Imagine a mail-reading agent opens a hostile email containing instructions to forward confidential messages, then tries to send one. This is an illustrative attack path—not a reported incident—but it shows why “I’ll ask first” in the model’s prompt is not a security control. The application that executes each tool call must independently decide whether that exact action is authorized.
Why an AI agent can act before you approve
An AI agent is more than a model producing text. It combines a model with software scaffolding that can read information, plan, call tools, and affect systems outside the conversation. Once it can send email, change code, or use business systems, the central security question is no longer just whether its answer is accurate: it is whether each action is authorized. NIST describes agent systems and tool use in its August 5, 2025 lessons from a consortium.
OWASP describes excessive agency as a combination of three conditions: too much functionality, too much permission, and too much autonomy. An agent may encounter indirect prompt injection in content it reads, make a mistaken inference, or use a compromised extension. If it also has broad write access and can act without a gate, a bad instruction or error can become an external action. OWASP’s LLM06:2025 guidance on Excessive Agency discusses these risks and mitigations.
What a real approval boundary requires
A model’s promise to ask is only text. A real boundary is enforced by the application or tool-execution component, outside the agent’s control. OWASP puts it plainly: “Enforce authorization in the execution component, outside the agent’s context.” See the OWASP AI Agent Security Cheat Sheet.
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For an approval to authorize a consequential action, it should identify the actor and the exact tool, target, and normalized parameters. If the recipient, amount, file, command, or other material detail changes after approval, require approval again. The executor should reject missing, invalid, expired, or reused authorization rather than guessing that the action is acceptable. OWASP recommends exact-action approval records, short-lived authorization artifacts, replay protection, and fail-closed handling for critical actions.
Use explicit gates for actions such as sending messages, deleting data, making payments, deploying software, changing privileges, or otherwise creating an external or security-sensitive effect. An approval summary shown to a person is useful only if the executor verifies that the actual tool call still matches the action they approved.
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Containment controls, layer by layer
Limit capabilities
- Remove tools the task does not need, especially write-capable integrations.
- Prefer narrow functions, such as “create a draft” or “read this ticket,” over open-ended shell, browser, or URL-fetching tools when practical.
- Separate read and write capabilities so that access to information does not automatically include permission to act on it.
Reducing available functionality limits what an agent can do even if it is misled or makes a mistake. OWASP recommends minimizing extensions and permissions in its Excessive Agency guidance.
Constrain identity and scope
- Grant downstream access only to the resources and operations required for the task; use resource-level read and write scopes where available.
- Prefer acting in the user’s authorization context to using a broad shared identity with privileges the user does not have.
- Keep credentials narrow, protected, and revocable; do not expose secrets to the model or an unrestricted tool environment.
A narrowly scoped identity reduces the impact of an unauthorized call. OWASP’s agent security guidance covers least privilege and user-context execution.
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Enforce an independent action policy
- Classify the proposed action at the execution boundary, not by trusting the agent’s own description of its intent.
- Bind any human approval to the actor, tool, target, and exact parameters that will be executed.
- Recheck authorization whenever material parameters change, and fail closed if the check is absent or invalid.
- Require review for actions whose impact is high, external, irreversible, persistent, or security-sensitive.
The policy should govern the actual call, not merely display a reassuring prompt. OWASP’s AI Agent Security Cheat Sheet recommends complete mediation and approval controls.
Isolate coding agents
Sandboxing a coding agent reduces the damage it can cause, but it does not prove that its instructions or proposed changes are safe. OWASP’s LLM Prompt Injection Prevention Cheat Sheet and Secure Coding with AI Cheat Sheet offer guidance for reducing exposure and validating agent-assisted work.
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- Run commands in a restricted shell, development container, virtual machine, or disposable workspace rather than on a broadly trusted host.
- Limit filesystem access to the project and files needed for the task.
- Block unnecessary outbound network access and restrict credentials available inside the environment.
- Review material code, configuration, and dependency changes before they are merged, deployed, or given wider access.
Make actions observable and recoverable
- Log authorization decisions and tool calls, including their targets and outcomes.
- Monitor relevant downstream effects so unexpected sends, changes, or access can be detected.
- Use rate limits where they help contain repeated or high-volume actions.
- Keep a way to revoke credentials, disable a tool, or stop an agent run.
Logging, monitoring, rate limits, and stop mechanisms help detect or limit damage; they do not replace authorization checks before execution. OWASP discusses monitoring and limiting excessive agency in its agent security guidance and Excessive Agency guidance.
Test the controls against adversarial cases
Validate not only the expected workflow but also attack paths: hostile instructions embedded in content the agent reads, tools with broader scope than intended, changed tool definitions, and altered or replayed approval details. Confirm that the execution layer rejects unauthorized calls and that the agent cannot bypass the intended sandbox or credential limits. OWASP recommends adversarial validation in its AI Agent Security Cheat Sheet and Secure Coding with AI Cheat Sheet.
How to choose the approval threshold
There is no single risk label that fits every agent deployment. NIST’s August 5, 2025 report presents workshop-derived taxonomies as approaches teams can tailor, not a universal standard. It points to factors including functionality, access patterns, action risk, reliability, modality, monitoring, and autonomy. In practice, consider what the action can change, where it runs, whether the effects are reversible or persistent, and how visible they will be.
- Lower impact: A well-scoped, reversible action may proceed automatically if policy allows it and the action is logged.
- Higher impact: An external, consequential, irreversible, persistent, or security-sensitive action should receive explicit review before execution.
For platform or deployment comparisons, examine read versus write access and resource scope; user-context identity versus shared privileged credentials; whether approval is enforced outside the model and bound to exact parameters; sandbox, filesystem, and egress controls; logging and downstream visibility; action reversibility and impact; and the quality of adversarial testing.
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