this type of visibility and oversight is something that enterprises have expected from SaaS platforms for years. “It allows administrators and users to quickly identify unauthorized access, terminate stale sessions, and reduce the risk of account compromise persisting undetected.”

Iterative upgrades disrupt governance

Last week, OpenAI updated GPT-5.5 Instant in both the ChatGPT app and API to “improve response style and quality,” the company said. It had rolled out GPT-5.5 Instant earlier in May as a successor to GPT‑5.3 Instant, calling it “generally smarter” and prone to fewer hallucinations.

According to OpenAI, the update makes GPT-5.5 Instant “easier to read, more natural in everyday conversations, and better paced in practical help tasks, with fewer overly long or bullet-heavy responses.”

But even with tools like Active sessions, enterprises continue to struggle with governance amidst seemingly continuous iterative model updates. It’s simply not sustainable, said Beauceron’s Shipley: “How do you build an appropriate testing plan with a nondeterministic system?”

SOCRadar’s Seker pointed out that many organizations perform security, compliance, and business validation testing before approving a model for production use. But, “when model behavior changes under the same version family, previously documented assumptions may no longer fully reflect actual performance,” he noted.

“The biggest governance challenge in AI is not model adoption, it’s model change,” Seker said. “Most organizations can evaluate a model once. Far fewer are prepared to continuously evaluate how that model evolves over time.”

This particularly creates challenges for regulated industries where auditability, repeatability, and change management are critical, he said. Even beneficial improvements can introduce governance concerns if organizations are not clearly informed about what changed and when.

Valence Howden, advisory fellow at Info-Tech Research Group, noted that organizations often can’t assess the implications of model iterations against their boundaries, and, worse, are often unaware of them.

While the biggest enterprise challenge was initially tied to which AI model was being used, what that model did, and who owned it, iterative updates can muddy those waters and increase reliance on third party practices and tools that organizations often don’t have the resources for, he noted. 

“Without the ability to opt out [of an update] before it’s incorporated, [enterprises] are basically red-teaming the updates with their clients,” said Howden.

The ongoing game

Security teams today are pushed to their limits because they are expected to manage rapidly evolving models, new features, and changing behaviors, while maintaining compliance, risk management, and business continuity, said SOCRadar’s Seker.

“Governance is difficult because organizations are no longer evaluating a static product,” he said. Rather, they are managing a “continuously evolving service” where capabilities, integrations, and user behaviors can change far faster than can traditional security review cycles.

Info-Tech’s Howden agreed, saying that enterprises’ existing governance practices, especially accountability, are poor, as are their risk practices.

“It’s hard to suddenly become good at things they’re already poor at doing,” he said. “They are also incentivized for speed and innovation, so they ignore governance as a constraint, or don’t want to do it at all.”

How enterprises should respond

Seker advised that, ultimately, organizations should treat AI models as living systems rather than fixed software releases.

Security and governance programs should include continuous validation, monitoring, and periodic re-assessment instead of sole reliance on one-time approval processes, he said. Enterprises should also establish clear vendor change management expectations, including requiring transparency around model updates, behavioral changes, and potential impacts to existing workflows.

“Effective AI governance increasingly depends on visibility into change, not just visibility into risk,” Seker said.

A vulnerability in GitHub’s browser-based VSCode editor could lead to the theft of a developer’s token under certain circumstances, says a researcher.

The issue, revealed this week in a blog by Ammar Askar, has apparently been already addressed by GitHub owner Microsoft. But it raises a questions about both DevOps security, and about the researcher’s allegation that, because Microsoft doesn’t treat bug discoveries seriously, he can justify giving it short notice before openly publishing vulnerabilities he finds.

First, the bug: Users of github.com may not realize it, but when they are on any repository, they can shift to github.dev and its browser-based version of VSCode just by changing the URL.

Why do this? Because the browser instance of VSCode is pretty powerful, Askar says in his blog. “You can view all the files in the repo (even if it’s a private one), you can send out pull requests, and even make commits.”

Rob Enderle, a IT consultant who heads the Enderle Group, agrees that jumping into VSCode this way is “an incredibly useful tactical tool for quick tasks. By just hitting the ‘.’ key in any GitHub repo, you instantly get a browser-based VS Code interface without having to clone gigabytes of data locally. It’s perfect for rapid PR reviews, quick documentation edits, or navigating code on the fly without breaking your workflow. Just keep in mind that it runs entirely in the browser sandbox; there’s no compute backend, no terminal, and no code execution.”

For any heavy lifting or actual compiling, he added, the developer will still need the raw compute of a local workstation, or a full cloud environment like Codespaces.

The problem, Askar says, is that this functionality is achieved by github.com POSTing over an OAuth token to github.dev that allows it to interact with GitHub on your behalf. “The token is not scoped to the particular repo you interacted with, meaning it has full access to every other repo that you have access to,” he wrote in the blog.

“The presence of this token, and the fact that this web app is running almost the entire brunt of VSCode’s million line Typescript codebase, makes it a great target for anyone looking into VSCode bugs,” he wrote.

The exploit

Askar said that a threat actor could install an extension in a repository using a Jupyter notebook, a web application for creating and sharing computational documents that has the ability to install a malicious local workspace extension while skipping the publisher trust check. In his proof of concept, Askar said that once his payload runs, the newly installed extension will grab the GitHub API token, run a query to get the private repos the developer has access to, and then print out the replies and the token.

This vulnerability also exists in the desktop version of VSCode, Askar said, though it’s harder to exploit, since a threat actor would need to convince the victim to clone their repo and open the notebook containing the webview script payload. “Of course,” he added, “if you [the hacker] had some other XSS [cross-site scripting attack] in a webview that you can get a victim to open, you get effectively full RCE [remote code execution] on their computer.”

In an email, he said this vulnerability was “about as serious as it gets. Any website on the internet could have redirected you to a github.dev link that could have provided an attacker a token to read and modify your code repos. If one could convince the maintainer of a popular software project to click a link, they could have made whatever modifications they wanted to their project.”

This means, said Enderle, “we have to start treating developer endpoints with strict, isolated, zero-trust parameters, because we clearly cannot rely on vendor complacency to protect us.”

This issue reinforces the point that you should never follow any links unless you know exactly where they will take you, added Dwayne McDaniel, principal developer advocate at GitGuardian.

Short notice

Here’s where things get complicated. Because of an unhappy experience when disclosing a previous VSCode vulnerability to Microsoft — the bug was fixed, but Askar wasn’t given credit — this time he only gave GitHub one hour notice that this new discovery was going to be published. Microsoft applied what Askar calls a “stopgap” fix by adding a confirmation when a developer opens notebooks in web VSCode, and by not allowing the trusted publisher requirement to be skipped by commands.

[Related content: When responsible disclosure becomes unpaid labor]

An ethical question

Askar’s short notice raises an ethical question: How far in advance should a responsible researcher give notice to a vendor about a vulnerability before publicly revealing it?

These days, most infosec pros agree that notice must be given, or else a threat actor can quickly exploit a hole. Not only that, but the researcher risks damage to their reputation if reasonable notice isn’t given. Experienced researchers often give vendors at least 30 days to create and distribute a patch.

For their part, vendors often create bug bounty programs, or partner with bug bounty programs, to reward researchers for their work. Unfortunately, some vendors don’t always credit researchers, or downplay the damage a vulnerability can cause. In fact, last month Microsoft and a prominent cybersecurity researcher got into a public spat about one such alleged incident.

An imbalance of power

Asked for comment about Askar’s most recent discovery, a Microsoft spokesperson said, “we value the critical role that the security research community plays in strengthening the security of our products, services, and the broader technology ecosystem. While independent researchers determine when and how to publish their findings, we remain committed to rapidly assessing reported issues, mobilizing the appropriate engineering and security response resources, and delivering mitigations, guidance, and protections as quickly as possible to help safeguard our customers.”

The spokesperson added that the issue Askar reported “has been mitigated for our services and no customer action is required.”

[Related content: Is the vulnerability disclosure process glitched?]

There is a balance between coordinating disclosure with a software vendor (CVD) and full disclosure, Askar told us. But, he added, there’s an imbalance of power. “A security researcher can pour countless hours into an issue, ensuring they develop a good proof of concept and provide all the steps to recreate the issue. With this, they hope to at least get an acknowledgement for their efforts, which they can use to further their security track record or, in the best case, a monetary bounty reward.”

However, he added, “If security vendors don’t adhere to their side of the bargain, public disclosure is one of the few options security researchers have (if they don’t want to sit on their vulnerabilities or sell them on the black market). It forces the vendor to acknowledge the security issue publicly and usually leads to a much faster resolution than any private communication would.”

This, said Enderle, creates problems for enterprises: “When vendor bureaucracy penalizes responsible disclosure, it alienates the security community and forces public zero-day drops, ultimately leaving enterprise customers holding the bag.”