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An AI agent ends up with more permissions than its user when it acts through a broadly privileged identity, or when it receives tools and data wider than its task needs. The fix is structural: limit what the agent can reach, carry the user’s authorization scope into every action, and have trusted code, not the model, decide whether each action is allowed.
Why an agent can end up with more authority than its user
An agent’s power is not defined by what it has been told to do. It is defined by the tools it can call, the credentials those tools use, the integrations it is connected to, and the environment it runs in. A model’s stated intention does not limit any of those underlying powers. If a tool can delete records, the agent can delete records, whatever the prompt says.
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The gap usually opens in one of two ways. The first is identity. For convenience, a team may run the agent under a generic, high-privilege service account, so every downstream request carries that account’s rights rather than the rights of the person who asked for the work. The second is scope. Agents are often given a broad toolset “in case” they need it, or allowed to act on high-impact systems without a checkpoint.
OWASP’s LLM06:2025 Excessive Agency page groups these causes into three categories:
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- Excessive functionality: the agent has tools it does not need for its purpose.
- Excessive permissions: a tool or identity has more rights than the task requires.
- Excessive autonomy: the agent can take high-impact actions without independent confirmation.
Any one of these can make an agent more powerful than the person it serves. The three often appear together, which is why a single fix rarely closes the gap.
How to close the gap
The OWASP guidance points toward a single principle that appears in several of its documents: an action should run with the authority of the specific user on whose behalf it is taken, and with the minimum privileges necessary. The steps below turn that principle into a working review.
- Inventory every tool and integration the agent can call. List each tool, the system it reaches, and the identity it uses when it runs. Many gaps are found at this step because the identity is shared and invisible in the agent’s configuration.
- Remove tools that the agent’s purpose does not require. Start from the task and add tools only when a specific workflow needs them. The OWASP AI Agent Security Cheat Sheet recommends applying least privilege to all agent tools and permissions.
- Scope each remaining tool to specific resources and operations. A tool that can read one project folder should not be able to reach the whole drive. Separate read access from write access, and give write-capable paths their own, narrower grant.
- Map the agent’s effective rights to the user’s rights. For each action, the question is whether the requesting user could perform that same action directly. If the agent can do something the user cannot, that is the gap to fix.
- Check authorization in trusted code at execution time. Before a tool runs, application or execution code should confirm the actor and the exact action. A model proposing a tool call is not proof that the call is permitted.
- Gate high-risk actions with explicit, action-specific approval. Sending external email, moving money, changing access rights, and deleting data are typical candidates. Approval should cover the specific action, not a general permission to act.
- Keep the ability to revoke. Each agent should be attributable and revocable on its own, without disabling the human accounts it works alongside.
Identity and credentials
Give the agent its own identity, separate from any developer’s personal credentials. Prefer short-lived, task-scoped tokens over long-lived secrets. Where practical, use separate identities for read-only and write-capable work. This makes agent activity attributable in logs and lets you revoke one agent’s access without affecting anything else.
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Authorization placement
Authorization belongs outside the model’s decision process. OWASP’s guidance is explicit that classifying a tool as available does not grant permission to run it. The model can suggest an action, but the surrounding code must independently verify who is asking, what they are allowed to do, and whether an approval exists for that exact operation.
Intent checks
Evaluate each proposed tool call against the user’s original request. An agent asked to summarize a document should not be sending that document to an outside address. A mismatch between the request and the proposed action is a signal to stop, not to proceed on the model’s reasoning.
Why prompt injection makes the gap more dangerous
Prompt injection can arrive directly from a user or indirectly through external content such as web pages, documents, or email. The OWASP LLM Prompt Injection Prevention Cheat Sheet covers the input-side defenses. The permission question is separate: if an injected instruction succeeds, the damage is limited by what the agent can actually do.
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OWASP’s excessive agency guidance describes a case in which an injected instruction inside an email leads an agent to misuse an email tool. The agent does not need to be “tricked” into anything unusual for this to matter. If the tool has broad authority, a manipulated instruction has broad consequences. Narrow scopes and execution-time checks reduce what a manipulated agent can do, even when the manipulation itself is not caught.
Review checklist for an existing agent
Use this table to check a deployed agent or a vendor design. Each row is a question that exposes a permission gap.
| Review area | Question to ask | Warning sign |
|---|---|---|
| Scope | Which tools, resources, and operations are available? | Tools are enabled “for flexibility” with no task-based justification |
| Read versus write | Are read and write permissions granted separately? | One identity can both read and modify every connected system |
| Identity | Does the agent act under its own attributable identity? | Actions appear in logs under a shared service account or a developer’s name |
| Credentials | Are tokens scoped and short-lived? | Long-lived secrets are stored in agent configuration |
| Enforcement | Does trusted code check the actor and exact operation at execution time? | The model’s output alone determines whether a tool runs |
| Approval | Do high-risk actions require action-specific approval? | A single standing approval covers an entire category of actions |
| Intent | Are proposed actions checked against the user’s original request? | No mechanism exists to compare an action with what the user asked for |
| Revocation | Can one agent’s access be revoked without affecting others? | Revoking the agent requires disabling a human user account |
What the sources establish, and what they do not
The guidance discussed here comes from OWASP’s published documents on agent security, excessive agency, and prompt injection. The following quoted wording is taken from OWASP’s pages:
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- FAST & CONVENIENT LOGIN: Plug in your Security Key NFC via USB-A and tap it, or tap it against your phone (NFC) to authenticate. No batteries, no internet connection, and no extra fees required.
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- OWASP GenAI Security Project, LLM06:2025 Excessive Agency: “Track user authorization and security scope to ensure actions taken on behalf of a user are executed in the context of that specific user, and with the minimum privileges necessary.”
- OWASP AI Agent Security Cheat Sheet: “Apply least privilege to all agent tools and permissions.”
These statements are organizational guidance, not statements by a named individual. The sources do not provide prevalence figures, incident counts, or measured results for how often agents exceed user permissions, so this article does not offer any. The controls above are a synthesis of OWASP’s recommendations and have not been benchmarked against specific products. Teams evaluating a particular platform should check its documentation against the questions in the table above.
The practical starting point is the same regardless of platform: list what the agent can reach, compare that with what the user could do directly, and remove or gate every difference that the task does not justify.
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