Authorize an LLM agent’s tool call in trusted code or the downstream service—not in the model’s reasoning. At execution time, check who is acting, what operation is requested, which resource it affects, and whether policy permits it. Give each agent only the capabilities it needs, preserve the user’s permissions when acting on their behalf, and require independent approval for high-impact actions.
Why tool authorization must sit outside the model
An agent can propose a tool call, but it cannot safely grant itself permission to make that call. A system prompt, model-generated risk label, or tool-discovery result is not an authorization decision: the execution boundary must verify the actual action against policy before anything happens.
OWASP’s LLM06:2025 guidance puts the principle plainly: “Implement authorization in downstream systems rather than relying on an LLM to decide if an action is allowed or not.” This protects the system even when the model is mistaken, manipulated, or operating on hostile content.
Tool availability and permission are separate. A tool may be visible to the model so it can determine whether it is relevant; the runtime still needs to deny the call unless the authenticated actor is permitted to perform that exact operation on that resource.
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What a runtime authorization decision should check
Evaluate each proposed action at the trusted tool boundary or in the service that carries it out. A useful policy decision considers all of these elements together:
- Principal: The authenticated user, service, or other identity on whose behalf the action is being taken.
- Tool and operation: The specific capability and action, such as reading or updating a record.
- Resource: The particular account, file, record, or other target within the principal’s permitted scope.
- Policy outcome: Whether that combination is allowed, denied, or requires approval before execution.
Deny by default when the requested action falls outside the defined scope. Do not treat missing identity, ambiguous targets, or an unrecognized operation as permission. The authorization check must apply to the action actually executed, not merely to a broad description supplied by the model.
Limit capabilities and resource scope
Start with the task and expose only the tools it requires. Prefer narrow operations over broad interfaces such as a general-purpose shell, unrestricted database credential, or API surface that combines unrelated powers. Separate read from write access, restrict which resources each tool can reach, and use different tool sets for different trust levels.
These limits should be enforced by the tool implementation or downstream service, not only by hiding tools from the model. If a read-only task has access to a write-capable credential, prompt wording does not remove that capability. Likewise, a tool restricted to one resource should not accept an arbitrary resource identifier and rely on the model to choose safely.
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Preserve the user’s identity and permissions
When an agent acts for a user, make the authorization decision in that user’s context where applicable. A broad agent or connector service identity must not silently grant access beyond what the user is allowed to do. Keep clear which principal is making the request, how that principal authenticated, and what scope was granted.
For connectors and MCP deployments, document the acting principal and the granted tool and resource scopes. Review how those scopes are added or changed rather than assuming that an initially narrow grant will remain narrow. OWASP’s excessive-agency guidance and MCP Top 10 both point to authorization and scope control as important safeguards.
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Require independent approval for high-impact actions
Identify actions with financial, administrative, destructive, privacy-sensitive, or externally visible consequences. Put an approval gate in the tool extension or downstream service before the action executes. The agent must not be able to bypass that gate by changing its reasoning or issuing a differently worded request.
Approval supplements authorization; it does not replace it. An approver should see enough detail to understand the specific proposed operation and its target. A user’s approval cannot make an action valid if the user or agent lacks the underlying permission, and an authorized action may still need approval because of its impact.
Treat ingested content and tool output as untrusted
Indirect prompt injection happens when hostile instructions are embedded in material an agent reads, such as an email, webpage, or document. NIST describes agent hijacking as indirect prompt injection through ingested data that can lead to unintended harmful actions. The user need not have supplied the malicious instruction directly.
Input filtering and prompt instructions can help manage risk, but they are not an authorization boundary. Segregate and validate untrusted inputs as appropriate, and continue checking every resulting tool action against policy after the model has interpreted the content. Apply the same caution to tool output: retrieved content should not be allowed to redefine permissions or skip execution checks.
Review MCP authentication, authorization, and scope
For MCP servers, make authentication and authorization explicit rather than assuming that connecting a server is sufficient control. Review which principal is represented, which tools and resources are exposed, what scope each grant carries, and how scope changes are approved and audited.
OWASP’s MCP Top 10 identifies insufficient authentication and authorization, privilege escalation through scope creep, and command injection as risks. Review command construction and permission expansion paths alongside the initial access configuration; a correctly authenticated connection can still be over-privileged or vulnerable to unsafe command handling.
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Compare designs by enforcement, identity, and scope
Use these questions to assess an authorization design, whether it is built into an application or supported by a service. They are evaluation criteria, not a vendor ranking.
| Dimension | What to verify |
|---|---|
| Enforcement point | Is permission checked in trusted code or downstream, or is it only suggested in prompts? |
| Granularity | Can access vary by tool, operation, resource, and read/write behavior? |
| Identity binding | Does execution preserve the requesting user’s identity and actual permissions? |
| High-impact gate | Can policy require approval before a specific sensitive action executes? |
| Untrusted-input resilience | Do tool boundaries continue enforcing policy when content or tool output contains malicious instructions? |
| Scope management | Are grants reviewable, and are changes controlled to resist scope creep? |
Practical implementation sequence
- Inventory actions and impact. List the tools an agent can call, the operations each exposes, the resources they can affect, and which actions have high-impact consequences.
- Define principals and scopes. Decide whose identity applies to each call and specify the minimum task-relevant tool, operation, and resource permissions.
- Enforce at execution. Add a trusted authorization check at the tool boundary or downstream service. Check the exact principal, operation, and resource; deny when the action is outside scope.
- Add approval gates. Put approval before execution for designated high-impact actions, with the specific action details presented to the approver.
- Review connector changes. For MCP and other integrations, inspect authentication, authorization, resource scope, command construction, and how permissions expand over time.
Common authorization failures to avoid
- Trusting the model to police itself: A prompt asking the agent not to perform an action does not prevent an execution component from carrying it out.
- Equating discovery with access: A listed or callable tool is not automatically an authorized tool call.
- Using one broad identity for everyone: A service credential can exceed the permissions of the user the agent is meant to represent.
- Approving a vague intent: Approval should concern a specific operation and target, not merely the general task.
- Relying on input filtering alone: Filtering cannot replace authorization after an agent interprets content or tool output.
- Ignoring permission drift: Connector grants and MCP scopes need review when tools, resources, or permissions change.
These practices align with OWASP’s AI Agent Security Cheat Sheet, LLM06:2025 excessive-agency guidance, OWASP MCP Top 10, and NIST’s discussion of agent hijacking. Their taxonomies and guidance may evolve, so consult the current versions when setting policy.
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