Giving an AI agent access to security tools lets its output trigger actions in connected systems. If the agent is misled by hostile data, makes a mistake, or misinterprets its task, the outcome can range from exposing information to changing or deleting data. Risk depends on the tools, permissions, reachable systems, and whether consequential actions require separate authorization.
How tool access turns an AI error into a security event
A tool-connected agent can do more than produce text: it can call functions that read data, change system state, or communicate with other services. Its practical authority is therefore set not just by the model, but by the functions exposed to it, the identity behind those functions, and the resources that identity can reach. OWASP notes that excessive agency can affect confidentiality, integrity, and availability depending on the systems an application can interact with: OWASP LLM08: Excessive Agency.
This does not mean every agent integration is equally dangerous. A read-only assistant limited to a particular dataset has a different risk profile from an agent with broad credentials, shell access, and permission to make changes without review.
What can go wrong
Indirect prompt injection can hijack the task
An agent may ingest untrusted content—such as an email, file, or website—that contains instructions intended to redirect it. NIST calls this agent hijacking through indirect prompt injection. The hostile instructions may be embedded in data the agent was asked to inspect, rather than typed directly by the user.
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In evaluation scenarios, NIST’s Center for AI Standards and Innovation (CAISI) considered objectives including using command-line access to download and run a program from an untrusted URL, exfiltrating cloud files, and sending phishing emails. These are examples of attack objectives, not evidence of how often they succeed in production. CAISI’s technical staff describe the underlying weakness as a failure to separate trusted instructions from untrusted data: “AI agent hijacking is the latest incarnation of an age-old computer security problem that arises when a system lacks a clear separation between trusted internal instructions and untrusted external data — and is therefore vulnerable to attacks in which hackers provide data that contains malicious instructions designed to trick the system.” Read the full explanation in NIST CAISI’s January 17, 2025 technical blog.
Excessive functionality gives the agent unnecessary options
A tool may expose more operations than the task requires. OWASP gives the example of an agent asked to read documents while its plugin also allows them to be modified or deleted. Open-ended shell or command functions create a broader action space than a narrowly defined operation.
Broad credentials can turn a narrow tool into a powerful one
A tool’s description does not limit the authority of the identity it uses. OWASP describes a read-oriented database integration whose credentials also permit updates, inserts, and deletions, and a user-facing integration that instead connects through a generic privileged identity able to access other users’ files. In either case, a mistaken or manipulated call can reach beyond the intended task unless the downstream system enforces the right user, resource, and operation scope.
Too much autonomy can complete harmful actions
If an agent can act without independent validation, a mistaken or manipulated output may become a real change. OWASP’s examples include deletion without user confirmation and recommend human review before sending a message or publishing a post. The same principle applies when security tooling can change systems, affect accounts, or expose sensitive information.
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Secrets, integrations, and logs can become exposure paths
Tool calls and their outputs can involve sensitive data; credentials and protocol logs can also create exposure risks. OWASP’s living MCP Top 10 identifies concerns including token mismanagement and secret exposure, tool poisoning, software supply-chain attacks, command injection, insufficient authentication and authorization, and inadequate audit telemetry. Tool definitions, dependencies, returned data, credentials, and logs all belong inside the security boundary.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What determines the level of risk?
NIST’s 2025 tool-use taxonomy distinguishes read-only, constrained-write, and write access, and considers whether an agent operates in a trusted setting or consumes untrusted resources such as the open internet. Those labels are a useful starting point, not a complete risk score. Assess the whole deployment:
- Permission level: Can the agent only read, make specific constrained changes, or write without meaningful limits?
- Identity and resource scope: Which user, repository, account, dataset, host, or tenant can the tool identity reach?
- Function scope: Does the agent have typed, task-specific operations, or open-ended shell, code-execution, or command functions?
- Action impact and reversibility: Does a call merely retrieve information, or can it change state, delete or publish data, or create a difficult-to-reverse result?
- Environment and inputs: Does the agent handle trusted material only, or can it read untrusted websites, files, or messages?
- Oversight and visibility: Are high-impact actions approved separately, and can investigators audit tool calls and changes to the agent’s context?
NIST’s taxonomy includes examples such as deep research, browser use, and computer use in untrusted environments. See NIST’s August 2025 lessons on tool use in agent systems. NIST also notes that risks can arise from adversarial data, insecure or poisoned models, and harmful actions without an adversary, such as specification gaming or misaligned objectives. No single failure is inevitable, and no one control removes every risk; the consequences depend on what the deployment can reach. See NIST CAISI’s request for information about securing AI agent systems.
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How to reduce the risk
- Expose only necessary tools. Remove functions the workflow does not need, and prefer specific operations over open-ended commands.
- Start with read-only access. Add only narrowly scoped write functions that the task requires, rather than granting general write access.
- Use task-appropriate identities. Bind actions to the relevant user or service identity and restrict downstream access to the required resources and operations. Avoid generic, high-privilege credentials.
- Enforce authorization at the action boundary. The downstream service or tool should check each request against policy independently; do not make the model the authority that decides whether an operation is permitted.
- Require human approval for high-impact actions. Place approval at the tool or downstream API boundary for consequential operations such as deletion, publication, or significant system changes.
- Constrain and monitor runtime access. Limit what the agent can reach and observe its access while it runs. NIST identifies deployment interventions to limit and monitor agent access as an area for security work.
- Keep auditable records. Record the agent identity, tool calls, authorization decisions, and relevant context changes. NIST NCCoE highlights identity, authorization, auditing, and non-repudiation in its February 5, 2026 concept-paper announcement; OWASP also flags missing audit telemetry as a concern.
- Test the workflow as it changes. Use task-specific evaluations that reflect the tools, data, and permissions in the actual deployment. CAISI says evaluations should adapt as systems change; task-specific performance and multiple attempts can help assess hijacking risk. An individual evaluation result is not a universal safety guarantee.
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