The safest way to limit an AI agent is to constrain it in three places before it runs: the identity it uses, the tools and data that identity can reach, and the authorization check that must approve every downstream action. An agent that summarizes files or drafts a reply needs a very different access profile from one that can send email, delete records, buy goods, deploy code, or change production permissions.
Do not treat a prompt such as “be careful” as a security boundary. Give the agent a distinct, accountable identity; expose only narrowly defined tools; scope every credential to the needed resource and operation; require approval for consequential side effects; and keep an audit trail that you can review and revoke.
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Start with the action, not the model
Write down what the agent is supposed to accomplish and classify each possible operation by its consequence and reversibility. Reading a document, preparing a draft, changing a customer record, sending a message, deleting data, purchasing something, deploying software, and changing permissions are not equivalent tasks.
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|---|---|---|
| Search or read approved data | Allow automatically when the resource and purpose are clear | Read access can still expose sensitive information, but it has no direct external side effect. |
| Summarize or classify | Allow with read-only credentials | The agent can produce an output without modifying the source. |
| Create a draft | Allow, but keep the draft separate from sending or publishing | A person or another deterministic control can inspect the proposed content. |
| Update a record | Allow only for named fields and resources, often with a review threshold | Writes can create financial, legal, operational, or privacy consequences. |
| Send, delete, purchase, deploy, or change permissions | Require explicit approval unless a narrowly bounded, low-risk automation is justified | These actions are externally visible, destructive, costly, or difficult to reverse. |
This classification becomes the design input for identity, tools, credentials, policy, and approval. It also prevents a common mistake: granting a broad role because the agent might need one small function later.
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Build least privilege as a layered design
1. Give every agent a recognizable identity and owner
Use a distinct workload or agent identity rather than a shared administrator account. Record the agent’s purpose, business owner, environment, data classification, approved tools, and retirement date. The identity should make it possible to answer “which agent acted, for whom, and under whose responsibility?”
Review effective permissions, not just the role shown in a configuration screen. Permissions can arrive through group membership, inherited resource policies, delegated tokens, service accounts, tool-specific secrets, or a downstream system that trusts a different principal. Microsoft’s identity guidance treats the agent identity, owner, and lifecycle as part of the control plane; the same principle applies outside Microsoft environments.
- Use separate identities for development, testing, staging, and production.
- Assign a named human or team owner who can approve changes and revoke access.
- Store the purpose and allowed operating window as policy metadata.
- Set an expiration or review date instead of granting access indefinitely.
2. Define the smallest useful task and data set
List the exact resources the agent needs: a mailbox folder, a ticket queue, a database view, a storage prefix, or a deployment project. Then list the operations: read, search, create draft, update specific fields, send, delete, or administer. “Access to the CRM” or “access to the repository” is not a sufficient requirement.
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3. Expose narrow tools instead of open-ended extensions
A tool should represent one bounded capability, not a general-purpose shell. A mail summarizer might receive list_messages and read_message_body for one folder, but not send_message, delete_message, or an unrestricted mailbox token. A search function should not inherit write authority merely because the same service account can update the index.
Prefer parameters that identify an allowed resource and operation explicitly. Reject arbitrary URLs, table names, file paths, or query fragments when a fixed allowlist can express the task. If a broad underlying API is unavoidable, place a wrapper in front of it that validates the target, operation, fields, and result size.
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4. Scope credentials to both resource and operation
Use the smallest permission set that can complete the task. Separate read, draft, write, send, delete, and administrative capabilities where practical. A token that can read invoices should not also approve payments; a deployment identity should not be able to alter production access control.
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For user-owned data, delegated access lets the agent act on behalf of a signed-in user while downstream systems enforce that user’s rights. Microsoft’s access-pattern guidance recommends delegated access when possible for this case. For scheduled or background work with no active user, app-only access can be appropriate, but the application permission set should be narrowly scoped. Managed identity is an option for supported Azure workloads; service principals or workload-identity federation may fit other environments. These are platform-specific choices, not universal requirements.
5. Authorize every action downstream
The model must not decide whether its own tool call is permitted. Put a deterministic authorization check immediately before each downstream operation. OWASP’s Gen AI Security Project states: “Implement authorization in downstream systems rather than relying on an LLM to decide if an action is allowed or not.”
At minimum, the policy decision should evaluate:
- the initiating human or upstream principal;
- the agent identity and its owner;
- the named tool and version;
- the target tenant, resource, record, file, or environment;
- the requested operation and fields;
- the credential scope and current policy;
- time, location, risk signals, and any approval token required by policy.
Perform this check for every call, including calls made after a plan has already been approved. A plan approval is not a permanent grant; the target or user’s permissions may have changed before execution.
6. Separate proposals from side effects
Design the normal path as observe, propose, validate, approve, execute. Reads and drafts can usually run without a person waiting. Sending, deleting, purchasing, deploying, changing permissions, or modifying regulated records should pause at an approval gate unless a documented risk assessment supports unattended execution.
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7. Log, review, and revoke
Record the initiating user, agent identity, tool, effective scopes, target, operation, parameters that matter, approval decision, timestamp, and result. Preserve enough context to reconstruct what the agent knew and which policy allowed the call, while filtering secrets and unnecessary personal data from logs.
Review grants periodically and after changes to prompts, tools, models, data sources, or ownership. Test an emergency disable path: stop new runs, invalidate active credentials, revoke delegated consent or application permissions, and confirm that queued jobs cannot continue with stale authority.
Choose the right access pattern
No single architecture is correct for every agent. Compare the options against the task, data ownership, consequence, and ability to revoke.
| Decision | Use when | Trade-off |
|---|---|---|
| Delegated identity | The agent acts for a signed-in user and should inherit that user’s rights to user-owned data. | Access follows the user, but consent, token lifetime, and changing user permissions must be managed. |
| App-only identity | A scheduled or background process must run without a user present. | Reliable for automation, but a mistake affects whatever application permissions were granted, so the scope must be very small. |
| Managed identity | A supported cloud workload needs an identity without embedded secrets. | Reduces secret handling, but its available features and resource coverage depend on the platform. |
| Service principal or workload federation | Other environments need a workload identity or short-lived federated credentials. | Useful across systems, but integration and trust-policy design are environment-specific. |
| Read/draft capability | The task can be completed by preparing information or a proposed change. | Safer and easier to review, but a separate step is needed to commit the change. |
| Write/execute capability | The business process genuinely requires an update or external side effect. | More useful for automation, but it requires stronger policy, approval, monitoring, and rollback. |
| Human-in-the-middle | Each action is consequential, ambiguous, or hard to reverse. | Reduces unattended damage, but reviewers can approve unsafe proposals if they do not verify the details. |
| Agent-only operation | The action is tightly bounded, low impact, reversible, and operationally well tested. | Fast and scalable, but exposed to prompt injection, insecure tool chaining, and error-handling weaknesses. |
| Narrow per-tool grants | Different tools need different resources or operations. | More policy work, but a compromised tool has a smaller blast radius. |
| Broad shared credential | Almost never; only consider temporarily during a controlled migration. | Simple to configure but difficult to attribute, review, or contain. Replace it with separate scoped credentials. |
An implementation sequence you can apply
- Write the task contract. State the trigger, expected output, approved data, allowed tools, prohibited actions, environment, owner, and maximum run duration. Include examples of valid and invalid targets.
- Map resources and operations. For every tool, name the exact resource and whether it may read, create, update, send, delete, or administer. Remove any operation that is not required for the first release.
- Create a separate identity. Use a workload identity or delegated principal appropriate to the environment. Attach an owner, review date, and production/non-production boundary.
- Issue scoped credentials. Grant only the required resource and operation. Prefer short-lived tokens, secretless workload identity, or federation where supported. Do not place long-lived administrator keys in prompts, configuration files, or tool responses.
- Wrap and validate tools. Define fixed schemas for arguments. Validate resource identifiers, allowed fields, maximum result sizes, destination domains, and environment names before making the downstream call.
- Insert a policy decision before execution. Check the user, tenant, agent, tool, target, operation, current scope, and required approval. Deny by default when a value is missing or ambiguous.
- Add the approval gate. Route sensitive operations to a reviewer with an exact preview. Bind approval to one target and one operation, expire it quickly, and require reauthorization if the request changes.
- Log and alert. Capture identity context, effective scope, action, target, result, and approval. Alert on unusual destinations, volume, privilege escalation, repeated denials, or a tool calling another tool outside its normal chain.
- Test revocation and failure. Disable the agent, revoke its credentials, remove a user’s permission, make the target unavailable, and simulate malformed or injected instructions. Confirm that the operation stops safely and that partial work is recoverable.
- Review before expanding. Compare observed use with the task contract. Remove unused scopes and tools; do not expand access simply because the model requested it.
Concrete designs for common agents
Mail summarizer
Give it read access to a named folder or mailbox view and permission to create a draft in a separate location. Do not grant send or delete. If a user later asks it to send a message, create a draft, display the recipients and body, and require a fresh authorization check plus explicit approval at send time.
Support-ticket assistant
Allow reading tickets assigned to the user’s queue and drafting a reply using approved knowledge sources. Limit updates to a small set of fields such as tags or internal notes. Keep customer-visible replies, refunds, account closure, and export of personal data behind separate tools and approval policies.
File-analysis agent
Mount a read-only workspace containing only the selected files. Block arbitrary network access, path traversal, and writes to the source directory. If the agent must create an output file, write to a separate staging area and scan or review it before publication.
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Deployment assistant
Let the agent inspect build results and propose a release. Use a deployment identity that targets one project and environment, not the entire organization. Require approval for production, restrict the artifact and change set, and keep a rollback path. A successful staging deployment should not automatically confer production authority.
Treat retrieved content as untrusted input
Files, web pages, emails, tickets, and user-provided text can contain instructions designed to manipulate the agent. Treat those instructions as data unless a trusted policy explicitly says otherwise. Prompt injection can still influence planning even when tools are well designed; least privilege limits the damage but does not make injection impossible.
- Keep system policy and tool authorization outside retrieved text.
- Mark untrusted content in the agent context and prevent it from redefining roles or approval rules.
- Require a fresh policy check after the agent changes target, recipient, amount, or operation.
- Prevent tool output from silently becoming executable instructions for another tool.
- Use allowlists for destinations, file paths, commands, and data classifications.
Approval is useful, but not a substitute for policy
Google Cloud describes a human-in-the-middle mode in which an agent proposes an action and a person approves each action, and an agent-only mode in which execution proceeds without waiting. The latter depends heavily on programming quality and is exposed to prompt injection, insecure tool chaining, and weak error handling. Human review also has a limitation: a person may approve a malicious or destructive proposal without checking the exact target.
Make approval meaningful by reducing reviewer fatigue. Batch only equivalent low-risk changes, show a diff rather than a vague summary, identify the data source, and reject requests with missing context. For high-impact actions, use two-person approval or a separate control owner. Rate limits and monitoring can reduce the size or speed of damage, but OWASP characterizes them as damage-limiting measures, not replacements for authorization.
Audit and revocation details that are often missed
Log effective authority
Logging only the configured role is misleading. Capture the permissions actually used, including delegated user, application scope, resource policy, approval identifier, and tool version. Record denials as well as successes; repeated denied calls can reveal a prompt-injection attempt or an incorrectly scoped workflow.
Revoke in layers
An emergency stop should disable the scheduler or agent runtime, revoke active tokens and API keys, remove application consent or role assignments, and block the downstream service account. Check queues, retries, and cached credentials. A disabled chat interface is not enough if a background worker can still submit jobs.
Test the negative path
Verify that the agent cannot read a neighboring tenant, access an unapproved folder, change a field outside its schema, send to an unapproved domain, or continue after the initiating user loses access. Test malformed arguments, timeouts, partial failures, duplicate requests, and a tool returning hostile instructions.
Platform guidance and standards status
Microsoft’s published guidance distinguishes delegated access from app-only access and describes managed identities and other workload identities as environment-dependent implementation choices. Microsoft Entra Agent ID is a platform example, not a requirement for every deployment; confirm current capabilities and licensing in the environment where you operate.
Google Cloud documentation uses the human-in-the-middle and agent-only distinction for agent workflows and warns about prompt injection and insecure tool chaining. Its agent identity features and Vertex AI Agent Engine controls are relevant only when they match your architecture and platform.
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Common mistakes and fixes
| Mistake | What goes wrong | Fix |
|---|---|---|
| Relying on a system prompt to enforce permissions | The model can misinterpret instructions or be manipulated by content. | Enforce authorization in the downstream service for every operation. |
| Giving one token access to read, write, send, and delete | A compromised plan can reach every capability. | Split capabilities and issue per-tool, per-resource scopes. |
| Using an administrator account for convenience | Attribution and containment become difficult. | Create a dedicated identity with an owner and a narrow role. |
| Approving a whole session | Later calls can target a different resource or operation. | Bind approval to one exact action, target, and short expiration. |
| Ignoring inherited permissions | The effective access is broader than the visible configuration. | Inspect group, tenant, resource, delegated, and tool-level grants. |
| Logging only successful actions | Suspicious probing and policy failures disappear from review. | Log denials, identity context, and scope evaluation as well as successes. |
| Forgetting queued work during revocation | Retries continue after the agent is supposedly disabled. | Cancel queued jobs, invalidate tokens, and verify downstream rejection. |
Pre-launch checklist
- The agent has a distinct identity, named owner, purpose, environment, and review date.
- The task contract lists approved resources and exact operations.
- Read, draft, write, send, delete, and administrative capabilities are separated where practical.
- Credentials are scoped to the smallest useful resource and operation.
- Delegated versus app-only authority is an intentional decision.
- Every downstream action performs a deterministic authorization check.
- Consequential actions show an exact preview and require an appropriately bound approval.
- Retrieved content is treated as untrusted and cannot redefine policy.
- Logs capture agent, user, tool, scope, target, operation, approval, and result.
- Disabling the agent and revoking credentials have been tested, including queued and retried work.
- Unused grants are removed after observing real usage.
The practical rule
Let an agent read and draft broadly enough to be useful, but make every ability to change the outside world a separate, explicit capability. Identity establishes who is accountable, tool design limits what can be requested, downstream authorization decides whether the request is allowed, approval adds human judgment for high-impact actions, and logging plus revocation limits the consequences when something goes wrong. That layered arrangement is more dependable than trusting the model, a prompt, or a single product feature to police itself.
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