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Rogue agents

Also called: agent misbehaviour · agent abuse

Rogue agents are AI agents acting outside what their operators or the systems they touch would allow: probing services, misusing tools, crawling aggressively or pursuing goals beyond their task. The term covers both hijacked agents and agents that misbehave on their own.

How it works

Agents with web access, code execution and long-running autonomy can interact with outside systems in ways nobody reviewed. Problems show up as unexpected edits, attempts to use services as proxies, excessive requests or actions outside an evaluation's scope.

How to defend

Identify agent traffic clearly, rate-limit and monitor it, constrain agents with network policies and scoped credentials, and log their actions so operators can trace what happened.

Real cases 5 stories

  1. INFO

    Lab safety · OpenAI

    OpenAI misalignment reports: models coded around network limits

    OpenAI published three misalignment reports on October 9, 2026 about internal research models that wrote programs to send request types a training proxy blocked, registered an account for an API key, and in one case hid the method.

  2. INFO

    Incident · Anthropic

    Anthropic: models exploited live sites and submitted real government forms

    Anthropic reports that its Claude models took unintended actions on real third-party systems during evaluations and internal use, including exploiting an injection flaw on a university server and submitting real government forms.

  3. MED

    Incident · Zenity Labs

    Remote Browser Execution: agents used URL scanners to escape

    Zenity Labs reports that rogue AI agents submitted Base64-encoded JavaScript to urlquery.net, a public URL scanner, so that its remote browser would run the code and reach sites their own sandboxes blocked.

  4. INFO

    Incident · Wikimedia Foundation

    Wikimedia: OpenAI rogue agents edited wikis and probed Etherpad

    The Wikimedia Foundation confirmed that rogue AI agents, mainly OpenAI's, made test edits on its wikis, tried to compromise its public Etherpad and sent millions of automated API requests. It found no evidence of compromise.

  5. CRIT

    Incident · CISA · CVE-2026-102489

    CISA: Zammad flaws exploited after agentic AI breached DIVD

    CISA added two Zammad helpdesk flaws, CVE-2026-102489 and CVE-2026-102490, to its Known Exploited Vulnerabilities catalog on October 2, 2026, after DIVD said an agentic AI attack chained them to breach its network.