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An AI agent that can read and send email may turn a malicious instruction hidden in an incoming message into a data leak. The risk is not simply that a system is called an “agent”; it comes from the tools it can use, the permissions those tools carry, and how freely it can act. Give an agent only the authority its task needs, enforce access rules outside the model, and require specific approval before consequential actions.
What does it mean for an AI agent to have too much power?
OWASP calls the vulnerability Excessive Agency. It describes three common ways an agent can be overpowered:
- Excessive functionality: the agent has tools or features the task does not require.
- Excessive permissions: those tools can reach more data or perform more operations than necessary.
- Excessive autonomy: the agent can proceed without a person reviewing important steps.
Unexpected, ambiguous, or manipulated model output becomes a security problem when connected systems can carry out the resulting actions. A prompt telling the model to “never send confidential information” does not prevent a mail tool or downstream service from sending it. Authorization must be checked by the execution layer or the system that receives the request.
How can an agent be manipulated into using its tools?
An agent may read content that is not trustworthy, including email, files, or webpages. That content can contain instructions intended to redirect the agent. NIST describes this as agent hijacking: malicious instructions embedded in data exploit weak separation between trusted instructions and untrusted content. See NIST’s discussion of agent hijacking evaluations.
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For example, an agent asked to summarize a mailbox might encounter a message that tells it to forward other messages to an external address. The message is data, not an authorization grant. Yet if the agent has broad mailbox access and permission to send externally, the toolchain may allow the action unless an independent control blocks it.
How much access should an AI agent have?
Start by documenting what each agent can do, what each tool enables, and which identity and resources sit behind it. NIST’s taxonomy groups tools across perception, reasoning, analysis, resource management, and actions such as computer use, code execution, software extensions, physical extensions, and human interaction. It is a way to reason about capability, not a universal risk score. NIST’s tool-use article was released August 5, 2025 and updated August 7, 2025: Lessons Learned from the Consortium: Tool Use in Agent Systems.
| Access level | What it allows | Questions to ask |
|---|---|---|
| Read-only | Retrieve or inspect data without changing it. | Which data can it read, and is that scope limited to the task? |
| Constrained write | Make changes within defined limits, such as a narrow operation or approved target. | Are the permitted targets, parameters, and effects enforced outside the model? |
| Write | Make changes without the same narrow constraints. | Could it send externally, execute code, alter important records, or cause hard-to-reverse effects? |
NIST distinguishes these access levels in trusted and untrusted environments. The practical risk depends on deployment conditions and how the tool is actually constrained, not just its label.
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Build a capability inventory
For every agent and tool, record the operation it enables, downstream resources, credential identity, whether the environment or content is trusted, and whether it can change state or communicate externally. Also assess data sensitivity, reversibility, credential lifetime and scope, independent approval, auditability, and sandbox and network-egress boundaries. These dimensions help compare workflows; they are not a standardized scoring formula.
How do you reduce an agent’s authority?
Reduce access in layers rather than relying on the model to choose correctly. OWASP recommends minimizing extensions and permissions, using narrow operations where possible, and validating authorization for each request in the downstream system. See OWASP’s LLM06:2025 guidance on Excessive Agency.
- Remove tools the task does not need. Prefer a specific operation over an open-ended shell or URL tool when that operation will do.
- Split broad extensions into narrowly scoped functions, and expose only the functions needed for the task.
- Use read-only access when changes are unnecessary; restrict write access to task-specific resources and operations.
- Use a dedicated agent identity rather than a person’s account or shared administrative credentials.
- Issue scoped, short-lived credentials; separate read-only and write-capable identities, and revoke unused or expired access.
- Make the downstream service or execution component enforce the actor’s permissions on every request. A model’s promise or a prompt instruction is not an authorization check.
OWASP’s AI Agent Security Cheat Sheet also recommends separating decision-making from execution and independently validating scope, privilege, and approval for high-impact actions.
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How should you contain agent execution?
Run tools in a sandbox or isolated, disposable environment where appropriate. Limit filesystem mounts and network egress, and keep production credentials out of the agent environment. Isolation limits the damage possible if untrusted content manipulates the agent. OWASP warns that permission prompts are not a security boundary against a manipulated agent; the actual controls must restrict what the execution environment and downstream services permit.
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Coverage varies by implementation: an operating-system sandbox may not constrain every file tool or MCP server connected to the agent. Verify the boundary for each tool and the resources it can reach rather than assuming one sandbox setting covers the whole workflow. OWASP’s AI Agent and MCP Security guidance discusses identities, permission policies, credentials, and sandboxing.
When should an agent need human approval?
Set the approval boundary according to the consequence of an action. Reading data is different from writing it; reversible changes differ from irreversible ones; internal actions differ from externally visible actions. Financial, administrative, destructive, or externally communicated actions generally warrant stronger controls than low-impact, reversible work.
Approval should authorize one concrete action, not grant blanket permission to an agent. Bind it to the tool, target, parameters, actor, and a limited time window. Independently check the action’s scope and privilege, use short-lived authorization artifacts, and fail closed if policy, approval, or audit checks fail. Where possible, use idempotency controls to reduce the chance that a retry repeats an effect. OWASP details these safeguards in its AI Agent Security Cheat Sheet.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How do you monitor and test the controls?
Log agent actions with enough detail to identify the agent identity, tool, target, and outcome. Monitor for unexpected activity and use rate limits to constrain damage. OWASP notes that logging, monitoring, and rate limiting can help detect or limit undesirable actions, but they do not replace least privilege or downstream authorization.
Evaluate the actual task and deployment, including untrusted inputs and the tools the agent can reach. NIST CAISI advises adaptive, task-specific evaluations and testing across multiple attempts. Its article describes testing with Claude 3.5 Sonnet, so those test details should not be treated as universal performance results for other models: Strengthening AI Agent Hijacking Evaluations.
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Use test cases that check whether the agent can access out-of-scope data, perform a write without required approval, communicate externally when prohibited, or act on instructions embedded in untrusted content. An evaluation only covers the threats and setup it tests. Repeat it when models, tools, permissions, or workflows change, and verify that rejected actions fail closed rather than succeeding through an alternate path.
A practical review checklist
- Is every tool necessary, and is each operation narrower than a general-purpose alternative?
- Are data access and write permissions limited to the task’s resources?
- Does each agent use an attributable identity with scoped, short-lived credentials?
- Do downstream systems independently authorize every action?
- Are untrusted content, filesystem access, code execution, and network egress contained?
- Do high-impact actions require approval bound to the exact action and time window?
- Are actions logged and monitored, and are controls tested across relevant attack scenarios?
OWASP summarizes the principle as: “The guiding principle is least agency: give an agent only the autonomy, tools, and access its task requires, for only as long as it needs them.”
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