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Start with a distinct identity and a defined job
Represent each agent as a separate non-human actor, not as a human administrator whose credentials it can inherit. Assign an accountable owner and record the agent’s purpose, approved tools, and resource boundaries. Separate identities by role or task where that helps prevent one agent’s access from silently expanding to unrelated work.
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This makes it possible to answer basic accountability questions: which agent requested an action, who owns it, and what was it allowed to do? NIST’s 2025 initial public draft, IR 8596, discusses separate permission and authorization policies for AI systems and the use of signed and verified agent assertions or tokens to support provenance checks. Because that document was identified as a draft, check NIST for a later version before treating it as current guidance.
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Define each grant in terms of the agent, tool, operation, resource, context, and approval requirement. For example, an incident-triage agent might be allowed to read specified incident records and query approved telemetry, but not to edit records, disable accounts, or change detection rules. Do not give it write or delete access simply because a connector bundles those capabilities with read access.
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OWASP’s AI Agent Security Cheat Sheet and LLM06:2025 Excessive Agency recommend least privilege, minimum necessary tools, and per-tool scopes such as read-only versus write access and resource-specific permissions. A practical implementation is to deny operations that are not explicitly granted. That deny-by-default policy is a design recommendation based on those principles, not a quoted NIST mandate.
- Scope access to named resources or resource groups instead of broad wildcards.
- Separate read, create, update, delete, administrative, and external-communication operations.
- Limit a grant by relevant context, such as the task or incident for which access was issued.
- Do not let a user message, retrieved document, web page, or API response add permissions.
Enforce authorization outside the model
The model can propose an action; a trusted execution component must decide whether it may happen. Put a policy check in a tool proxy, API gateway, service, or equivalent enforcement point. For every call, check the acting identity, exact operation, target resource, applicable scope, and whether required approval is present. OWASP’s cheat sheet explicitly calls for the execution component to check authorization and approval for the exact action.
Do not treat a prompt, a model-generated risk label, or the agent’s statement that an action is safe as a permission check. A model can misunderstand a request or be influenced by hostile content. The same external enforcement must apply if the agent changes its plan, retries, or reaches the resource through a different tool.
Set autonomy by action risk
Choose autonomy according to the action’s impact and reversibility, not simply the agent’s confidence. The following tiers are an operational design pattern; they are not a universal regulatory classification.
| Action class | Example | Guardrail |
|---|---|---|
| Low impact and reversible | Read an authorized incident record or query approved telemetry | Allow within a narrow, preapproved scope; log the request and outcome. |
| Meaningful change with a recovery path | Update an incident record or change a scoped detection setting | Require the relevant write grant; use a change boundary or approval when policy calls for it; record the before-and-after context where appropriate. |
| High impact, irreversible, administrative, financial, or externally visible | Disable an account, alter broad access policy, delete evidence, or send an external notification | Require independent human approval before execution, bound to the proposed action and target. |
Approval should not be a general “let the agent proceed” switch. Show the reviewer what operation will occur, which resource it affects, and the relevant parameters. If the target or material parameters change after approval, require a new policy evaluation and, where appropriate, a new approval. Prevent bypass through alternate tools, repeated retries, or a modified plan.
Constrain credentials and runtime behavior
Use credentials scoped to the agent’s role, task, and resources. Where the identity platform supports them, prefer bounded or short-lived credentials over persistent broad grants. The appropriate lifetime depends on the platform and task; there is no universal duration established here. Keep secrets out of prompts, model context, and ordinary logs.
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Contain the agent’s ability to amplify mistakes or abuse by setting limits for:
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- Retries and repeated attempts after a denial;
- Tool-chain length, recursion, and concurrent actions;
- Task duration and resource or service cost; and
- Persistent access, including how and by whom it can be revoked.
OWASP recommends limits and cautions against unrestricted tool access. Microsoft’s guidance offers a vendor implementation perspective on agent risk controls, rather than a neutral standard. CISA and partner agencies announced recommendations in 2026 that likewise emphasize limiting autonomy, avoiding broad or unrestricted access to sensitive data and critical systems, and using layered defenses, identity management, and oversight.
Treat external content as untrusted input
Security agents often read attacker-controlled material: emails, incident notes, web pages, documents, tickets, or tool responses. That content may contain instructions intended to redirect the agent, reveal data, or induce a privileged action. Treat it as data to analyze, not as policy or authorization.
- Validate inputs and constrain what the agent can return to tools.
- Keep authorization decisions in the enforcement layer, where retrieved text cannot change grants.
- Apply the same permission and approval checks to actions suggested by tool output as to actions suggested directly by a user.
- Test whether malicious content can cause unauthorized tool calls, data disclosure, or approval bypass.
Log decisions and make access reviewable
For consequential actions, retain structured records that let an operator reconstruct what happened without exposing credentials or unnecessary sensitive content. Useful fields include:
- Agent identity and accountable owner;
- Requested tool, operation, target resource, and relevant parameters;
- Policy outcome, including a denial reason where available;
- Approval identity and the action the approval covered; and
- Execution result, including failure or partial completion.
Monitor for anomalies such as repeated denied calls, unusual targets, unexpected tool sequences, or activity outside the agent’s intended task. Review grants when the owner, purpose, tools, or integrations change, and revoke access that is no longer needed. Protect logs so they do not become a source of credential leakage or sensitive-data exposure. OWASP, NIST’s draft profile, and Microsoft’s vendor guidance address monitoring, accountability, or identity controls in this area.
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Test the connected system, not only the prompt. Include cases where the model is asked to exceed its scope, where a connector exposes more privileges than the task needs, and where untrusted content attempts to redirect it. Confirm that enforcement and approval cannot be sidestepped through another tool or a multi-step chain.
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- Attempt an ungranted operation and verify the execution boundary denies it.
- Attempt to access an out-of-scope resource using an otherwise permitted tool.
- Supply a malicious document or tool response and verify it cannot alter permissions or suppress required approval.
- Change the target or material parameters after an approval and verify policy is checked again.
- Exercise retry, chaining, recursion, duration, and cost limits, including repeated denied actions.
- Review the resulting logs for attribution, policy outcome, approval binding, execution result, and sensitive-data leakage.
Repeat these tests after material changes to prompts, tools, memory, retrieval sources, or model providers. OWASP recommends structured adversarial testing and retesting after such changes; testing can reveal weaknesses, but it does not by itself prove a control will be effective in every production situation.
Compare designs by their enforcement signals
| Area | Safer design signal | Weak design signal |
|---|---|---|
| Enforcement location | A trusted proxy, API, or service checks the exact action at runtime. | The model is expected to obey a prompt or self-declared risk score. |
| Permission granularity | Per-agent, per-tool, operation, and resource scopes. | Shared human credentials or broad wildcard access. |
| Approval | Policy requires approval at a defined high-impact boundary and binds it to the proposed action. | The agent decides whether approval is needed or can retry through another tool. |
| Identity and accountability | Distinct agent identity, attributable owner, and records of decisions and actions. | Shared identity, unclear ownership, or incomplete action records. |
| Containment | Bounded retries, tool chains, duration, and cost, with revocable access. | Unbounded loops and persistent broad grants. |
| Input handling | External content is validated as data and cannot change authorization. | Retrieved text or tool output can silently change goals or privileges. |
Account for guidance limits
OWASP’s AI Agent Security Cheat Sheet is a living document, so consult its current text when adopting a control. NIST IR 8596 was identified as an initial public draft from 2025; verify whether a later version has been issued before citing it as current. These sources and the 2026 CISA announcement provide control guidance, not measured proof that a particular design or product prevents unauthorized actions. They also do not establish jurisdiction-specific legal duties or confirm that any particular product implements the controls effectively.
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