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Contain the agent before you investigate it. Pause the affected workflow, fail closed if a safety control is unavailable, revoke or narrow its permissions, block dangerous tools and destinations, and preserve the run history and system logs. Once the action is contained, reconstruct every decision and tool call, determine whether the failure was a model mistake or a control failure, recover from a known-good state, and keep autonomous execution disabled until a human owner approves the fix.
This procedure applies to agents that can change infrastructure, access data, send messages, open tickets, deploy software, alter accounts, or invoke other systems. It is designed to work across vendors because the essential controls belong at the identity, policy, tool, and logging boundaries—not only in the model prompt.
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1. Declare and contain the incident
Use the first minutes to stop additional impact, not to debate why the agent acted. Treat an unsafe action as an incident even when the visible result appears minor; an apparently harmless permission change or message can trigger downstream automation.
Record the minimum incident facts
- Time of the first observed harmful outcome and the time the response began.
- Agent name, model and agent version, workflow or task identifier, tenant, environment, and operator.
- The original request, the intended outcome, and the first action known to be unsafe or incorrect.
- Affected accounts, hosts, applications, data stores, queues, deployments, or external recipients.
Write these facts into the incident record before changing configuration. A precise start point makes later log correlation and notification decisions much easier.
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Stop execution and fail closed
- Pause the agent run or disable the specific workflow. If you cannot pause it cleanly, disable its scheduler, queue consumer, or execution worker.
- Fail closed when risk classification, approval validation, policy lookup, identity verification, or audit logging is unavailable. Do not let an agent proceed on a timeout or an empty policy response.
- Revoke or narrow the credentials used by the run. Remove write, delete, privilege-management, production, and external-communication permissions first.
- Block destructive commands, high-risk integrations, unknown destinations, and new outbound network paths at the tool gateway, proxy, firewall, or identity layer.
- Stop dependent automations that could consume the agent’s output and propagate the change.
OWASP’s AI Agent Security Cheat Sheet explicitly recommends user interruption and rollback, least privilege for every tool and permission, and fail-closed behavior when safety checks or audit functions fail.
Preserve volatile evidence before cleanup
Do not delete the agent’s run, truncate traces, rotate away the only copy of a token-use record, or restore a system before collecting evidence. Preserve the agent transcript, retrieved context, tool arguments and results, retries, errors, approval records, identity-provider events, network and application logs, and the current state of affected systems. Record who collected each item and when. If logs are normally short-lived, export them to protected, centralized storage immediately.
2. Reconstruct exactly what happened
The final text shown by an agent is not an execution record. Reconstruct the action chain from infrastructure logs and join records by a run ID, session ID, request ID, or another immutable correlation key. If no common key exists, correlate timestamps, identities, target resources, and network events while documenting uncertainty.
Build a single chronological timeline
| Timeline element | What to capture | Why it matters |
|---|---|---|
| Trigger and task context | User request, system instructions, retrieved documents, memory, tool output used as context, policy version, and task parameters | Shows what the agent was asked to do and whether untrusted content altered the task. |
| Agent identity | Agent and model version, service account, session, tenant, operator, delegation chain, and execution environment | Distinguishes one run from another and reveals inherited or delegated authority. |
| Tool activity | Every tool call, exact arguments, result, retry, timeout, error, approval reference, and execution timestamp | Identifies the precise call that caused the side effect instead of relying on the agent’s explanation. |
| Effective authorization | Tokens, roles, scopes, group memberships, policy decisions, destination restrictions, and approval state at the moment of execution | Shows what the agent could actually do, which may differ from its configured role. |
| Targets and side effects | Assets touched, records read or changed, configuration diffs, messages sent, tickets opened, deployments, data transfers, and downstream triggers | Defines the real blast radius and catches effects the agent did not report. |
| Response activity | Alerts, operator interventions, credential revocations, isolation, rollback attempts, and final recovery state | Establishes when propagation stopped and whether recovery itself introduced changes. |
Protect the evidence
- Send copies to centralized storage with restricted write access, protected retention, and an audit trail for reads and exports.
- Separate the account that writes logs from the account that can administer the agent; an agent compromise should not permit log deletion.
- Capture clock and time-zone information so events from identity, network, cloud, and application systems can be ordered correctly.
- Mark missing records explicitly. Never fill a gap with an assumption that a tool call did or did not occur.
CISA guidance calls for logging user activity, administrator actions, network traffic, application logins, and system events; centralizing those logs; alerting on high-risk events such as privilege escalation; protecting logs from unauthorized access or deletion; and assigning incident-response roles.
3. Establish the blast radius
Containment stops future actions; blast-radius analysis determines what the completed actions already changed. Start with the first unauthorized or incorrect call and follow every direct and indirect dependency.
Check identities and access
- List accounts whose roles, group memberships, keys, tokens, sessions, or password-reset settings changed.
- Identify secrets the agent could read, copy, expose in a tool result, or send to an external destination.
- Compare effective permissions before and after the event, including temporary elevation and delegated access.
- Invalidate sessions and rotate credentials when exposure is possible, not only when a secret is visibly printed.
Check systems and data
- Compare infrastructure and application configuration with a known-good baseline or versioned change record.
- Inspect data reads, exports, deletions, edits, and permission changes, including records accessed through secondary tools.
- Trace messages, tickets, deployments, queue jobs, webhooks, and other outputs that could have triggered further automation.
- Check network destinations, DNS activity, object-storage access, and egress volume for unexpected transfers.
Separate confirmed effects from possibilities
Label each finding as confirmed, probable, or unverified. A missing log is not proof that an action did not happen. Keep the unverified set visible until retention windows, system owners, or independent telemetry resolve it.
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4. Determine whether the problem was model error or control failure
Compare the observed sequence with the intended task and the policy that should have governed it. One incident can have several causes; classify each contributing condition rather than forcing a single label.
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The agent selected an incorrect action even though the action was authorized and the tools behaved as documented. Examples include applying a configuration to the wrong environment, misunderstanding a natural-language constraint, or choosing a destructive operation when a read-only inspection would have satisfied the request. Corrective work includes clearer task boundaries, structured parameters, confirmation of target and scope, and evaluations that test ambiguous requests.
Context or prompt manipulation
Untrusted instructions in retrieved documents, memory, user input, or tool output changed the plan. Preserve the exact content supplied to the model, its source, trust classification, and the point at which it entered the context. Treat external text as data unless a separately enforced policy allows it to issue commands. Sanitizing a prompt alone is not a sufficient control for a tool that can make high-impact changes.
Excessive agency
The agent had more permissions, tools, destinations, or autonomy than the task required. A read-only inventory task should not carry delete rights; a staging deployment should not reach production; and a ticket triage agent should not be able to alter identity policy. Reduce scopes, split duties, use task-specific credentials, and require a fresh authorization check immediately before execution.
Control-plane failure
An approval, identity, policy, logging, rate-limit, or rollback control was missing, stale, misconfigured, or bypassed. Verify the policy version and decision returned at execution time, not just the policy visible in an administrative console. If an approval was recorded, confirm its requester, approver, scope, expiration, and linkage to the exact parameters executed.
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An API, connector, wrapper, or integration applied a parameter incorrectly, returned unsafe data, retried a non-idempotent operation, or produced an unexpected side effect. Reproduce the call in a safe environment with the same version and parameters. Compare the agent’s requested arguments with the tool’s received arguments and the target system’s audit record.
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Use evidence at the infrastructure boundary
Do not infer root cause from the agent’s final explanation. Verify the executed calls, effective authorization, policy decision, and target-system result independently. The model may be mistaken about what it did, what a tool returned, or which account performed the action.
5. Remediate and recover deliberately
Stop propagation
- Isolate affected hosts, accounts, queues, integrations, or network paths when continued activity could worsen the incident.
- Disable scheduled retries, event handlers, and downstream jobs that consume the agent’s output.
- Preserve the current state and configuration diff before applying a rollback, so responders can explain what changed.
Restore a known-good state
- Select a dated, verified configuration or backup from before the first harmful action.
- Restore in dependency order, beginning with identity and policy controls, then infrastructure, applications, and data.
- Validate service health, data integrity, access boundaries, queues, integrations, and monitoring after each major restoration step.
- Reconcile every externally visible side effect: access changes, messages, tickets, deployments, notifications, and data transfers.
A rollback is not complete when a version-control diff looks clean. Confirm that caches, replicas, scheduled tasks, credentials, and downstream systems reflect the intended state.
Rotate exposed credentials
Rotate API keys, service-account secrets, signing keys, session tokens, and database credentials when the agent could have accessed them or when logs may contain them. Invalidate existing sessions and review where the credentials were used. Update dependent services safely; an incomplete rotation can create an outage while leaving the original exposure active.
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Keep autonomy disabled until sign-off
Leave the affected agent disabled or approval-gated while owners review the corrected policy, permissions, tool implementation, monitoring, and rollback path. The approving human should verify a bounded test in a non-production environment and record the conditions for re-enablement.
6. Harden the design before re-enabling the agent
Enforce policy outside the model
Place authorization, input validation, destination allowlists, risk classification, approval checks, and execution constraints in a gateway, proxy, or tool-execution layer. The model can propose an action, but an independently enforced control must decide whether the exact action is allowed. Re-check authorization at execution time because roles, approvals, and target state can change between planning and execution.
Use task-scoped least privilege
- Issue short-lived credentials limited to the task, environment, resources, operations, and data fields required.
- Separate read, write, delete, privilege-management, and external-communication capabilities.
- Use distinct identities for planning and execution when practical, and prevent the planner from minting broader credentials.
- Allow only approved tools and destinations; deny by default and make exceptions explicit and auditable.
Require human approval for high-impact actions
Require explicit approval for destructive operations, financial commitments, sensitive-data access or transfer, privilege changes, production modifications, and actions with irreversible or difficult-to-reverse effects. Bind approval to the exact target, parameters, risk summary, expiration, and agent run. A generic approval to “handle the incident” should not authorize every subsequent tool call.
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Limit rate, budget, concurrency, and blast radius
- Set maximum calls, spend, data volume, runtime, concurrent operations, and affected-resource counts per task.
- Require a pause after a threshold or an unusual pattern so a human can review before propagation continues.
- Use sandboxes and disposable environments for experimentation, tool discovery, and evaluation.
- Make destructive operations idempotent where possible and require a pre-change snapshot or transaction boundary where not.
Make interruption and rollback dependable
Provide an operator control that stops new calls, cancels queued work, revokes credentials, and prevents retries. Test it while a tool is running, during a network partition, and after a worker has lost contact with the control plane. Rollback must identify the changes made by the run and restore dependent systems, not merely reverse the last API call.
Monitor continuously
Alert on privilege escalation, new destinations, unusual data volume, policy-denied actions, repeated retries, disabled logging, approval bypass, and changes outside the task’s declared scope. Give each alert an owner and a response playbook. Monitoring without a staffed response path is visibility, not containment.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.7. Design an audit trail that answers the hard questions
An agent-action audit log should let an investigator answer: who or what initiated the run, what the agent knew, which policy applied, what it attempted, what was authorized, what actually executed, and what changed afterward.
| Audit field | Required detail |
|---|---|
| Run identity | Immutable run ID, parent task, session, tenant, agent version, model version, environment, and operator. |
| Context provenance | Input request, retrieved item identifiers and trust levels, memory references, policy and prompt versions, and timestamps. |
| Decision record | Risk classification, proposed action, approval ID, policy decision, reason for allow or deny, and expiration. |
| Execution record | Tool name and version, exact parameters, sanitized result reference, retries, timeout, error, target, and completion status. |
| Authorization snapshot | Credential identity, scopes, roles, delegated principals, destination restrictions, and effective permissions at execution time. |
| Side-effect record | Before-and-after resource versions, data accessed, messages or transfers, downstream job IDs, and rollback reference. |
| Response record | Alerts, human interventions, interruption time, credential revocation, isolation, recovery actions, and final approval. |
Protect these records against unauthorized access and deletion, retain them long enough for the incident and regulatory needs of the environment, and test that an investigator can retrieve a complete timeline without relying on the agent itself.
8. Compare agent designs by control strength
When choosing between two autonomous-agent architectures, compare the controls that remain effective when the model is wrong or compromised. A polished interface or higher task-completion rate does not compensate for weak execution boundaries.
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|---|---|
| Permission scope | Are credentials task-scoped, short-lived, and separated by operation and environment? |
| Policy enforcement | Is policy enforced in a gateway or tool layer, or only described in a prompt? |
| Human approval | Which destructive, financial, sensitive-data, privilege, and production actions require explicit approval? |
| Tool and destination controls | Are tools and outbound destinations allowlisted, validated, and denied by default? |
| Logging | Are context, calls, parameters, approvals, effective permissions, results, and side effects centralized and tamper-resistant? |
| Interruption and rollback | Can operators stop queued and in-flight work, revoke credentials, and restore dependent systems? |
| Isolation and limits | Are there sandboxes, rate limits, budgets, concurrency caps, and resource-count limits? |
| Recovery | How quickly can owners identify affected assets, restore a known-good state, rotate secrets, and validate integrity? |
| Evidence quality | Can an investigator reconstruct the full chain without trusting the agent’s narrative? |
9. Map the runbook to recognized governance practices
NIST published the AI Risk Management Framework 1.0 on January 26, 2023. It is voluntary, rights-preserving, non-sector-specific, and use-case agnostic, and organizes risk work into Govern, Map, Measure, and Manage.
Manage 2.4: supersede, disengage, or deactivate
Maintain a tested mechanism and an assigned owner who can supersede, disengage, or deactivate an agent when its performance or outcomes are inconsistent with intended use. The mechanism must work during degraded dependencies and must not depend on the agent cooperating.
Manage 4.1: post-deployment monitoring and response
Define monitoring plans with user and actor input, appeal and override, decommissioning, incident response, recovery, and change management. Document who can approve re-enablement and what evidence they must review.
Manage 4.3: communicate, track, recover, and document
Communicate incidents and errors to the people who need to act, track response milestones, recover affected services and data, and document lessons that change policies, tooling, training, and tests.
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10. Exercise the controls before the next incident
Run controlled evaluations and tabletop exercises that cover both agent mistakes and control failures. At minimum, test:
- An incorrect but authorized change to the wrong environment.
- Prompt or context manipulation through a retrieved document or tool result.
- An approval service, policy lookup, or audit logger becoming unavailable.
- A tool retrying a non-idempotent operation or returning malformed data.
- Privilege escalation, unexpected outbound destinations, and excessive data volume.
- Operator interruption during an in-flight call and credential revocation during a retry.
- Restoration from backup followed by validation of dependent services and data integrity.
Measure time to detect, time to pause, time to revoke access, completeness of the reconstructed timeline, recovery time, and the number of side effects that required manual reconciliation. Feed every exercise and real incident into policy and procedure changes.
Quick Recap
11. Common response mistakes and the safer alternative
| Mistake | Why it fails | Safer alternative |
|---|---|---|
| Relying on the agent’s explanation | The model may misstate tools, targets, permissions, or results. | Verify execution and authorization at the tool and target-system boundaries. |
| Deleting the run to stop the problem | It destroys evidence and may not stop queued or delegated work. | Pause execution, revoke credentials, block tools, and preserve logs. |
| Restoring immediately without a snapshot | You can lose the evidence needed to identify side effects and prove recovery. | Capture the current state and configuration diff, then restore in dependency order. |
| Fixing only the prompt | A compromised or confused model can still reach dangerous tools. | Enforce least privilege, validation, approval, and allowlists outside the model. |
| Assuming a denied call had no impact | Retries, partial execution, or earlier calls may have changed state. | Check tool, network, and target-system records for partial and downstream effects. |
| Re-enabling after a successful demo | A demo may not exercise failure modes, degraded dependencies, or rollback. | Require a bounded test, complete evidence review, and owner sign-off on recovery controls. |
12. A concise incident checklist
- Record time, agent and model versions, workflow, tenant, operator, and first harmful outcome.
- Pause the run and dependent automation; fail closed when a safety control is unavailable.
- Revoke or narrow tokens; block destructive tools, destinations, and integrations.
- Preserve transcripts, context, tool traces, approvals, identity events, network logs, and target-system logs.
- Correlate the complete action chain and snapshot effective permissions.
- Determine affected identities, hosts, data, configurations, messages, deployments, and transfers.
- Classify contributing causes as planning, context manipulation, excessive agency, control-plane, or tool defects.
- Isolate propagation, rotate exposed credentials, restore from a known-good state, and validate dependencies.
- Keep autonomy disabled or approval-gated until a human owner signs off.
- Update policies, permissions, tools, monitoring, rollback, and exercises based on documented lessons.
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