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Prevent unauthorized changes by combining several controls rather than trusting an agent’s instructions. Give each agent a separate, auditable identity; begin with read-only, task-scoped permissions; allow only the files, commands, tools, data sources and network destinations required for the current job; and run the agent in a sandbox without production or long-lived credentials. Enforce authorization outside the model, pause irreversible or high-impact actions for an independent human approval, record every tool call and resulting diff, and maintain a tested way to revoke access and stop the agent. This layered design limits blast radius even when an agent is confused, compromised or manipulated by hostile input.
What does it mean for an AI agent to make an unauthorized change?
An unauthorized change is any write, deletion, deployment, permission alteration, message, purchase, network connection or other side effect that falls outside the task the owner approved. The agent might act on a legitimate request but still exceed its scope, or it might be tricked by content it reads. A safe design therefore checks both who is acting and what action is permitted at the moment it is attempted.
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Model instructions are useful for explaining intent, but they are not an access-control system. The U.S. Department of Energy’s GEAR guidance puts this plainly: "A prompt such as ‘never delete files’ is not an access control." The enforcement point must be an operating system, application, API gateway, scheduler, database or policy engine that can deny the operation even when the model proposes it.
Which controls provide the strongest protection?
Use defense in depth. Each layer addresses a different failure mode, so a mistake in one layer does not automatically become a production incident.
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| Control | What it limits | Recommended default |
|---|---|---|
| Identity and least privilege | Which resources and actions an agent can reach | Unique identity, named owner, task-scoped role, read-only first |
| External authorization | Whether a specific operation is allowed | Deny by default; explicit allowlists; fail closed |
| Sandbox and egress boundaries | Damage if the agent or a tool is compromised | Disposable workspace, no production secrets, restricted outbound network |
| Approval gates | High-impact or irreversible side effects | Independent human approval showing exact command and arguments |
| Monitoring and recovery | Detection, investigation and containment time | External immutable logs, anomaly alerts, tested revocation and rollback |
OWASP’s DevSecOps guidance summarizes the authorization posture as "Start from deny and allow explicitly." Treat that as the baseline for every tool, file path, API method and destination, not merely as a setting in the agent interface.
How do I give an agent a safe identity and minimum permissions?
Create a dedicated identity for each agent or workflow, with a named human owner and an audit trail. Do not reuse a developer’s personal account or a broad service account. A separate identity lets you attribute every action, revoke the agent without disabling a person, and review its effective permissions across downstream systems.
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Define the smallest role that can complete the current task. A documentation agent may read a repository and write to a generated-docs directory, but it does not need permission to change application code, create users or deploy. A test-fixing agent may edit a feature branch and run a bounded test command, while the merge and deployment rights remain elsewhere.
- Prefer read-only access for discovery, analysis and planning.
- Separate read, write, destructive, network and administrative capabilities instead of combining them in one role.
- Restrict file access to named directories or repositories; do not expose a home directory, cloud drive or entire filesystem by default.
- Limit commands and arguments with an allowlist where the platform supports it.
- Review effective permissions in every downstream system, including storage, source control, package registries, databases and cloud APIs.
Make credentials short-lived
Use ephemeral tokens or credentials that expire when the task ends. If an agent needs temporary elevation, issue it for one operation or short session, record the approver and scope, then revoke it immediately. Static credentials increase the damage from prompt injection, a compromised tool or an abandoned workspace.
Separate identities by environment
Development, staging and production should use different identities and policy boundaries. An agent that can edit a development branch should not inherit a production deployment token. If a workflow must promote an artifact, make promotion a separate, approved action with its own identity rather than extending the original agent’s privileges.
How can I make an AI agent read-only?
Read-only operation requires enforcement at every path that could write, not a sentence in the system prompt. Remove write and delete permissions from the agent identity, mount its workspace read-only where possible, and configure tools to expose read methods without their mutation counterparts.
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- Create a separate read-only identity. Grant it read access to the specific repository, data set or ticket queue. Do not attach a role that contains write permissions even if the interface hides those buttons.
- Use a narrow workspace. Copy or check out only the files needed for analysis. Avoid mounting credentials, configuration directories, sockets or a user’s home directory.
- Disable mutation tools. Remove file-write, delete, shell, deployment, messaging and administrative tools unless the task explicitly requires one. Where a tool cannot be removed, place an enforcing policy in front of it.
- Block write-capable APIs. At the API gateway or service layer, deny methods that create, update, delete, merge, deploy or change permissions. The denial must apply even if the model calls the endpoint directly.
- Test the boundary. Ask the agent to perform a harmless write in a disposable workspace and verify that the operating system or service returns a denial. Check logs to confirm the attempt was recorded.
- Keep a controlled handoff. Export the agent’s proposed patch, query or plan for a human or separate automation to review. Do not quietly convert a read-only session into a write session.
Read-only does not mean risk-free: bulk reads can expose sensitive data, and an agent can still make network requests or send information through an allowed channel. Apply data minimization and egress controls as well as write restrictions.
Where should authorization be enforced?
Put the decision at the layer that owns the resource. Filesystem permissions should protect files, the source-control service should protect branches, the deployment system should protect releases, and the API gateway or database should protect records. The agent can request an action, but an independent policy layer decides whether it is allowed.
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Fail closed when review is unavailable
If the policy service, approval queue or identity provider is unavailable, deny the high-impact operation rather than allowing it through. Queue the request with its context for later review. OpenAI cybersecurity guidance emphasizes denying unauthorized actions, pausing ambiguous or high-risk changes for human approval, enforcing independent filesystem and network boundaries, keeping audit logs and failing closed when review is unavailable.
Show the exact operation
Authorization should evaluate the concrete resource and arguments, not a vague label such as “deploy.” A useful approval request identifies the repository, branch, files, command, arguments, destination, data volume and expected diff. If those details change after approval, require a new decision.
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How do sandboxing and network controls reduce blast radius?
Run agents in a dev container, disposable virtual machine or equivalent hosted isolation boundary. The environment should contain only the task workspace and deliberately supplied dependencies. Destroy it after the session when practical, or reset it from a known image before reuse.
Keep secrets out of the sandbox
- Do not mount production credentials, browser profiles, SSH keys, cloud metadata endpoints or broad secret stores.
- Pass a narrowly scoped, short-lived token only when a task requires it.
- Mask secrets in command output and logs; never include secret values in approval records.
- Use separate test data instead of live customer or production data.
Control outbound traffic
Deny outbound connections by default and allow only named destinations and ports required by the task. A build might need a package mirror, while a code review normally needs no network access. Record each destination and alert when the agent requests a new one. Understand the boundary: a sandbox that restricts shell commands may not restrict file tools, plugins or MCP servers, and a network filter may not prevent data exfiltration through an otherwise permitted service.
Pin dependencies and tools
Pin versions of agent tools, plugins, MCP servers and project dependencies, and review updates before enabling them. A changing tool description or dependency can alter what the agent is encouraged or able to do. Keep the image and policy configuration under version control so a reviewer can see changes.
Which actions should require a human approval?
Require an independent person to approve any action that is irreversible, externally visible, costly or capable of expanding privileges. The person approving must not be the same agent that proposed or executed the change.
- Pushes to protected branches, merges and releases
- Deployments, infrastructure changes and production migrations
- Deletion, overwriting or bulk modification of files and records
- Permission, role, credential or policy changes
- Spending, purchases, refunds or quota increases
- Sending messages, publishing content or contacting customers
- Installing software, changing system configuration or resetting services
- Connecting to a new network destination or data source
The approval screen should show the exact command and arguments, affected resources, proposed diff, actor identity, requested duration and rollback plan. A broad approval such as “let it handle the rest” defeats the control. If the agent changes its plan or generates a different diff after approval, stop and request approval again.
Can prompt injection bypass an agent’s rules?
Yes. An agent can encounter hostile instructions in an issue, pull request, web page, log, dependency file, agent instruction file or tool description. The content may tell it to reveal secrets, alter its task or call a dangerous tool. Do not rely on the model to recognize every manipulation; permissions and isolation must limit what happens if it follows the injected instruction.
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Treat instructions as data until authorized
Separate trusted policy from untrusted content. Pin and review instruction files and MCP servers, define which repositories or pages may supply instructions, and prevent untrusted text from changing the system-level policy. A document that says “ignore previous rules” should be treated as text to analyze, not as a command to execute.
Reduce the value of a successful attack
- Use read-only identities for browsing and triage.
- Keep secrets and production network paths outside the workspace.
- Require approval for every high-impact tool call, regardless of the reason supplied by the model.
- Log the source content that led to a tool request so investigators can trace the injection.
- Limit bulk reads, credential-file access and unusual destinations with alerts or automatic denials.
What should an audit log record?
Send logs to a system outside the agent’s control so it cannot rewrite its history. Record enough context to reconstruct the decision without copying secret values.
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- Model or workflow version and tool or plugin version
- Timestamp, requested action, full arguments and target resource
- Policy decision, approver identity and approval scope or expiry
- Network destination and data-transfer metadata
- Resulting diff, status code, error and rollback reference
- Credential issuance, elevation, revocation and policy changes
Protect logs with append-only or immutable storage and restrict who can delete or alter them. Redact tokens, passwords, personal data and proprietary content. Configure alerts for credential-file access, unexpected destinations, bulk reads, privilege drift, instruction-file changes, unusual deletion and attempts to disable or delete logging.
How do I revoke an agent quickly?
Prepare a kill switch before granting write access. It should disable the agent identity, invalidate active tokens, block network egress, stop running jobs and prevent queued actions from executing. Test the sequence rather than assuming that deleting a process also invalidates cloud sessions or downstream credentials.
Test recovery scenarios
- Disable the agent identity and confirm that new API and repository requests fail.
- Rotate or invalidate every credential the workflow could have received.
- Remove temporary roles and verify that effective permissions have returned to the baseline.
- Stop the sandbox or worker and quarantine its artifacts and logs for investigation.
- Restore a known-good version or revert the specific diff using a separate, authorized operator.
- Review the audit trail, identify the first unauthorized action and update the policy or tool configuration before re-enabling the workflow.
Revocation should be independent of the agent itself. An agent that is malfunctioning or compromised must not be able to veto, delay or approve its own shutdown.
Which protection approach should I choose?
The following comparison uses the practical axes that matter when selecting a control baseline. A prompt-only approach is not sufficient for production-impacting work; stronger options add operational effort but contain failures more reliably.
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| Approach | Authorization strength | Blast-radius containment | Permission granularity | Approval coverage | Credential lifetime | Network control | Audit and revocation | Operational overhead |
|---|---|---|---|---|---|---|---|---|
| Prompt instruction only | Model instruction; bypassable | None | Broad or unclear | Usually none | Often static | Often open | Incomplete; slow to revoke | Low initially, high incident risk |
| Workspace sandbox with external policy | Enforced by OS or service policy | Narrow workspace | Task-scoped allowlist | High-impact actions can pause | Short-lived preferred | Allowlisted destinations | Central logs and tested disablement | Moderate |
| Disposable VM plus external policy and approvals | Enforced at multiple layers | Strong isolation and reset | Fine-grained files, tools and APIs | Required for irreversible actions | Ephemeral | Deny by default, explicit egress | Immutable logs, rapid revocation and rollback | Highest |
Choose the strongest boundary justified by the data and side effects. A read-only documentation task may fit a workspace sandbox, while an agent that can alter infrastructure or handle sensitive records warrants disposable isolation, strict egress and mandatory approvals.
What is a practical rollout sequence?
Introduce controls in an order that exposes hidden dependencies before the agent receives powerful credentials.
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- Inventory the workflow. List every agent, model, tool, plugin, data source, owner and downstream permission. Include indirect access through repositories, package managers, databases and cloud roles.
- Write an action policy. Categorize operations as read, write, destructive, network or administrative. Define which resources are in scope, which are denied and which require a person.
- Start read-only. Use a narrow workspace with no production credentials. Capture proposed patches, commands and API calls without executing mutations.
- Add explicit allowlists. Permit only named files, commands, APIs, data sets and destinations. Keep denied operations visible in logs so missing scope can be corrected deliberately.
- Gate high-impact actions. Require an independent approval for pushes, merges, deployments, deletion, overwriting, permission changes, spending, messaging, software installation and new destinations.
- Deploy isolation and egress controls. Use a disposable container or VM, deny outbound traffic by default, and pin tool and dependency versions.
- Centralize monitoring. Send immutable audit records outside the agent’s environment and configure alerts for anomalous access, privilege drift and attempts to disable controls.
- Exercise revocation and recovery. Disable identities, rotate credentials, remove stale permissions and restore a known-good state in a scheduled test.
- Re-review after change. Repeat the assessment whenever the workflow, tool, data scope, model, policy or execution environment changes.
How do I troubleshoot common safety failures?
The agent modified files outside the task directory
Remove broad filesystem mounts, inspect effective OS permissions and add a path allowlist at the file-service or container layer. Review the audit trail for the first out-of-scope request, then recreate the workspace from a clean image before another run.
The agent accessed a credential file
Revoke and rotate the exposed credential immediately, even if logs show no subsequent use. Remove the file from the workspace, block credential directories, and add an alert for future access attempts. Do not assume prompt instructions will prevent recurrence.
An approval was granted but the resulting change differed
Make approvals bind to a content hash, exact diff or exact command and arguments. If any material field changes, invalidate the approval and require a new review. Preserve both versions in the audit record.
The agent cannot complete a legitimate task under least privilege
Keep the denial, identify the precise missing resource or operation and issue the smallest temporary permission needed. Set an expiry, record the approver and remove the elevation when the task ends. Never solve repeated denials by attaching a broad administrator role.
Logs are missing or can be deleted
Move logging to an external, append-only system and deny the agent access to its retention and deletion controls. Treat a logging outage as a policy failure: pause high-impact actions until records are flowing again.
What should a secure agent policy say?
A useful written policy is specific enough for an enforcement system and an auditor to test. Include:
- The agent’s owner, purpose, identity and approved environments
- Allowed repositories, directories, data sets, tools, commands, APIs and network destinations
- Explicitly denied resources and operations
- Read, write, destructive, network and administrative classifications
- Actions requiring independent approval and the information the approver must see
- Credential issue, expiry, elevation and revocation rules
- Logging fields, retention, redaction and alert thresholds
- Kill-switch procedure, rollback owner and recovery test schedule
- Review triggers, including model, tool, dependency, workflow or data-scope changes
Keep the policy outside the model prompt and make the enforcement configuration traceable to the written rules. The prompt can explain the mission and ask the agent to behave cautiously; the policy must remain authoritative when the two conflict.
How should teams judge whether the controls are working?
Run safe, repeatable exercises rather than relying on a successful demonstration. Attempt denied writes, out-of-scope reads, new network connections, privilege changes and log deletion in a disposable environment. Confirm that the request is blocked, the event is logged, an alert is generated when appropriate and revocation works without agent cooperation.
Review near misses as seriously as incidents. A blocked request to delete a directory, access a token or contact an unapproved host reveals where an agent’s plan or tool set is broader than intended. Tighten the allowlist or redesign the workflow instead of merely telling the model to be more careful.
The goal is not a guarantee that an agent will never make a mistake. It is a system in which an incorrect or manipulated decision is denied, contained, visible and recoverable before it becomes an unauthorized change.
Frequently Asked Questions
Can an AI agent safely work without internet access?
Often, yes. Run the task with outbound traffic denied and provide a reviewed local package mirror or preloaded dependencies when builds require them. If a new destination becomes necessary, treat it as a separate, approval-gated change and record the host and purpose.
Should agent instruction files be trusted because they are in the repository?
No. Repository instructions, issue text and pull-request content can be modified by contributors or injected through dependencies. Pin and review trusted instruction files, keep them separate from untrusted content, and enforce permissions independently of what those files say.
How frequently should agent credentials be rotated?
Use credentials that expire with the session or task, and revoke them immediately after any temporary elevation. Rotate or invalidate them at once after suspected exposure; a fixed calendar interval cannot replace event-driven revocation and scope checks.
What should happen if the approval service is offline?
High-impact actions should stop and remain queued with their context. Allowing the operation during an outage creates an implicit approval path, so the policy should fail closed until an authorized reviewer and the audit system are available.
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Define reversibility in operational terms: a tested rollback, preserved data, bounded impact and a known recovery owner. If restoring the prior state depends on uncertain backups, external communication or unavailable staff, classify the action as high impact and require approval.
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