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Limit an AI assistant by restricting its tools, data, and credentials; enforce permissions in the connected systems rather than trusting the model to obey instructions; and require approval before high-impact actions such as sending, deleting, spending, or changing access. A prompt that says “do not send email” is not a security boundary if the assistant still has a tool that can send it.
Start with the smallest set of permissions
Give an assistant only the access its task requires. Begin with a deny-by-default policy, then explicitly allow the necessary tools, resources, and operations. Remove unneeded functionality instead of leaving broad tools enabled and relying on instructions to limit their use. OWASP recommends this least-agency approach in its guidance on excessive agency and AI agent and MCP security guidance.
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Inventory what the assistant can reach
Before enabling proactive actions, list every connected app, tool, credential, filesystem location, and network destination. For each, identify whether the assistant needs to read, write, send, delete, or administer. Remove integrations that do not serve the task, and split broad tools into narrower operations where possible.
Do these 3 things before closing this tab:
1Clear out junk files and repair common Windows errors2Fix the driver behind crashes, sound loss and screen glitches3Repair Windows errors before they cause bigger problemsFor example, an assistant that summarizes a mailbox may need permission to read messages but not to send or delete them. These are separate capabilities; granting one should not imply the others.
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Use explicit allowlists
Allow only named tools and appropriate argument ranges. Avoid unrestricted shell access, broad network access, secret locations, and unreviewed integrations unless a specific task requires them. Keep permission settings in reviewable, version-controlled configuration where the product supports it, and apply organizational policy to approved tools. Exact controls and labels vary by product, so check that product’s current permission documentation.
Make the connected system enforce authorization
The assistant should propose actions, not decide whether it is authorized to carry them out. A policy gateway or the downstream service should check every tool request using the agent identity, the user’s authorization context, the target resource, the operation, and the arguments. OWASP’s excessive-agency guidance recommends placing authorization in downstream systems rather than relying on model reasoning.
Keep credentials and identity narrow
Use credentials scoped to the task. A read-only document assistant should use an identity that cannot write or delete. When an assistant acts for an individual, preserve that person’s authorization context instead of using a generic privileged identity that can access everyone’s data. This makes permissions attributable and reduces the damage a mistaken or manipulated request can cause.
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For sensitive API workflows, OpenAI’s cybersecurity checks documentation advises reviewing proposed tool calls against approved scope, denying unauthorized actions, pausing ambiguous or high-risk changes for human approval, enforcing independent filesystem and network boundaries, keeping audit logs, and failing closed if review is unavailable.
Require approval for actions with serious consequences
Decide which operations need a person’s review based on the harm they could cause and how difficult they are to undo. OWASP gives reading documents as a low-risk example and sending email, executing code, deleting a database, and transferring funds as higher-risk examples. Those examples are illustrative; classify actions for your own environment, and do not silently treat unknown operations as low risk. See the OWASP AI Agent Security Cheat Sheet.
Make approval specific and hard to replay
A vague “Are you sure?” prompt gives a reviewer little to assess. Show the exact action, target, and parameters before approval. Bind approval to the actor, tool, target, normalized parameters, time, and expiry so it cannot be reused for a different action or replayed later. For critical operations, use step-up authentication and fail closed if policy or approval validation is unavailable.
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To avoid approval fatigue, safely allowlist and sandbox routine low-risk actions while keeping human review for actions where harm is difficult to reverse. OWASP discusses this balance in its DevSecOps guidance.
Limit the damage from untrusted content and integrations
Emails, websites, documents, and tool descriptions may contain instructions aimed at the assistant. Treat that content as data, not as authorization to expand the assistant’s powers. OWASP describes a malicious email manipulating an assistant with mailbox access into scanning and forwarding messages; read-only mail access and user approval before sending reduce the available path to harm. The example appears in OWASP’s excessive-agency guidance.
Vet extensions and MCP servers
Before connecting an extension or MCP server, establish what code or service will run and what it can access. OWASP recommends using an approved server registry, vetting maintainers and requested permissions, pinning versions, granting minimal scopes, and sandboxing local servers with restricted filesystem and network access. A trusted-looking description is not a substitute for checking the server’s actual access.
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Log actions and contain runaway behavior
Record tool calls, commands, writes, network requests, initiating identity, session, and outcomes or diffs. Keep logs outside the assistant’s control where feasible, and do not record secret values. Alert on unusual credential access, unexpected destinations, bulk reads, new servers, and changes to instruction or CI files. OWASP’s AI agent and MCP guidance covers these monitoring controls.
Set limits on retries, tokens, cost, recursion, and tool chains. These caps do not replace authorization, but they can constrain runaway behavior and give people time to detect it. Maintain an interruption and recovery path appropriate to the system; a log is useful for investigation, but it does not by itself undo a completed action.
Test the boundaries before and after changes
Treat permission rules and approval checks as software controls. Test them before production and after material changes to prompts, tools, memory, retrieval, policies, or providers. Keep regression cases for past failures, and do not release high-risk permission or approval changes without updated tests.
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- Try prompt overrides and requests to use unauthorized tools.
- Test privilege escalation, memory poisoning, and data exfiltration attempts.
- Check recursive tool abuse, approval bypass, and multi-agent chaining.
- Verify that denied requests stay denied when policy review is unavailable.
These abuse cases and testing recommendations are described in the OWASP AI Agent Security Cheat Sheet.
Compare assistant setups by their controls
When choosing an assistant or reviewing its configuration, assess the security boundaries rather than relying on a general claim that it is “safe.” Look for permission granularity at the tool, operation, resource, and argument levels; authorization enforced by a gateway or downstream system; scoped and attributable identities; and approvals that preview and bind to the exact action.
Also check filesystem, network, and code-execution isolation; audit logs and alerts; interruption and recovery options; rate and loop limits; and whether policies and abuse cases can be versioned and regression-tested. NIST NCCoE’s Agentic AI Identity and Authorization project hub describes ongoing work on practical resources in this area. NIST’s February 5, 2026 announcement of a concept paper describes a proposed project, not a finalized agent-specific implementation standard.
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