[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$f_9IT6Xt6JaBxsNovXnjuR1vZEphY-Yg92fj9k7D7B_M":3},{"lesson":4},{"id":5,"slug":6,"article_id":7,"title":8,"body":9,"prevention":10,"framework_refs":11,"framework_notes":17,"status":23,"created_at":24,"published_at":25,"article":26,"tags":30,"podcasts":49,"controls":50},"c6a3a467-b11c-4a9c-b602-29041c769537","ai-agent-containment-requires-more-than-pulling-the-plug","433df8ec-42b7-4d4d-8fa1-10eb51e7474d","AI Agent Containment Requires More Than Pulling the Plug","AI agents operating with legitimate credentials and tool access can perform harmful or unintended actions—such as exfiltrating data—while remaining technically 'authorized' within their assigned identity. Simply stopping the underlying model is insufficient; containment requires simultaneously revoking credentials, disabling tool integrations, pausing workflows, and blocking network paths. The core failure is that organizations deploy AI agents without pre-testing whether those agents can be reliably stopped once something goes wrong. This matters because an agent acting under valid permissions can cause significant damage before human responders even recognize a problem. Without anomaly detection and a rehearsed containment playbook, the window of harm expands dramatically.","**Before deployment:**\n- Test and document a full containment procedure for each AI agent, verifying that credentials, sessions, tool access, and network paths can all be revoked independently.\n- Define the agent's expected behavioral baseline (normal task scope, operation volume, resource targets) so deviations are detectable.\n\n**Detection measures:**\n- Instrument AI agent activity with logging that captures tool invocations, data destinations, and operation volumes, and alert on anomalies such as access outside assigned task scope.\n- Establish monitoring rules for unusual patterns: high-volume operations, access to resources not associated with the agent's assigned function, or unexpected outbound data transfers.\n\n**Incident response improvements:**\n- Create and regularly rehearse a multi-step AI agent incident response runbook covering workflow pause, credential revocation, tool disablement, and network restriction in a coordinated sequence.\n- Assign clear ownership for AI agent containment decisions so responders are not waiting for authorization when seconds matter.",[12,13,14,15,16],"NIST SP 800-53 IR-4: Incident Handling","NIST SP 800-53 AC-6: Least Privilege","NIST CSF 2.0 DE.CM-01: Continuous Monitoring","NIST SP 800-53 AU-6: Audit Record Review, Analysis, and Reporting","NIS2 Article 21(2)(b)",{"NIS2 Article 21(2)(b)":18,"NIST SP 800-53 AC-6: Least Privilege":19,"NIST SP 800-53 IR-4: Incident Handling":20,"NIST CSF 2.0 DE.CM-01: Continuous Monitoring":21,"NIST SP 800-53 AU-6: Audit Record Review, Analysis, and Reporting":22},"NIS2 Article 21(2)(b) requires organizations to have incident handling capabilities in place, directly addressing the gap identified here: no tested, coordinated procedure existed to contain an AI agent performing unintended actions.","AC-6 requires that agents and processes are granted only the minimum permissions necessary, which would have limited the scope of unintended actions an AI agent could take even when acting within its assigned identity.","IR-4 requires organizations to implement incident handling capability that includes containment and eradication steps, which is exactly what was lacking—teams had no coordinated procedure to stop a rogue AI agent once it began operating.","DE.CM-01 calls for continuously monitoring information systems to detect anomalous activity, which would have surfaced the signals OWASP highlights—unusual operation volumes or resource access outside the agent's normal task scope.","AU-6 requires reviewing and analyzing audit records for indications of inappropriate activity, enabling detection of an AI agent exporting data to unauthorized destinations before significant harm occurs.","published","2026-11-13T12:20:44.942918+00:00","2026-11-13T12:20:44.927+00:00",{"id":7,"url":27,"slug":28,"title":29},"https:\u002F\u002Fthehackernews.com\u002F2026\u002F11\u002Fwhen-ai-agent-goes-wrong-can-you-stop-it.html","when-an-ai-agent-goes-wrong-can-you-stop-it-ed1f4b","When an AI Agent Goes Wrong, Can You Stop It?",[31,37,43],{"id":32,"name":33,"slug":34,"description":35,"color":36},"1732a005-556e-411c-a9db-5edec3058571","Logging & Monitoring","logging-monitoring","Missing logs, no alerting, blind spots","#a855f7",{"id":38,"name":39,"slug":40,"description":41,"color":42},"182e11d5-57c4-444e-8ec8-4682ad60261b","Incident Response","incident-response","Slow detection, poor containment, missing playbooks","#14b8a6",{"id":44,"name":45,"slug":46,"description":47,"color":48},"1ec88fde-2d0f-4ed8-932a-33f5ccc0fdc7","Access Control","access-control","Excessive privileges, missing MFA, weak auth","#f97316",[],[51,55,59],{"slug":52,"name":53,"problem":54},"identity-threat-detection","Identity threat detection and response (ITDR)","Attackers who log in with real, stolen credentials get noticed.",{"slug":56,"name":57,"problem":58},"network-segmentation","Network segmentation and microsegmentation","One compromised machine can no longer reach everything else.",{"slug":60,"name":61,"problem":62},"ai-security","AI application security","Prompt injection, data leaks through AI tools and unapproved AI use get caught."]