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If an AI agent needs human approval before an action, silence must not let that action run. If the reviewer does not respond—or the review service cannot be reached—the system must keep the action blocked, deny it, or leave it paused for a later explicit decision. A timeout is never approval.
What happens if an AI agent approval request times out?
The action does not execute. The application can treat the pending request as denied, mark it expired, or pause the workflow so a person can review it later. Those are different workflow choices, but all preserve the same security rule: no valid approval, no side effect.
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There is no universal timeout duration established by the guidance cited here. Choose a duration to fit the action and review process; do not let the duration determine consent. OpenAI’s agent documentation says to fail closed when review times out or becomes unavailable, and describes recording an approval interruption that can later be approved or rejected before the saved run resumes. OpenAI: Guardrails and human review
The Tool Desk
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Yes, for actions that require approval. “Fail closed” means that uncertainty or failure in the approval path cannot grant permission. If the reviewer is unavailable, a callback is malformed, or the system cannot verify the decision, the execution boundary must stop the action rather than infer consent.
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This is a security invariant, not a requirement to use one particular software architecture. A terminal denial and a paused, resumable workflow can both be safe. The unsafe outcome is allowing the side effect to proceed because the approval process timed out or failed.
How do I require human approval before an AI agent runs a tool?
Put a deterministic authorization check in the component that executes the tool or in the downstream system that performs the side effect. The agent may propose an action, but its own statement that a person approved it is not proof of authorization. OWASP specifically warns that a flag such as user_confirmed is insufficient on its own. OWASP: AI Agent Security Cheat Sheet
- Propose: The agent submits a tool call with its intended operation and parameters.
- Classify: A policy layer decides whether that kind of action requires review. Risk classification determines whether review is needed; it does not itself authorize execution.
- Review: A reviewer approves or rejects a pending, specific action.
- Enforce: Immediately before execution, the tool boundary verifies that approval is authentic, current, scoped to the submitted action, and not already used. If any check fails, it blocks the side effect.
Keep the authorization check next to the tool or downstream operation that changes state. Agent-level guardrails may not cover every tool in a manager-style workflow, so do not assume a check in one part of the agent automatically protects every execution path. OpenAI’s documentation describes approval interruptions and resuming saved run state, while emphasizing validation at the side-effect boundary. Its behavior is specific to the documented workflow; other frameworks do not necessarily provide these controls automatically. OpenAI: Guardrails and human review
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How do I prevent an agent from reusing an old approval?
Bind each approval to the exact action it authorizes, and consume it only once. At minimum, validate the requesting actor, tool, target, normalized parameters, validity period, and approval’s consumption state. If the agent changes the target or parameters after review, the old approval no longer matches; request approval for the changed action.
Perform the check and consumption atomically immediately before execution. Otherwise, two concurrent or repeated requests might both observe the same approval as unused and run. OWASP recommends this action-bound, one-time approach. OWASP: AI Agent Security Cheat Sheet
Should a timed-out request be denied or left pending?
Either choice can preserve the invariant if timeout never resolves to approval. Select based on how the workflow should recover, and ensure a later approval is explicit and still applies to the action that will execute.
| Timeout outcome | Workflow semantics | Operational consideration |
|---|---|---|
| Deny or expire | The request ends; a new attempt requires a new authorization path. | Provides a clear terminal outcome, but a legitimate action may need to be resubmitted. |
| Pause for later review | The workflow remains suspended until an explicit decision resumes it. | Supports recovery, but the resumed run must revalidate the action and avoid executing a stale or duplicated request. |
OpenAI documents a resumable approval interruption. Microsoft’s Agent Governance Toolkit design record describes a durable pending protocol with fail-closed handling for timeout and other failures. That record is one project’s design, not an industry standard; it also illustrates the added schema, storage, identity integration, and execution latency a durable protocol can entail. Microsoft Agent Governance Toolkit: Action-Bound, Fail-Closed Approval Protocol
Which agent actions should require human approval?
Set review requirements according to the consequences of an action, not simply whether an agent is capable of performing it. Consider potential harm, reversibility, external visibility, privilege, and the interruption cost of asking a reviewer.
Best Value
- Require explicit approval for high-impact or difficult-to-reverse actions, such as sending consequential messages, deleting important data, transferring funds, publishing content, or changing privileged settings.
- Consider exempting clearly low-risk actions, such as read or search operations, when their consequences and access scope justify it.
- Keep permissions narrow even when approval is enabled. An approval prompt does not compensate for giving an agent unnecessary tools or broad downstream privileges.
OWASP frames excessive agency as a risk that can arise from unnecessary functionality, overly broad downstream permissions, or consequential actions without independent approval. Its guidance recommends minimizing extensions and permissions, requiring approval for high-impact actions, and enforcing authorization in downstream systems rather than trusting the model to make the decision. OWASP GenAI Security Project: LLM06:2025 Excessive Agency
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What should you test and record?
Test the approval mechanism as part of the execution path, including failures and repeated requests. A gate that works only when every service responds normally is not a reliable gate.
- Timeout and outage: The reviewer never responds or the review service is unavailable; verify that execution remains blocked.
- Invalid decision: A malformed, unauthenticated, or otherwise unverifiable response cannot authorize the action.
- Restart and recovery: After a process restart, confirm pending state is handled deliberately and a resumed workflow rechecks its authorization.
- Changed action: Modify the target or parameters after approval; confirm the old decision cannot authorize the new request.
- Replay and concurrency: Repeat the request or submit it concurrently; confirm an approval cannot be consumed more than once.
- Audit reconstruction: Record enough to establish which actor requested and approved or denied which action, when it expired or timed out, and whether execution occurred.
OWASP recommends validating approvals and testing failure cases; Microsoft’s design record illustrates idempotent duplicate handling and reconstructable audit events. Audit records should distinguish approval, denial, timeout, and execution outcomes so an incident review can establish whether the protected action ran. OWASP: AI Agent Security Cheat Sheet Microsoft Agent Governance Toolkit: Action-Bound, Fail-Closed Approval Protocol
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