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Why AI Agents Can Be Hacked: Permissions, Prompt Injection, and Tool Access Explained

AI agents can encounter hostile instructions in content they read. Their potential impact depends on tool access, account permissions, and whether consequential actions require approval.

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An AI agent can be manipulated when it treats hostile text in an email, document, or webpage as an instruction—and its tools may let it act on that instruction. The risk depends on two things: what untrusted content the agent reads and what operations its tools and connected accounts are allowed to perform. Prompt-injection defenses therefore need to be paired with narrowly scoped access, authorization checks, and human review for consequential actions.

How prompt injection reaches an AI agent

Prompt injection is an attempt to manipulate a model through crafted input. It can be direct, such as text a user submits, or indirect, embedded in material the system consumes, including websites, documents, and email. OWASP describes both forms in its prompt-injection guidance.

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For an agent, the concern is not only that hostile content could influence an answer. If the system can choose tools and take actions, an injected instruction may lead it to attempt an operation. What it can actually do depends on the functions exposed to it, the permissions of the connected identity, and the authorization enforced by the service receiving the request.

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How reading hostile content can lead to an action

Consider an illustrative email assistant built to summarize messages. If it can also send email, a malicious message could contain text that tries to persuade the agent to send a message or disclose information. The example shows a possible design risk; it is not evidence of a measured real-world incident.

For a summarization task, the assistant generally needs read access, not the ability to send or delete mail. Removing unnecessary functions and using a read-only mail scope can limit what an injected instruction can accomplish. If sending is genuinely part of the task, require the user to review the proposed message before it is sent. OWASP discusses these controls under LLM06:2025, Excessive Agency.

Three ways an agent can have excessive agency

OWASP uses “Excessive Agency” for system designs that give an LLM-enabled application more capability or independence than its task requires. The risk can arise in three separate places:

Excessive functionality: too many tools

A tool may expose operations the task does not need. A summarizer with send and delete functions has more capability than one that can only retrieve and summarize messages. Prefer narrow, task-specific functions over broad operations that can affect many resources.

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Excessive permissions: an overpowered identity

Even a narrowly defined tool can operate through an account with broad access. Scope each connected identity to the minimum data and operations needed; use read-only access when the task only requires reading. Tool design and account permissions are separate controls, so reducing one does not automatically fix the other.

Excessive autonomy: consequential actions without review

An agent may have suitable tools and account scopes yet still be allowed to take high-impact actions on its own. Keep a person in the approval path for operations such as sending or deleting messages when an error or manipulation could have meaningful consequences.

How to assess an agent’s access and safeguards

Use these questions when configuring an agent or evaluating a service that connects to your accounts:

  • Are the available functions necessary? A summarizer may need to retrieve messages but not send or delete them. Remove capabilities that are not required.
  • Are tool functions narrowly defined? Prefer a specific operation for a specific task over an open-ended function with broader effects.
  • Is the connected identity appropriately scoped? Compare read-only with read/write access, and task-specific permissions with broad credentials.
  • Does the downstream service enforce authorization? Access should be checked by the system that owns the resource, for the relevant user and resource—not left to the model’s judgment. OWASP puts it plainly: “Implement authorization in downstream systems rather than relying on an LLM to decide if an action is allowed or not.” See its Excessive Agency mitigations.
  • Which actions require human approval? Identify consequential operations and put review before execution, rather than relying on the model to recognize every risky case.
  • Can an action be reversed? Consider reversibility when deciding which operations can run automatically and which need confirmation.

OWASP’s Prompt Injection Prevention Cheat Sheet treats defenses as layered. Filtering inputs or outputs and separating external content can help, but they do not replace least privilege, tool-call validation, downstream authorization, and review.

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What the available evidence does—and does not—show

The cited OWASP materials provide security guidance and illustrative threat scenarios. They do not establish a representative incident rate or a percentage of deployed agents successfully compromised through prompt injection. The design risks and mitigations are useful without treating an illustrative scenario as a prevalence statistic.

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