The Tool Desk
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This design limits the damage from mistakes, compromised connectors, and prompt injection. The practical pattern is a dedicated agent identity, deny-by-default tool and file access, task-scoped credentials, isolated execution, controlled network egress, action-specific approval, and logs stored outside the agent’s reach.
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What least privilege means for an AI agent
Least privilege is an enforced boundary around what an agent may read, change, execute, and send. A support agent might read tickets and a knowledge base, but have no access to payroll files, private keys, production databases, or outbound email. A coding agent might edit a checked-out repository and run tests in a disposable workspace, but not alter production infrastructure or read a developer’s home directory.
The boundary must be evaluated at the point of use. OWASP’s AI Agent Security Cheat Sheet and LLM Prompt Injection Prevention Cheat Sheet both emphasize that authorization belongs in trusted execution code, not in model reasoning. A prompt can ask an agent to “only use the reports folder,” but it cannot stop a tool from opening another path if the tool itself is over-permissioned.
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Use four questions for every capability:
- What resource? Name the specific path, record set, API object, mailbox, repository, or tenant.
- What operation? Separate read, create, update, delete, publish/send, and administration.
- Who and which session? Bind the grant to the initiating human, agent identity, tenant, and current task.
- For how long and through which route? Prefer short-lived credentials and make the same policy cover shell commands, file tools, MCP servers, connectors, and network egress.
A useful test is to imagine the model fully compromised. If it followed malicious instructions from a web page or tool result, the permitted blast radius should still be small.
Start by defining the task boundary
Write the job in operational terms before selecting an agent framework. List the exact files, applications, data fields, destinations, and actions needed for a successful run. Remove capabilities that are merely convenient. Split capabilities by risk so a read-only task does not inherit write or administrative tools.
| Action class | Examples | Typical control |
|---|---|---|
| Read | Open approved documents, query selected records, inspect build logs | Allowlisted resources with read-only permission |
| Write | Edit a draft, create a ticket, update a staging record | Separate write tool, constrained fields and paths |
| Delete | Remove files, close records, purge data | Explicit policy and action-specific human approval |
| Publish or send | Send an email, post publicly, deploy a release | Exact destination and arguments shown for approval |
| Administer | Change permissions, create credentials, alter production settings | Keep outside the normal agent role or require a separate, tightly controlled workflow |
Use separate tool sets for different trust levels. For example, a document summarizer can receive a search-and-read interface that returns selected fields, while a records-maintenance agent receives a different interface that can update only approved status fields. Avoid a universal “manage everything” tool whose behavior depends on the model choosing safe arguments.
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Create a dedicated identity and preserve delegation limits
Give the agent a service identity, bot account, or workload identity rather than a developer’s personal account. Keep it out of administrator roles. A dedicated identity makes every action attributable and lets you revoke the agent without disabling a person’s access.
When a human starts a task, carry the initiating user, tenant, session, and task identifier into the authorization decision. Delegation must attenuate permissions: an agent may receive a subset of the user’s grant, never a broader one. If a user can read one project, the agent should not gain access to every project simply because its service account has a larger role.
Check these properties before enabling delegation:
- The agent identity is independently revocable.
- Policies can distinguish user, tenant, session, resource, operation, and task.
- A delegated token cannot be exchanged for a broader role.
- Logs record both the agent and the human who initiated the action.
NIST describes the feasibility of this approach in Back to the Future: Why Agentic AI Needs a Strong Identity Foundation: “the ability to implement essential pre-requisites – such as dynamic, tightly scoped, audience-restricted tokens and credentials – exists today.”
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Restrict files and tools with deny-by-default policy
Begin with no file or tool access, then add explicit allow rules. A file policy should name approved directories and operations rather than granting access to a home directory or an entire disk. Exclude credential stores, private keys, environment files, shell history, browser profiles, source repositories unrelated to the task, and operating-system configuration.
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One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware matchPrefer a narrow file API over unrestricted shell access. If shell execution is unavoidable, expose an allowlist of commands with fixed argument rules, run as a low-privilege operating-system user, and block command substitution or path traversal where those features are not required. Validate canonicalized paths so an encoded ../ or symlink cannot escape the permitted directory.
A practical policy for a report-generation task might allow:
- Read access to
/work/input/reports/. - Write access only to
/work/output/. - No access to
/home/, credential files, private keys, or environment files. - Only the approved parser and renderer commands, with fixed input and output directories.
Do not assume that a container or application sandbox automatically governs every connector. Verify whether the same restriction covers built-in file tools, shell tools, MCP servers, plugins, and remote APIs. OWASP’s AI Agent and MCP Security guidance warns that enforcement coverage can vary between execution paths.
Scope app permissions and keep standing secrets away from the model
Choose the narrowest application scope and resource-level permission available. Separate read-only identities from write-capable identities. If an agent only needs calendar availability, do not grant full mailbox access; if it updates a project board, limit it to that board and the fields it must change.
Prefer a trusted token broker or connector that obtains credentials for the current task. The model should receive a capability to invoke the connector, not the underlying production secret. Do not put persistent tokens in prompts, configuration files, process environments, shell history, transcripts, or ordinary logs. Redact secret values from error messages and tool responses.
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Short-lived, audience-restricted credentials reduce the time and places in which a stolen token is useful. Bind a token to the intended service, resource, operation, user, and task when the platform supports those claims. Revoke it when the task ends or when the agent identity is disabled. A secrets manager alone is not sufficient: it reduces exposure only when the issued scope, caller binding, policy, and egress controls are correct.
Isolate execution and control network egress
For agents that execute code or commands, use a disposable container, virtual machine, or equivalent sandbox. Remove host filesystem mounts and sensitive environment variables. Run as a low-privilege user and destroy the environment after the task when persistence is unnecessary.
Disable network access by default. If the task needs an API, allowlist the exact destination, protocol, and operation. DNS, proxies, package managers, browser automation, and secondary services can create alternate routes, so verify every path through which data could leave. A sandbox that blocks shell networking but leaves an unrestricted connector available does not provide complete containment.
Treat an MCP server as code or a remote service, not as a trusted description. Review the permissions it receives, pin versions, restrict its filesystem and network access, and monitor changes. OWASP’s Agentic AI AAI8: Insufficient Sandboxing describes tool execution as a threat boundary; the same principle applies to plugins and hosted connectors.
Make approval useful at consequential boundaries
Require human approval for hard-to-reverse actions: deleting data, sending external messages, deploying code, changing permissions, creating credentials, or spending money. The approval screen should show the exact tool, resource, destination, and arguments, not a vague message such as “the agent wants to continue.” Record the approver and the approved parameters, then reject any later call that differs from them.
Do not ask for a click on every harmless operation. Repeated prompts create approval fatigue and can train users to approve automatically, a risk discussed in the NIST identity guidance. Safely pre-authorize low-risk reads and bounded transformations with enforced allowlists; reserve interactive approval for genuine decision points. An approval prompt is not a substitute for policy or isolation: a manipulated model could still cause harm between prompts if the underlying tools are unrestricted.
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Log actions outside the agent’s control
Send audit records to a central system the agent cannot modify or delete. At minimum, capture:
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- Tool name, exact parameters, resource, operation, and policy decision.
- Outcome, error, files written, records changed, and network destinations.
- Approval request, displayed arguments, approver, and approval result.
Redact tokens, passwords, private keys, and sensitive payloads. Retain enough metadata to reconstruct what happened without copying entire confidential documents into the log. Alert on credential-file access, bulk reads, unfamiliar destinations, new MCP servers, privilege changes, and modifications to agent policy.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Test both allowed and denied behavior
A least-privilege design is incomplete until its boundaries are tested. Use harmless fixtures and instrumented tools to verify that legitimate calls succeed and forbidden calls fail before reaching the target system.
- Test a permitted read, write, and (where applicable) send operation.
- Attempt a path outside the allowlist, including traversal, symlink, and alternate encoding variants.
- Attempt a forbidden operation with an otherwise valid identity, such as deleting when only reading is allowed.
- Try to use an expired, wrong-audience, or different-user token.
- Attempt to reach an unapproved network destination through shell, browser, package manager, MCP, and connector routes.
- Place direct instructions and indirect prompt injection in a document, web page, email, tool result, and tool description; confirm that downstream authorization still denies unsafe actions.
- Verify that logs contain the identity, arguments, decision, and outcome without secret values.
OWASP’s prompt-injection guidance recommends treating external content as data and validating downstream actions. A test that only checks what the model says, rather than what the tool gateway permits, does not demonstrate authorization.
Compare implementation choices by the boundary they enforce
Different products and platforms expose different permission keys. Compare the controls below rather than assuming that a feature labeled “agent security” covers every route.
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1Clear out junk files and repair common Windows errors2Scan for outdated or missing drivers - takes under a minute3Repair Windows errors before they cause bigger problems| Decision area | Strong implementation | Questions to verify |
|---|---|---|
| Scope granularity | Policy distinguishes resource, operation, user, session, tenant, and task. | Can one tool call be limited to one record, path, or project? |
| Credential lifetime and delegation | Short-lived, audience-restricted tokens are attenuated during delegation and independently revocable. | Can a delegated agent ever obtain a broader grant than the initiator? |
| Boundary coverage | The same policy and sandbox cover shell, file tools, MCP servers, connectors, and egress. | Which execution paths bypass the sandbox or use separate credentials? |
| Approval quality | Approvers see exact arguments, while low-risk operations use enforced pre-authorization. | Can a changed argument reuse an earlier approval? |
| Auditability | Logs are attributable, centrally retained, protected from agent modification, and secret-redacted. | Can investigators connect an action to both the agent and initiating human? |
A practical rollout sequence
- Write the task contract. State the goal, approved resources, operations, destinations, maximum duration, and explicit exclusions.
- Classify every action. Mark each capability as read, write, delete, publish/send, or administer. Remove capabilities not required for completion.
- Create the identity. Provision a dedicated non-administrator service identity and define how the initiating user, tenant, session, and task are carried into policy checks.
- Build the tool gateway. Start with deny-all rules, expose narrow schemas, validate every argument, and reject calls outside the resource and operation allowlists.
- Issue task credentials. Use a broker or connector to mint short-lived, audience-restricted credentials. Keep raw secrets out of prompts, environments, configuration, transcripts, and logs.
- Deploy an isolated runtime. Remove unnecessary mounts and variables, run as a low-privilege user, and block network access except for explicitly required destinations.
- Add approvals. Require exact-argument approval for destructive, external, financial, deployment, and permission-changing actions. Pre-authorize only bounded low-risk work.
- Centralize telemetry. Record identity, session, tool, parameters, decision, outcome, writes, destinations, and approvals outside the agent’s control.
- Run boundary tests. Exercise allowed calls, denied calls, expired credentials, traversal attempts, alternate routes, and direct or indirect injection fixtures.
- Review after changes. Reassess permissions when tools, MCP servers, prompts, connectors, models, or task definitions change. Revoke unused identities and credentials.
Common failure modes and fixes
The prompt says “do not open secrets,” but the agent can read them
Cause: The file tool or service account has broad access. Fix: Remove the permission at the filesystem, gateway, or identity layer and test a denied call. Prompt wording can remain as guidance, but it is not the control.
A container is isolated, yet data still leaves
Cause: An unrestricted connector, proxy, DNS path, mounted socket, or MCP server bypasses the intended network boundary. Fix: inventory every tool route, remove unnecessary mounts and sockets, default-deny egress, and allowlist destinations at the point where traffic is enforced.
Delegation gives the agent more access than the user
Cause: The agent service account’s role is used without intersecting it with the initiating user’s grant. Fix: compute the effective permission as the permitted subset of both identities, bound to the current tenant, session, and task.
Users approve everything
Cause: Approval is requested for routine, low-risk actions or hides the exact parameters. Fix: pre-authorize bounded reads and transformations, display precise arguments for consequential actions, and make approvals single-use for those arguments.
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Logs expose the credentials they are meant to protect
Cause: Raw headers, environment dumps, tool payloads, or exception traces are retained. Fix: redact at the logger and connector, test redaction with synthetic secrets, and store only the metadata needed for investigation.
Bottom line: enforce the boundary where the action happens
An AI agent should receive the smallest task-scoped capability that can complete its job: a dedicated identity, allowlisted resources and operations, short-lived credentials, isolated execution, restricted egress, and approval for irreversible effects. Put those checks in the tool gateway, operating system, identity provider, and sandbox, then verify them with denied-action tests and tamper-resistant logs. If malicious content changes the model’s plan, the enforced boundary—not the model’s good intentions—should determine what actually happens.
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