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Before an AI agent goes live, verify that its tools and credentials allow only the actions its task requires, that a separate control checks consequential actions, that activity is visible to responders, and that a human can stop the runtime without the agent’s cooperation. Use the checklist below before launch and repeat it after changes to prompts, tools, memory, retrieval, credentials, models, or orchestration.
1. Map the agent’s authority before granting it
Start with the actions the agent must perform, then compare them with what its tools and credentials actually permit. A prompt saying “do not delete records” is not an access control: enforcement belongs in the tool’s backend, an authorization service, or another deterministic execution boundary.
- Inventory every tool, connector, API, data source, credential, reachable system, and downstream action.
- For each tool, record whether it can read, write, send, delete, deploy, or purchase—and which resources and users it can affect.
- Remove unused functions and replace open-ended tools with narrower operations where possible. Separate read and write access when the task does not need both.
- Use user-bound or delegated identity where practical instead of a broad shared service identity. Restrict credentials by task, resource, and duration; make them revocable.
- Enforce authorization for every action. Validate the tool name, input schema, arguments, actor, tenant or session, and target resource before execution. Re-check authorization if the context or scope changes.
- Keep policy controls outside the agent’s ability to rewrite them. Treat retrieved webpages, documents, email, and tool output as untrusted input.
- Set explicit limits for steps, loops, retries, invocation rate, and cost.
OWASP’s Excessive Agency guidance illustrates why the distinction matters: a document-reading extension can be overpowered if its downstream identity can also update or delete records, or if a privileged identity acts across user boundaries. Assess the task against the effective permissions of both the tool and its credential—not just the agent’s stated purpose.
2. Decide which actions require a policy gate or human approval
Do not give every action the same approval path. Classify actions by their impact, reversibility, affected people or data, external visibility, and potential blast radius. The following is a practical policy template, not a prescribed OWASP or NIST classification.
#1 Best Overall
| Action category | Typical handling | Examples to classify in your environment |
|---|---|---|
| Low impact and readily reversible | May be automated if permissions are narrow and the action is logged. | Read an authorized document; draft text without sending it. |
| Meaningful impact or limited reversibility | Require a preview, extra validation, or a human checkpoint according to policy. | Change a shared record; send a message to a limited audience. |
| High impact, irreversible, or broad blast radius | Require action-specific human authorization or block agent execution. | Delete important data; deploy to production; make a consequential external commitment. |
For high-impact actions, separate the model’s proposal from execution. OWASP’s AI Agent Security Cheat Sheet states: “The execution component must still check the actor’s authorization and any required approval for the exact action.” A separate executor should independently verify that the current actor is authorized and that the action remains within policy.
- Bind approval to the agent or requester, tool, target, normalized parameters, execution context, and expiry. Make approval single-use where feasible.
- Reject an approval if the target or parameters change after review, or if it has expired. Do not treat a confident model response or a generic “approve” as authorization for a different action.
- Fail closed if the policy check, approval, risk classification, or audit path is unavailable. Decide in advance what happens if an approver does not respond; OWASP AISVS calls for blocking when approval is not satisfied within the defined time.
- Use idempotency where possible. If duplicate execution remains possible, require explicit confirmation or another safeguard against retries.
3. Monitor actions and control failures
Logs should let an incident responder reconstruct what happened without collecting unnecessary secrets or sensitive content. Record denied attempts as well as successful executions.
- Identity and context: actor or service identity, agent instance, session, tenant or user context, and timestamp.
- Action and authority: tool, target, relevant parameters, effective permission state, policy version, and risk classification.
- Decision and result: approval identifier and outcome, authorization result, execution status, and errors or incomplete work.
- Privacy and integrity: redact credentials, minimize sensitive payloads, restrict log access, and preserve enough context for investigation.
Alert on attempted permission expansion, unexpectedly powerful tool selection, unusual call frequency, repeated approval failures, out-of-pattern high-impact actions, abnormal loops or cost, and suspected data exfiltration. Connect agent events to existing security monitoring and incident response; assign an owner and a response action to each alert, such as pausing a workflow, revoking credentials, blocking a tool, requiring human review, or activating shutdown.
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Test the monitoring path itself. Verify that a tool call creates a record with identity and policy context, that denied calls are captured, and that alerts reach the right responder. OWASP AISVS identifies weak SIEM correlation, infrequent-only drift checks, and missing AI forensics as monitoring pitfalls.
4. Make emergency shutdown independent of the agent
Name the person or role authorized to stop the system and provide a route that works if the agent is compromised, stuck, or unresponsive. OWASP AISVS calls for reliable, exercised shutdown and graceful-degradation paths under human control. The shutdown mechanism should be out of band and isolated from the agent runtime; asking the agent to stop itself is not a sufficient control.
- Define the stop scope. Specify whether the control blocks new tool calls, revokes credentials, interrupts active inference or jobs, halts downstream workers, or isolates connected services. Decide which actions are immediate and who can invoke them.
- Set in-flight behavior. Preserve traces and incident evidence, prevent partial writes where possible, mark incomplete work clearly, and ensure restart does not replay an action unintentionally.
- Choose recovery options. Document when to roll back to a stable version, disable a function, enter safe mode, or hand critical work to a human. AWS Prescriptive Guidance recommends planning for rollback, safe mode, and continuity or fallback systems for critical operations.
- Rehearse and record. Exercise the stop and recovery path on a schedule and after material architecture changes. Record the date, result, owner, gaps, and remediation. A control that exists only in documentation has not demonstrated that it can stop the running system.
5. Test misuse cases before launch and after changes
Run repeatable tests against the actual runtime and verify the expected enforcement, logging, alerting, pause, or shutdown behavior. OWASP recommends structured security testing before production and after material changes.
- Direct and indirect prompt override, including hostile instructions in retrieved content or tool output.
- Unauthorized tool calls, invalid arguments, cross-user or cross-tenant access, and attempts to expand permissions.
- Malicious or misleading memory and retrieved content; suspected data exfiltration.
- High-impact actions without valid approval, an expired or reused approval, and approval followed by changed parameters or target.
- Recursive tool use, excessive retries, abnormal invocation volume, or cost-limit evasion.
- Multi-agent delegation that attempts to pass work to an agent with broader authority.
- Shutdown during active work, credential revocation, restart behavior, and recovery into the chosen safe mode or fallback.
For each run, retain the tested agent, model, tool-policy configuration, test case, expected and observed outcome, and residual risk. Repeat the tests when prompts, tools, policies, retrieval, memory, credentials, model or provider, or orchestrator change.
6. Assign responsibility for the deployment you actually run
Hosted services do not remove the customer’s need to configure and operate controls. Microsoft’s shared-responsibility guidance distinguishes IaaS, PaaS, and SaaS arrangements across agent scope, tool permissions, identity, approvals, orchestration limits, sandboxing, and monitoring. It identifies customer responsibilities that remain across deployment models: protecting data, managing agent identity and credential scope, authorizing actions, and providing human oversight.
Best Value
Use the responsibility model for your specific service to assign owners for configuration, operation, monitoring, incident response, and recovery. Confirm the division with the owners of downstream tools as well as the cloud or agent provider; a provider’s controls cannot substitute for authorization enforced by the systems the agent can reach.
Use the checklist as a deployment control, not a one-time sign-off
Keep the inventory, approval rules, alert ownership, shutdown procedure, test evidence, and residual risks together with the deployed configuration. Revisit them at launch and after any material change. The recommendations here are platform-neutral: exact IAM policies, log schemas, and shutdown controls depend on the chosen framework and deployment. NIST’s voluntary AI Risk Management Framework is a useful broader reference, but it is not itself a binding agent-security checklist; NIST reports that AI RMF 1.0, released in 2023, is being revised.
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