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If an AI agent takes an unintended action, first stop further effects using the safest available control, preserve logs and system state, and find out what the agent touched. Then work with the people responsible for those systems to contain the incident and recover. Your next steps depend on whether the action is still running, whether it affected an external system, and whether sensitive information may have been exposed.
1. Stop further effects without making the incident worse
If there is credible ongoing harm or compromise, use the preplanned control for the affected component: for example, stop the workflow, suspend the session, restrict a tool, or move the agent to a human-reviewed or reduced-functionality mode. Choose a control that addresses the risk without unnecessarily disrupting dependent services.
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These controls are not interchangeable. Stopping an agent may leave its credentials active; revoking a credential may affect other workflows; isolating infrastructure or abruptly killing a process can disrupt service or damage downstream state. If the action is no longer in progress, avoid a hurried restart or cleanup until relevant evidence and state have been preserved, when feasible.
2. Preserve evidence and establish what happened
Before cleanup, rollback, or restart, retain relevant logs and system state when feasible. Record what is available about the agent or session, timestamps, tool calls, targets, parameters, results, approvals, and affected resources. OWASP’s Agentic Skills incident response playbook recommends tamper-evident evidence and chain of custody; an AWS incident-response presentation hosted by NIST advises mapping logs to investigation questions and business functions (presentation).
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Reconstruct the inputs, outputs, and actions you can observe. Do not treat an AI-generated account of its reasoning as proof of what it intended or why it acted. Logs, system records, and the state of connected services are more useful for establishing what occurred.
3. Determine the blast radius
Trace the agent’s integrations and check which resources it accessed or changed, which actions completed or remain in flight, and which permissions or credentials it used. Check for follow-on activity as well as the initial action.
- Was information exposed, sent, or made public?
- Were accounts, permissions, or configurations changed?
- Were files or records deleted or modified?
- Did the agent send external messages, publish content, or initiate a financial action?
- Could another system or workflow have acted on the change?
The checks depend on the connected systems and the action. Involve the owners of those systems rather than assuming the agent’s own logs show every downstream effect.
4. Choose containment and recovery with system owners
Once you know what happened, compare possible controls before acting. The AWS presentation recommends preparing component-level decision trees that account for containment choices and their costs to business functions. Use that approach where available; the right choice depends on the incident and on who has authority to accept the operational impact.
| Option | What it may address | What to check first |
|---|---|---|
| Stop or suspend the workflow | Further actions by the active agent session | Whether work is still in flight, whether the stop preserves state, and which dependent processes will be interrupted |
| Restrict a tool or revoke access | Further use of a particular integration or credential | Whether the credential is shared, which other workflows rely on it, and whether access remains through another route |
| Disable or isolate a component | Potential activity from a compromised or unsafe component | Service dependencies, disruption, and evidence preservation |
| Roll back or restore affected state | Changes already made to data, configuration, or a resource | Whether the action is reversible, what changes would be lost, and who can authorize restoration |
| Switch to a fallback | Continuity of a business function while the agent is unavailable | Whether the fallback is safe and capable of handling the affected work |
These are options, not a universal sequence. Some changes cannot be undone, and containment itself can cause harm. Confirm the likely consequences and approval authority with the relevant system owner before taking a disruptive step.
5. Escalate and communicate according to impact
Follow your organization’s incident process and involve security, operations, and the owners of affected systems. Bring in privacy, legal, compliance, supplier, or communications teams when the facts warrant it. If the system may be compromised or sensitive data may have been exposed, ask the responsible organization to assess whether users or affected people should be notified and what obligations apply in the relevant jurisdiction.
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Notification duties cannot be determined from the fact that an AI agent made a mistake alone. They depend on what happened, which data or systems were affected, and the applicable organizational and legal context.
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6. Fix the weakness before restoring autonomy
Investigate whether the action followed from model error, an ambiguous prompt, direct or indirect prompt injection, excessive permissions or functionality, an inadequate approval step, a compromised tool, or another failure. OWASP’s prompt injection guidance and Excessive Agency guidance describe risks that can increase when agents have broad tools, permissions, or autonomy.
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- Limit permissions and tools to what the task requires.
- Enforce authorization in the connected system, rather than trusting the model to decide whether an action is allowed. OWASP states: “Implement authorization in downstream systems rather than relying on an LLM to decide if an action is allowed or not.”
- Require human approval for high-impact actions.
- Improve logging and monitoring so actions and affected resources can be investigated.
- Review the incident and verify the revised controls before re-enabling the capability.
As Robert Saul, General Manager of the AWS Customer Incident Response Team, put it in the NIST-hosted presentation: “If you can’t describe its identities, its data flows, and its failure modes right now, you don’t have governance over it. You have hope.”
Why an agent may take an unintended action
An unintended action can result from model error, ambiguous instructions, or direct or indirect prompt injection. The possible harm also depends on what tools and permissions the agent has and how much it can do without approval. An incident may therefore be a sign not only of a mistaken output, but of a boundary that allowed that output to change a real system.
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