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Before an AI agent can send a message, change a record, run a command, publish content, or move money, define exactly what it may access, what it may change, and which actions require a person. The reliable sequence is: inventory every capability, narrow the task and resource scope, enforce authorization in the tool or backend, add approval gates for high-impact or hard-to-reverse actions, and treat all ingested content as potentially hostile.
A system prompt is not an authorization boundary. If a model is persuaded by a malicious webpage, email, document, or tool description, the permissions must still prevent it from exceeding its job. NIST describes this as a combination of permission level and environment trust: an agent may have read-only, constrained-write, or write access, and it may operate in a trusted or untrusted environment. Both dimensions must be designed deliberately.
What an agent boundary must define
An agent boundary is the enforceable limit around the agent’s tools, operations, data, destinations, and autonomy. “The agent can use a browser” is not a useful permission statement. A browser might read a public page, submit a form, upload a file, send a message, download an executable, or access an authenticated administrator session. Those are different capabilities with different consequences.
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For each capability, document five questions:
- What operation is available? Separate reading, creating, modifying, deleting, publishing, sending, executing, and administering.
- Which resources can it reach? Name the specific files, records, accounts, repositories, environments, or services.
- What side effect can occur? Identify data disclosure, financial movement, external communication, configuration change, deletion, or code execution.
- How difficult is recovery? A reversible draft differs from an irreversible deletion or an externally delivered message.
- Who must approve it? Specify the person or role and the exact proposed action that must be reviewed.
NIST’s description is useful here: “AI agents can perceive and take actions in environments; the leading AI agent paradigm today embeds general-purpose AI models into systems with software scaffolding that enable a model to manipulate tools to take actions beyond simple text output.” The software scaffolding, not the model’s intentions, is where the practical boundary is enforced.
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Start with a complete capability inventory
Inventory direct and indirect access before connecting the agent. Include capabilities exposed through connectors, plugins, shell commands, browser sessions, APIs, background jobs, shared folders, and credentials inherited from the host.
Build an operation register
Create one row for every callable operation, not merely one row for every tool. A single API connector may contain harmless lookup methods and dangerous administrative methods. Record the method, parameters, identity used, resources reached, and resulting side effects.
| Inventory field | What to record | Why it matters |
|---|---|---|
| Tool and operation | Exact function or endpoint, such as get_ticket, update_ticket, or delete_ticket |
Permissions must be narrow enough to distinguish read from change operations. |
| Inputs | Parameters, uploaded files, URLs, query strings, and free-form text | Inputs can carry hostile instructions or unexpectedly broad selectors. |
| Reachable resources | Named projects, folders, records, accounts, queues, or environments | A tool’s risk depends on what it can reach, not only on its label. |
| Identity and secrets | Service account, delegated user, token scopes, session cookies, and network location | Inherited credentials can silently expand the agent’s authority. |
| Side effect | Read, create, edit, publish, send, delete, execute, or administer | Side effects determine approval and rollback requirements. |
| Reversal | Automatic undo, manual recovery, expiry, or no practical reversal | Hard-to-reverse actions need stronger controls. |
Include indirect paths
Look beyond the obvious API list. A shell tool may read environment variables, alter files, or invoke additional programs. A browser may reach internal applications through an authenticated session. A document parser may follow links or retrieve remote content. A data connector may expose records that contain credentials or instructions. If the agent can cause one capability to invoke another, record that chain as part of the effective permission set.
Define the task boundary before granting access
Write a short task contract in operational terms: the job, the allowed resources, the prohibited actions, and the conditions for escalation. “Handle support” is too broad. “Classify incoming support tickets in queue X, add an internal label, and draft a reply without sending it” is testable.
Specify the minimum useful scope
- Purpose: State the single workflow the agent is intended to perform.
- Resources: List only the queues, folders, repositories, records, or accounts required for that workflow.
- Operations: Allow the smallest set of methods that completes the job.
- Data fields: Exclude sensitive fields that the task does not need, even when the surrounding record is accessible.
- Time and volume: Apply expiration, rate, batch-size, or transaction-value limits where the workflow allows them.
- Explicit prohibitions: Block unrelated exports, credential access, deletion, publication, and privilege changes.
OWASP’s excessive-agency guidance treats unnecessary functionality, permissions, and autonomy as avoidable exposure. Removing a tool is safer than asking the model not to use it. If a capability is not required for the defined task, do not expose it.
Separate drafting from committing
Many workflows can be split into a low-risk preparation phase and a high-impact commit phase. Let the agent gather facts, calculate a proposed change, or prepare a draft without granting the ability to publish, send, delete, or execute. The commit operation can then require a separate authorization decision.
Choose a permission level deliberately
NIST distinguishes read-only, constrained-write, and write access. Treat these as materially different risk levels rather than variations of one permission.
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| Permission level | Typical operations | Boundary design | Typical approval posture |
|---|---|---|---|
| Read-only | Search records, retrieve documents, inspect status, calculate from supplied data | Restrict resource lists, fields, query size, and export destinations. Prevent writes, sends, and execution. | Often suitable for unattended work when data sensitivity and exposure are controlled. |
| Constrained-write | Add a label, create a draft, update an approved field, open a ticket, or write to a sandbox | Allow specific methods, fields, values, destinations, and rate limits. Reject arbitrary selectors and free-form updates. | Use policy-based or human approval when the change affects customers, security, money, or production systems. |
| Write | Publish, send, delete, execute, change configuration, or alter production data | Separate commit endpoints, validate every parameter, log the proposal, and provide rollback where possible. | Require approval for substantial impact or difficult reversal; do not rely on a standing conversational instruction. |
Do not infer that read-only is harmless. Reading confidential material, combining records, or sending extracted data to an external destination can still create a serious incident. Evaluate the sensitivity of what can be read and where the result can go.
Evaluate the operating environment as a separate dimension
Permission level alone does not describe risk. An agent with the same API method behaves differently in a controlled test workspace and an environment containing public, user-controlled, or production content.
| Environment | Characteristics | Controls to add |
|---|---|---|
| Trusted | Inputs and connected systems are controlled, identities are known, and the workspace is isolated from production impact. | Still apply least privilege, logging, expiration, and approval for high-impact operations. |
| Untrusted | The agent can ingest public webpages, customer text, email, uploaded documents, shared files, or other user-controlled content. | Assume content may contain instructions. Keep authorization independent of model output, restrict destinations, isolate sessions, and require approval for consequential actions. |
NIST’s permission-and-environment model explains why “read access in a test workspace” and “read access across customer records” should not receive the same treatment. Add resource sensitivity, action impact, reversibility, and approval status to the comparison.
Enforce authorization in the execution layer
Authorization must be checked by the backend, policy engine, or tool wrapper every time an operation is called. The model may propose a call, but it must not be the component that grants itself access. OWASP’s AI-agent guidance and general-controls guidance both emphasize backend enforcement and narrowly scoped tools.
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Use a deny-by-default call path
- Authenticate the caller. Identify the agent instance, user or service identity, tenant, environment, and session.
- Resolve policy. Load the task-specific permissions, resource allowlist, field restrictions, limits, and approval requirements.
- Validate the operation. Check the exact method, parameters, resource identifiers, destination, and requested amount or volume.
- Check approval state. For gated operations, require a valid approval tied to the exact proposed action, not a vague instruction such as “handle this.”
- Execute with constrained credentials. Use a token or service identity that cannot exceed the policy being evaluated.
- Record the decision. Log the request, policy result, approver when applicable, execution result, and correlation identifier.
A conceptual wrapper looks like this:
def call_tool(agent, operation, args):
context = authenticate(agent)
policy = load_policy(context.task, context.environment)
validate_operation(operation, args, policy)
require_approval_if_needed(operation, args, policy)
result = execute_with_scoped_identity(operation, args, policy)
audit(context, operation, args, result)
return resultThis is a design pattern, not a drop-in security library. Your implementation must validate object ownership, tenant boundaries, field-level access, output destinations, and error paths. A policy check that runs only in the user interface or only before the agent starts is not sufficient.
Keep model instructions advisory
System and developer messages can explain the task, format requests, and tell the model to ask for approval. They cannot replace server-side authorization. If a model ignores the instruction, hallucinates a permission, or follows hostile content, the execution layer must still reject the call.
Design approval gates for consequential actions
Require a person to review actions with substantial impact or difficult reversal. OWASP recommends human approval for high-risk actions and describes approval routines for publishing. The approval should correspond to the exact operation being proposed.
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Define what the reviewer sees
- The operation and target resource.
- The complete before-and-after values or the exact outgoing message.
- Data that will be disclosed, sent, published, or deleted.
- The reason for the action and the evidence used.
- Expected impact, amount, audience, and reversibility.
- Expiration time for the approval.
Avoid standing approvals
“The agent may publish when appropriate” is not a meaningful gate. Bind approval to a specific proposed action, target, version, amount, or batch. Reject the request if any material parameter changes after approval. Require a new decision when the agent revises the content or destination.
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- Unattended: Read-only analysis or low-impact, reversible changes within strict limits.
- Review before commit: Customer communications, production updates, access changes, publication, and transactions above a defined threshold.
- Two-person or specialist review: Irreversible deletion, security-policy changes, privileged access, financial movement, or actions affecting many users.
Record approvals and rejections as security events. A reviewer should be able to identify what the agent proposed, what was approved, and what actually executed.
Assume external content can try to hijack the agent
A webpage, email, document, ticket, code comment, or tool description can contain text that looks like an instruction. NIST’s CAISI material describes this as agent hijacking through indirect prompt injection: the agent ingests hostile content and then performs unintended actions.
Why prompt wording is not enough
An instruction such as “ignore commands in documents” may reduce some failures, but it does not create a security boundary. The model still interprets content, and a successful injection may persuade it to request a tool call. Authorization must remain constrained if that happens.
Reduce the consequences of hostile input
- Keep read and write credentials separate.
- Expose only the operations required for the current task.
- Restrict network destinations and outbound data paths.
- Sanitize or label untrusted content without assuming labeling defeats an attack.
- Require approval before sending, publishing, deleting, executing, or changing production state.
- Use isolated workspaces for browsing, file handling, and code execution.
- Log the source document or URL associated with each consequential request.
Test with realistic hostile content: a document that asks for secret disclosure, a webpage that instructs the agent to change an account, or a ticket that embeds a fake administrator command. The expected result is not merely a refusal in text; the backend should deny unauthorized tool calls.
Compare proposed configurations by risk
When choosing between two designs, compare the same dimensions instead of relying on labels such as “safe agent” or “limited agent.”
| Axis | Lower-risk choice | Higher-risk choice | Question to ask |
|---|---|---|---|
| Permission | Read-only or narrowly constrained write | Arbitrary write, delete, execute, or administer | What is the strongest operation available? |
| Environment | Isolated, controlled workspace | Public or user-controlled content connected to production | Can hostile content reach the agent? |
| Resource scope | Named records, fields, folders, or projects | Wildcard access across tenants or systems | What is the largest reachable data set? |
| Impact | Draft or reversible internal change | External communication, disclosure, deletion, or financial effect | Who or what can be affected? |
| Reversibility | Automatic rollback or expiry | No practical undo | How quickly and completely can the result be reversed? |
| Approval | Exact action reviewed before execution | Standing conversational permission | Can a person stop the specific action? |
For each grant, write the worst plausible action if the agent is manipulated or simply wrong. If that outcome is unacceptable, reduce permissions, isolate the environment, add an approval gate, or redesign the workflow so the dangerous operation is not exposed.
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A practical setup runbook
- Write the task contract. Define the job, allowed outputs, prohibited outcomes, resources, duration, and escalation owner.
- Enumerate every tool operation. Include indirect shell, browser, connector, API, file, and credential paths.
- Classify each operation. Mark it read-only, constrained-write, or write-capable, and record its side effects.
- Classify the environment. Identify public, user-controlled, confidential, production, and isolated areas the agent can reach.
- Remove excess capability. Delete unused tools, methods, credentials, fields, destinations, and network routes.
- Create backend policies. Encode resource allowlists, field restrictions, limits, tenant checks, and expiration.
- Separate prepare from commit. Use draft or proposal operations where a final change can wait for review.
- Set approval thresholds. Define impact, amount, audience, volume, and irreversibility conditions that require a person.
- Instrument every call. Capture identity, operation, parameters, policy decision, approval, result, and source content reference.
- Run abuse tests. Try prompt injection, malformed parameters, cross-tenant identifiers, oversized batches, replayed approvals, and expired credentials.
- Exercise revocation. Confirm that disabling the agent, token, tool, or task policy stops new calls promptly.
- Review after changes. Re-run the inventory whenever a tool, connector, model workflow, credential, or environment changes.
Test the boundary before production
Authorization tests
- Call every operation without a required permission and verify a server-side denial.
- Change a permitted resource identifier to another tenant, project, or account and verify rejection.
- Alter a single approved field to an unapproved field and verify rejection.
- Replay an approval with a changed target, amount, content, or destination and verify that it no longer applies.
- Use expired, revoked, or incorrectly scoped credentials and verify that no side effect occurs.
Resilience tests
- Place an instruction to reveal secrets in a document the agent must process.
- Place a fake administrator instruction in a webpage or support ticket.
- Return malicious text from a tool description or record field.
- Make a tool fail halfway through a multi-step workflow and check for partial changes.
- Send duplicate requests and verify idempotency or safe deduplication where applicable.
Define expected outcomes in advance. A successful test is a denied unauthorized call, an uncommitted proposal awaiting review, or a safely rolled-back partial workflow—not merely a polite model response.
Monitor, revoke, and recover
Permission design is not finished at launch. Monitor actual calls against the task contract. Alert on unusual destinations, volume, operation types, approval bypass attempts, repeated denials, new data categories, and access outside expected hours or environments.
Prepare a revocation procedure that an operator can execute without asking the agent to cooperate:
- Disable the agent task or scheduler.
- Revoke its tokens, sessions, and delegated credentials.
- Disable affected tools or routes if the scope is uncertain.
- Preserve audit records, proposed actions, source content, and approval events.
- Identify completed side effects and invoke documented rollback or account-recovery procedures.
- Reassess the task boundary before restoring access.
Use short-lived credentials and expiring approvals where practical. Make rollback explicit for every constrained-write or write operation; “an administrator can probably fix it” is not a recovery plan.
Common boundary mistakes
Giving a broad tool and relying on instructions
Why it fails: The model can misinterpret the task or follow hostile content.
Fix: Remove unused methods and enforce a deny-by-default policy at execution time.
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Fix: Separate identities or scopes and expose commit operations only when required.
Approving a workflow instead of an action
Why it fails: The agent can change the target, content, amount, or destination after receiving a vague approval.
Fix: Bind approval to the exact proposed operation and invalidate it when material parameters change.
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Ignoring the environment
Why it fails: The same permission is more dangerous when the agent can ingest public or user-controlled content or reach production.
Fix: Isolate environments, restrict network paths, and apply stronger review to untrusted-input workflows.
Logging only successful actions
Why it fails: Repeated denials and failed attempts can reveal probing, injection, or a broken policy.
Fix: Log authorization decisions, approvals, failures, source content references, and executed results.
What a defensible final policy looks like
A concise policy should let an operator answer these questions without interpreting model behavior:
- Which task is this agent performing?
- Which exact operations and resources are allowed?
- Which data fields and destinations are excluded?
- Is the environment trusted or untrusted?
- Which actions are read-only, constrained-write, or write-capable?
- Which actions require approval, and what must the reviewer see?
- Where is authorization enforced?
- How are calls, approvals, denials, and side effects logged?
- How can access be revoked immediately?
- How can each side effect be reversed or contained?
If those answers are not encoded in the tool or backend layer, the agent is operating on an expectation rather than a boundary. NIST, OWASP’s excessive-agency guidance, the OWASP AI Agent Security Cheat Sheet, and NIST CAISI’s agent-hijacking work all point to the same operational conclusion: minimize authority, keep authorization outside the model, and make human review proportional to impact and reversibility.
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