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This checklist is a practical baseline for developers, engineering leads and security teams. Product defaults differ, so verify the selected agent and operating system before deployment.
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Start with a permission map, not a single “allow” switch
An agent’s authority is a combination of filesystem, process, network, credential and approval permissions. Treat each as a separate control. An agent that can read a repository may still be unable to modify it; an agent that can edit source may not need package-install or deployment rights.
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|---|---|---|
| Filesystem | Read the task repository; write only the working tree or explicitly named subdirectories | Limits accidental edits and exposure of unrelated files |
| Execution | Run approved tests, formatters and build commands; block administrative commands | Commands can alter the host even when source changes look harmless |
| Network | Off by default; permit only approved destinations when required | Prevents data exfiltration and untrusted downloads |
| Credentials | No broad secrets; use short-lived, scoped access through a broker or proxy | Generated code can read anything available to its environment |
| Approval | Pause for external, destructive, elevated or ambiguous operations | Keeps consequential decisions under human control |
| Audit | Record prompts, decisions, tool calls, results and network outcomes | Enables investigation and policy improvement |
OpenAI describes the sandbox as the technical boundary for where an agent can write, whether it can reach the network and which paths remain protected. Approval policy is the mechanism that asks before an action crosses that boundary. Read the distinction in Running Codex safely at OpenAI.
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1. Scope filesystem access to the task
Use the repository as the initial boundary
Start the agent in the repository or task directory it actually needs. Permit read access to source, tests and configuration required to understand the change. Permit writes only to the working tree, generated artifacts or other paths named in the task. Add a directory deliberately when a build genuinely requires it; do not expose a whole home directory for convenience.
- Keep personal documents, SSH keys, cloud credentials, password stores and unrelated repositories outside the sandbox.
- Keep operating-system directories and security configuration read-only or inaccessible.
- Decide explicitly whether the agent may write build caches, dependency directories and temporary files.
- Protect version-control metadata and policy directories unless the task specifically requires a reviewed change to them.
OpenAI’s Windows sandbox design discusses ACLs and write-restricted tokens for enforcing write scope, and identifies .git, .codex and .agents as protected locations in that design. Those paths are an implementation example, not a universal rule for every agent or platform. See Building a safe, effective sandbox to enable Codex on Windows.
Separate read, write and delete
Reading a file, editing it and deleting it have different blast radii. If the runtime supports separate capabilities, grant read first, then write to named paths, and require approval for deletes or broad renames. A task that only explains code needs no write permission. A documentation change may need writes to a docs directory but not to deployment manifests.
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Filesystem policy must apply to tools launched by the agent, not only to the agent process. Resolve symlinks and mount points so a writable project path cannot transparently reach a protected directory. Confirm that archive extraction, package scripts and test fixtures cannot write outside the intended root.
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2. Allow execution narrowly
Define an approved command set
Permit the smallest set of commands that completes the task: for example, a project’s test runner, formatter, type checker and build command. Use fixed working directories and predictable arguments where possible. OpenAI describes rules that can allow benign commands while requiring approval for or blocking dangerous patterns in its safety guidance.
- Allow read-only inspection commands without a prompt when they cannot alter state.
- Require approval for package installation, migration scripts, code generation that overwrites many files and commands that modify git history.
- Block privilege escalation, service management, disk operations and host-wide configuration changes.
- Review shell metacharacters, command substitution and scripts fetched at runtime; a harmless-looking command can invoke a second program.
Make effects understandable
An approval request should show the exact command, working directory, files or resources it can affect, and whether it starts child processes. Avoid blanket approval for an entire shell session: users quickly learn to accept prompts without reading them, and the agent may later issue a materially different command.
3. Keep network access off unless the task needs it
Use an allowlist, not a general internet switch
Most local editing and testing can run without outbound network access. If dependency retrieval, an API integration test or documentation lookup is required, allow only the specific hosts, ports and protocols needed for that step. OpenAI’s API sandbox guidance recommends permitting outbound traffic only to approved endpoints; the security guidance is at Sandbox security.
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- Prefer an internal package mirror over unrestricted public registries.
- Separate production endpoints from development and test endpoints.
- Set time, bandwidth and response-size limits to reduce accidental transfers.
- Record every allow and deny decision, including the destination and calling process.
Do not treat proxy variables as enforcement
Environment-based proxy settings are advisory. A program can ignore them, bypass the configured PATH, or open sockets directly. OpenAI’s Windows write-up highlights this implementation caveat. Enforce network policy independently at the sandbox, operating-system, container or host boundary, and verify that child processes inherit the same restriction.
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Inspect fetched content before execution
Downloading a package or script expands the attack surface. Pin dependency versions and verify checksums where your ecosystem supports it. Do not automatically execute install hooks or downloaded scripts with the agent’s full environment. If a task needs a new dependency, make the package name, version and destination visible in the approval request.
4. Keep credentials out of the agent’s reach
Assume generated code can read available secrets
OpenAI’s Agents API documentation states: “Agent-generated code can access the files, credentials, and network available to its environment.” Any key in an environment variable, mounted file or credential helper may therefore be exposed through code, logs or an unintended network request.
Do not mount a developer’s full cloud profile, SSH directory or production configuration. Keep application keys and third-party credentials outside the sandbox whenever possible. The same security guidance warns that injecting stored secrets into the environment exposes them to agent-generated code; it also distinguishes an environment key restricted to connecting that environment from an application API key. Read the credential and environment-key guidance.
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Use scoped, short-lived access
When access is unavoidable, issue a token limited by destination, operation, repository and time. A trusted proxy or secret broker can perform the privileged call without revealing the underlying secret to generated code. Rotate or revoke the token when the task ends, and ensure logs redact secret values while retaining an identifier for investigation.
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Separate development from production
Use test accounts and data for agent-run workflows. Production credentials should require a separate, deliberate release process rather than being available during coding, testing or debugging.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.5. Put human approval at consequential boundaries
Always pause for high-blast-radius actions
Require an explicit, action-specific approval before the agent:
- writes outside the approved workspace;
- deletes or mass-renames files;
- changes access controls, CI secrets or deployment configuration;
- contacts a new external service or uploads project data;
- runs with elevated privileges or changes host configuration;
- performs sensitive cybersecurity activity; or
- takes an action whose intent or side effects are ambiguous.
OpenAI’s cybersecurity guidance says to deny unauthorized actions, pause ambiguous or high-risk changes for human approval, enforce independent filesystem and network boundaries, keep audit logs and fail closed when review is unavailable. See Cybersecurity checks.
Show enough context to decide
Approval UI should identify the requesting task, exact tool and arguments, affected paths or destinations, credential class, expected side effects and reversibility. Let a reviewer approve once for a narrowly bounded operation, not for an unspecified sequence of future commands.
Avoid both extremes
Blanket auto-approval removes the safety boundary. Prompting for every harmless file read creates fatigue and teaches users to click through. Classify operations by risk and reserve prompts for actions that cross a boundary or have meaningful blast radius.
6. Log the agent’s decisions and effects
Retain an event record that connects intent to outcome. At minimum, capture:
- the user request and relevant task or ticket identifier;
- the permission policy in force;
- each approval, denial or automatic decision and the reviewer;
- tool name, arguments, working directory and affected resources;
- stdout, stderr, exit status and resulting file changes;
- network destination, allow or deny result and transferred-volume metadata; and
- credential or broker-use identifiers without storing secret material.
OpenAI says Codex can export OpenTelemetry events for user prompts, tool approval decisions, tool execution results, MCP usage and network-proxy decisions. Its rules and telemetry discussion appears in Running Codex safely at OpenAI. Combine agent events with operating-system process, file and connection logs so an investigation can reconstruct what happened.
Set retention and access rules
Protect logs from the agent itself, define a retention period that meets your incident-response and privacy requirements, and restrict who can view prompts and outputs. Redact tokens, personal data and proprietary content while preserving enough metadata to correlate events.
7. Fail closed when review is unavailable
If a required policy engine, approval service, network gateway or secret broker is down, do not silently continue with broader permissions or an unreviewed fallback. Stop the operation, report which control is unavailable and provide a safe recovery path. OpenAI explicitly recommends failing closed when review is unavailable for sensitive cybersecurity workflows.
A practical rollout sequence
- Inventory the task. List required files, commands, destinations, data classes and expected outputs.
- Create the smallest sandbox. Mount the repository, make only necessary paths writable and leave network disabled.
- Add capabilities one at a time. Enable a test command, package mirror or brokered service only when the task demonstrates the need.
- Attach approval rules. Map destructive, external, elevated and ambiguous actions to human review.
- Test escape paths. Try symlinks, child processes, shell metacharacters, direct sockets and attempts to read home-directory secrets.
- Run a dry task. Confirm expected files change, blocked actions are denied and logs contain the required context.
- Review and revoke. Remove temporary paths, tokens and allowlist entries when the task finishes.
Permission review checklist
- Is the workspace limited to the repository or task directory?
- Are read, write, delete and execute capabilities separated?
- Do symlinks, mounts and child processes remain inside the boundary?
- Is outbound network disabled unless a destination is explicitly approved?
- Are network controls enforced independently of environment variables?
- Can generated code read any credential, token or personal file?
- Are available credentials short-lived, destination-scoped and revocable?
- Do destructive, elevated, external and ambiguous actions pause for review?
- Does the approval request show exact scope and side effects?
- Are prompts, decisions, tool results and network outcomes logged and protected?
- Does the workflow stop if a required review or enforcement service fails?
- Have you verified the selected product’s current behavior rather than assuming another agent’s defaults?
What this checklist cannot standardize
There is no universal permission profile across coding agents, operating systems or deployment models. The official guidance cited above does not establish a current vendor-by-vendor comparison of defaults. Capabilities, protected paths, policy syntax and telemetry differ, so inspect the product’s documentation and test the runtime boundary you will actually deploy. The least-privilege principle remains portable: start with no access, add one justified capability, enforce it outside the model and record the result.
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