When an AI agent acts without human approval, a bad interpretation or a malicious instruction can become a real change in connected systems. The agent reads or receives information, treats it as a valid instruction, and uses the tools and permissions it has—potentially exposing data, sending messages, deleting files, or changing systems before anyone intervenes. The risk depends not only on how the model reasons, but also on what it is allowed to do and what independent checks stand between its decision and execution.
How an instruction becomes an action
An agent typically receives a goal, reads information such as email or web pages, and may call tools to search, write, send, or modify data. A malicious instruction can be embedded in material the agent is asked to process. If the agent fails to distinguish that untrusted content from the user’s request or developer rules, it may be redirected while appearing to continue the task.
NIST describes this as an agent-hijacking risk rooted in weak separation between trusted instructions and untrusted external data. The agent’s permissions then determine what the redirected system can do. An agent that can only summarize a document has a smaller potential impact than one that can also send email, access cloud files, or administer production systems. NIST CAISI’s evaluation write-up discusses these attack paths and the test scenarios used to examine them.
What can go wrong
Malicious content redirects the agent
A hostile instruction in an email, document, or website may persuade an agent to pursue an attacker’s goal rather than the user’s. In NIST CAISI’s simulated evaluation scenarios, outcomes included downloading and running untrusted code, transferring cloud files to an unknown recipient, and sending phishing messages. These were test scenarios, not reports that those events occurred in deployed products.
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The evaluation also shows why one attempt may not tell the whole story. In a held-out set of Workspace tasks, the strongest attack success rate increased from 11% for the strongest baseline attack to 81% for the strongest new attack developed for the upgraded model. Across five injection tasks, average attack success rose from 57% after one attempt to 80% when each attack was tried 25 times. These figures describe that controlled evaluation’s models, environment, tasks, and attack methods; they are not real-world incident rates or a general failure rate for AI agents. The sources cited here do not establish a representative prevalence rate for incidents caused by agents acting without approval.
It exercises more authority than the task needs
An email summarization task may require inbox read access, but not permission to send or delete messages. If an agent uses a generic privileged identity, it may also reach data beyond the user’s own scope. OWASP treats excessive permissions and excessive autonomy as distinct risk factors: the former expands what the agent can touch, while the latter gives it more latitude to act without review. Its example describes a malicious incoming email inducing an agent to search an inbox and forward sensitive information. OWASP’s Excessive Agency guidance recommends limiting tool capabilities and using user-scoped authorization.
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It makes a destructive or visible change
Deleting data, making a payment, changing permissions, deploying to production, or posting publicly can be costly, difficult to reverse, or visible to others. If a misunderstanding or compromised agent can execute such an action directly, damage may occur before a person sees what happened. Even an action that can technically be undone may leave copies, trigger downstream processes, or affect other users.
It leaks data or sends harmful messages
Read and send permissions together can turn a prompt-injection attempt into disclosure. A misleading or malicious message can also be sent at scale if the agent has broad communication access. Removing a send capability when it is unnecessary, using read-only user authorization, and reviewing outgoing messages reduce this exposure.
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Failures compound across systems or repeated attempts
An agent connected to other agents or services can propagate an error into additional actions. OWASP identifies cascading failures in multi-agent systems and unbounded loops that can consume resources or create denial-of-wallet costs. Rate limits and bounded tool use can constrain these failure paths, but do not replace authorization checks.
Why a confirmation click is not enough
A human approval prompt can help, but it is not a complete security boundary. A vague prompt may hide the actual target or parameters; a user may approve something different from what will execute; and a stolen, reused, or overly broad approval can authorize unintended work. If the model itself is the only component deciding whether approval is needed, a compromised or mistaken model may bypass the safeguard.
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OWASP advises adding controls beyond a simple approval prompt for destructive, financial, administrative, or externally visible actions. An approval should be tied to the specific actor, tool, target, and normalized parameters, with a short expiry and protection against replay. The system carrying out the action should independently verify authorization at execution time, rather than trusting the model’s account of what was approved. OWASP’s AI Agent Security Cheat Sheet details these controls, including audit validation, idempotency where possible, and failing closed when required checks fail.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Which actions deserve human review?
Review should be proportional to impact, reversibility, data sensitivity, external visibility, permission scope, and confidence that the action is authorized. These are practical decision factors drawn from OWASP and NIST guidance, not a universal risk-scoring standard.
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| Action type | Typical handling | Why |
|---|---|---|
| Read-only lookup or summarization within the user’s authorized scope | May proceed without interruption when the tool and data scope are narrow | Usually reversible and does not directly alter or disclose information to others |
| Sending an external message, publishing, or sharing a file | Show the recipient or audience, content, and attachments; require review when disclosure or reputational impact is meaningful | Externally visible and potentially difficult to retract |
| Deletion, payment, permission change, or production deployment | Require explicit approval bound to the exact operation and independently validate it at execution | Potentially destructive, financial, administrative, or high impact |
| Unfamiliar, unusually broad, or out-of-scope action | Stop for review or deny until authorization and scope are established | Uncertainty about intent or authority raises the chance of unintended consequences |
Approvals should be informative: identify what will happen, which tool will do it, what target will be affected, and the parameters that matter. Avoid asking people to approve every routine step. NIST NCCoE’s summary of comments records concern that frequent prompts for ordinary actions can create consent fatigue, making meaningful requests easier to overlook. NIST’s comments summary discusses this concern.
How to reduce the blast radius
- Grant the smallest useful authority. Separate read and write access, scope credentials to the user’s resources, and omit tools the task does not need. A summarizer should not inherit send, delete, or administrative powers by default.
- Put consequential actions behind independent policy checks. A separate policy service or downstream system should verify identity, resource scope, authorization, and approval at execution time. Do not let the model be the sole authority on whether an action is permitted.
- Bind approval to the exact operation. Record the actor, tool, target, parameters, time, and expiry. Use short-lived approvals and replay protection so confirmation cannot be reused for a different action.
- Fail closed when safeguards fail. If authorization, risk classification, approval validation, or required audit logging is unavailable, block the consequential action rather than proceeding by default. Use idempotency where possible to limit duplicate effects.
- Log and limit activity. Keep records of tool calls and outcomes, and set rate limits and bounds on loops or repeated operations to contain runaway activity.
- Test against adaptive attacks. Test malicious instructions embedded in realistic documents, emails, and web content, including repeated attempts. A single successful run or failure does not capture how an agent behaves across retries.
NIST NCCoE describes the broader challenge in its project framing: autonomous software and AI agents may operate with limited human supervision, and the scale and range of their actions can increase substantially. Its Software and AI Agent Identity and Authorization project focuses on the identity and authorization issues that arise as agents take action.
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