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Set an AI security agent’s authority in an enforceable policy or execution layer—not in the model’s own judgment. Start with least-privilege tools and task-scoped credentials, then let only low-impact, reversible actions run automatically. Require a human approval tied to the exact operation before an agent can make a high-impact, privileged, irreversible, or externally visible change. If the action is unknown, out of scope, or the policy and audit services are unavailable, block it and escalate.
What approval limits should control
An approval limit is a technical boundary around what an agent may do without a person. It is not a sentence in a system prompt and not a conversational question such as “Are you sure?” If another tool path can execute the operation without an independent authorization check, the limit is not real.
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OWASP’s Gen AI Security Project states the principle directly: “Implement authorization in downstream systems rather than relying on an LLM to decide if an action is allowed or not.” The policy engine, gateway, or execution service must enforce the decision immediately before the side effect.
For each proposed action, the control should answer five questions:
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- Which agent identity and human user are requesting it?
- What tool and exact operation are being requested?
- What resource, tenant, account, or data set is the target?
- What are the operation’s impact, sensitivity, reversibility, and external effects?
- What approval, credential, expiry, and audit record are required?
These checks should run for every execution, including actions suggested by a model, returned by a plugin, or chained from another agent.
Reduce authority before adding approvals
Approval is a second line of defense. The first is to remove capabilities the task does not need. OWASP identifies excessive functionality, excessive permissions, and excessive autonomy as common causes of excessive agency. Prompt injection, model malfunction, and overpowered extensions can turn an otherwise useful agent into a path to sensitive systems.
Use task-specific tools
Expose separate, narrow tools instead of a general-purpose administrative interface. A document-triage agent might have search_document and read_document, but no file-write, delete, shell, or permission-management operation. A security-monitoring agent may retrieve alerts and create a draft incident, while a separate, approved workflow handles containment.
Use least privilege and distinct identities
Give each agent its own identity and only the permissions required for its assigned task. Do not let an agent inherit a human administrator’s standing privileges merely because the human initiated the conversation. OWASP DevSecOps guidance recommends distinct agent identities, task-scoped short-lived credentials, deny-by-default rules, and approval for actions outside explicit allow rules.
Where a user’s authority is relevant, carry that user context to the downstream service and evaluate it there. The agent should not be able to enlarge the user’s permissions by changing a prompt, selecting a different connector, or passing a broader parameter.
Constrain parameters, not just tool names
A tool called update_access is still dangerous if it accepts any principal, resource, role, or duration. Restrict each parameter to an approved scope: named repositories, production accounts, data classifications, network segments, or maximum time windows. Normalize parameters before approval so equivalent representations cannot bypass a rule.
A practical risk-tier policy
The following table is a starting pattern derived from OWASP’s illustrative action list. It is not a universal standard. Adapt the tiers to your assets, sector, jurisdiction, and operational risk.
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| Action class | Default treatment | Illustrative examples |
|---|---|---|
| Low impact, read-only | Permit only when the user, task, and data set are explicitly scoped; log the access. | Search documents; read a file |
| Limited write | Show a preview and request approval unless a narrow, reversible workflow has been explicitly preauthorized. | Write a file |
| High impact or externally visible | Require explicit approval bound to the exact operation before execution. | Send email; execute code |
| Critical or difficult to reverse | Require approval, independent policy validation, stronger authentication, and recovery controls where feasible. | Delete database records; transfer funds |
| Unknown, out of scope, or unvalidated | Deny and escalate. Never infer permission from model confidence or apparent user intent. | Unmapped tool; failed policy, approval, or logging check |
Do not publish universal dollar amounts, record counts, or confidence-score cutoffs. The available guidance supports risk-based boundaries but does not establish numeric thresholds that apply to every organization.
Low-impact read actions
Read-only does not mean harmless. A search over confidential legal, health, or identity data can create a serious disclosure. Permit reads only against the user’s authorized data set, enforce row- or document-level controls downstream, and record the query, target scope, and result access.
Limited writes
Writing a file, changing a ticket, or updating a draft can be automated when the scope is narrow and rollback is reliable. Otherwise show the proposed diff, destination, and resulting permissions and obtain approval. A “write” operation that changes an access-control file or deployment manifest belongs in a higher tier than an ordinary draft.
High-impact and external actions
Email delivery, code execution, production configuration changes, customer notifications, and security-containment actions can affect people or systems outside the agent. Require a human decision for the exact recipient, code or command, target environment, and timing.
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Deletion, funds movement, credential revocation, bulk permission changes, and destructive infrastructure operations need layered controls. Use independent policy validation, step-up authentication, short-lived authorization, replay protection, idempotency, and a tested rollback or recovery path where one exists.
Design the approval and escalation workflow
Approval should be a complete transaction between the requester, policy service, human approver, and execution component. The model can propose an operation, but it must not approve itself.
- Classify outside the model. Evaluate the tool, target, scope, data sensitivity, reversibility, and potential impact. An unknown tool or unmapped operation defaults to review or denial. OWASP’s example classification treats unknown tools as high risk; that label does not authorize the tool.
- Check identity and delegated authority. Resolve the agent identity, the initiating user, the task or case identifier, and the credential’s expiry. Confirm that the user and any designated approver are authorized for this action class.
- Build an action-specific preview. Show the real operation in human-readable terms: tool, target, normalized parameters, affected records or recipients, expected side effects, and whether the change is reversible. Do not display only the model’s natural-language summary.
- Bind the approval. Store the actor, tool, target, normalized parameters, timestamp, expiry, policy version, and approval decision. A token approved for one file, recipient list, or command must not authorize a later variation.
- Validate again at execution. Immediately before the side effect, the execution service rechecks policy, identity, approval status, expiry, and parameter equality. Reject stale, replayed, altered, or partially validated requests.
- Fail closed and route to an owner. If classification, policy lookup, approval validation, credential issuance, or audit logging fails, do not execute. Send the case to a named human owner and record the reason for the block.
- Record and review. Store enough request, decision, execution, and outcome data for incident investigation and compliance obligations. The appropriate retention period depends on your organization and jurisdiction; no universal period is established by the cited guidance.
What the approval screen must show
- The agent and human user requesting the action.
- The exact tool or API operation.
- The target resource, account, tenant, environment, or recipient.
- All normalized parameters, including filters, quantities, command text, and time ranges.
- Expected impact, data classification, reversibility, and recovery option.
- Why the action was proposed and which policy rule triggered approval.
- Approval expiry, required authentication strength, and any second approver.
Never ask a person to approve a vague statement such as “fix the incident.” The person should be able to understand the concrete operation without trusting the model’s interpretation.
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When an agent must stop and ask for a person
Escalate whenever the operation cannot be safely evaluated or falls outside a preauthorized boundary.
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- The action crosses from read to write, from internal to external, or from a test to a production environment.
- The request affects privileged identities, authentication factors, security policy, or multiple tenants.
- The operation is destructive, irreversible, financially consequential, or difficult to recover.
- The proposed scope is broader than the task or the initiating user’s authority.
- The model receives conflicting instructions, suspected prompt injection, or untrusted tool output.
- The policy service, identity provider, approval record, or audit sink is unavailable.
- The action changed after approval, even if the change appears minor.
- The system cannot prove that a rollback or recovery procedure will work.
Escalation should identify a specific owner and a response path for time-sensitive cases. The cited guidance does not prescribe universal job titles; organizations must map action classes to roles such as incident commander, security administrator, finance approver, or service owner in their own runbooks.
Implement fail-closed behavior
Fail closed means an unavailable or contradictory control produces no side effect. It does not mean silently discarding the request. Return a clear blocked status, preserve the request for investigation, notify the designated owner, and allow a controlled retry after the dependency recovers.
Control failures that must block execution
- No policy rule matches the tool or operation.
- The policy decision cannot be retrieved or is older than its allowed freshness window.
- The approval token is missing, expired, replayed, or bound to different parameters.
- The agent identity or delegated user context cannot be verified.
- Audit logging fails or the event cannot be correlated to the request.
- A connector returns an untrusted or malformed target.
Do not implement a fallback such as “allow if the model is highly confident.” Confidence is not authorization, and it is especially unsafe when a model may be manipulated by prompt injection.
Use short-lived, single-purpose authorization
Issue an authorization artifact for one action or tightly bounded batch, with a short expiry and a unique identifier. Reject reuse after execution. For critical operations, add step-up authentication and an idempotency key so retries cannot duplicate a transfer, deletion, or notification.
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Reference implementation pattern
The following pseudocode illustrates where enforcement belongs. It is intentionally vendor-neutral and omits organization-specific thresholds.
request = agent.propose(tool, target, parameters)
context = identity.resolve(agent_id, user_id, task_id)
normalized = policy.normalize(request)
risk = policy.classify(tool, target, normalized, context)
if risk == "unknown" or not policy.in_scope(context, normalized):
return escalate("unclassified or out-of-scope action")
if not policy.allow_without_approval(risk, context, normalized):
preview = approval.render(tool, target, normalized, risk)
decision = approval.require_human(preview, expires_in="short")
if not decision.valid_for(agent_id, tool, target, normalized):
return escalate("missing, changed, or expired approval")
if not policy.recheck_now(context, tool, target, normalized):
return escalate("execution-time policy check failed")
if not audit.can_record():
return escalate("audit path unavailable")
return executor.run(tool, target, normalized, idempotency_key=decision.id)The executor—not the model runtime—should be the final gate. Every connector and downstream service should enforce its own authorization rather than trusting a value supplied by the agent.
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Monitoring, audit, and recovery
Approval controls are only useful if you can prove what happened. Record the proposed action, policy classification, identity chain, approval decision, normalized parameters, execution result, error or block reason, and timestamps. Protect these records from alteration and correlate them with incident and change-management systems.
Monitor for control bypass
- Execution requests without a corresponding policy decision.
- Repeated attempts with slightly altered parameters after a denial.
- Unexpected tool discovery or connector activation.
- Unusual privilege escalation, data-volume, recipient, or time-of-day patterns.
- Approval tokens reused across targets or tasks.
- Agents that repeatedly reach the escalation path or fail to produce valid previews.
Test the whole path
Threat-model prompt injection, malicious tool output, compromised credentials, policy-service outages, stale approvals, replay, race conditions, and partial failures. Test both single-agent and multi-agent flows; a downstream agent must not inherit authority merely because an upstream agent was approved.
Run regular security assessments and exercises that include forced interruption and rollback. CISA’s May 1, 2026 joint guidance on adopting agentic AI services highlights limited autonomy, layered defense, identity management, oversight, threat modeling, continuous monitoring, and regular security assessments.
Make recovery practical
For each high-impact action, document how to stop it, reverse it, or contain its effects. Use transactions and idempotency where supported. If an operation cannot be reversed, require a higher approval tier and a tested recovery plan before allowing automation.
How current guidance fits together
OWASP’s LLM06:2025 Excessive Agency guidance focuses on preventing overpowered tools, permissions, and autonomy, with authorization enforced downstream. Its security cheat sheet adds previews, explicit approval for high-impact or irreversible operations, audit trails, interruption or rollback, and stronger safeguards for critical actions.
OWASP’s Agent Control Standard page, dated September 1, 2026, describes runtime middleware hooks for declarative policy enforcement and calls for behavior that is inspectable, traceable, and instrumentable. It is a direction for control design, not evidence that any particular implementation has been independently assessed.
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Evaluate an implementation before deployment
Whether you are building middleware or assessing a governance product, use these questions:
- Is authorization checked for every action at execution time, including connector and downstream API calls?
- Can permissions be narrowed by agent, user, task, resource, parameter, and time?
- Does approval bind to normalized parameters, expiry, and the exact actor and target?
- Does the system fail closed when policy, identity, approval, or logging dependencies fail?
- Are audit events complete, tamper-resistant, searchable, and integrated with incident response?
- Can operators interrupt, roll back, or recover from each high-impact operation?
- Are multi-agent delegation and tool-discovery paths subject to the same controls?
A rollout plan for teams
- Inventory capabilities. List every tool, connector, permission, target type, and side effect available to each agent.
- Remove excess authority. Delete unused tools, split broad functions, create agent identities, and replace standing credentials with short-lived task credentials.
- Define local risk tiers. Classify actions by impact, reversibility, sensitivity, and external visibility. Document exceptions and owners.
- Put policy at the execution boundary. Make deny-by-default the behavior for unknown tools, parameters, and targets.
- Build exact previews and approvals. Include normalized operation details, expiry, required authentication, and the approver’s scope.
- Add fail-closed and recovery paths. Exercise outages, stale approvals, replay, partial execution, interruption, and rollback.
- Instrument and review. Monitor decisions and executions, investigate denied or bypass-like patterns, and revise policies as systems and threats change.
Common design mistakes
Relying on the system prompt
A prompt can explain policy but cannot enforce it. A compromised model, injected instruction, or alternate connector can ignore the wording. Enforce in the policy and execution layers.
Approving a category instead of an operation
“Approve email” is too broad. Bind approval to the exact recipients, content or template, attachments, sending identity, and expiry.
Checking only when the plan is created
Permissions, targets, and incident conditions can change between planning and execution. Recheck immediately before the side effect.
Treating logs as optional
If execution continues when the audit sink is unavailable, you lose the evidence needed to investigate a potentially harmful action. Decide explicitly which operations require a durable audit event before execution.
Using universal thresholds
A record count or monetary amount that is safe for one organization may be dangerous for another. Set boundaries from asset criticality, legal obligations, recovery capability, and the people available to approve.
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