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The safest useful setup for an AI coding agent uses two separate decisions: a technical boundary and an approval policy. Limit which files it can read or change, decide whether its commands can access the network, and then require confirmation for actions that cross those limits or create meaningful external effects. For code explanation and review, start read-only. For implementation, start with writes confined to the project or workspace, keep network access off unless the task needs it, and approve terminal, URL, and integration tools independently. Expand access only for a named task, and verify the effective policy on the machine that actually runs the agent.
What permissions should an AI coding agent have?
Give the agent the smallest set of capabilities that can complete the current task. A reviewer needs to inspect source files, tests, and configuration; an implementer usually needs to edit files inside one workspace and run selected local checks. Neither role automatically needs unrestricted home-directory access, arbitrary network access, or permission to call every connected service.
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Think in two layers:
- Technical boundary: which paths are readable or writable, whether processes can reach the network, and which execution environment runs commands.
- Approval behavior: which actions pause for your confirmation, which are pre-approved, and whether an approval applies once or more broadly.
These layers complement each other. An approval prompt is a review checkpoint, not a filesystem restriction; once you approve an action, it may still have all the access allowed by the sandbox. Conversely, a sandbox can continue to block an operation even when prompts are bypassed. Microsoft describes these as separate controls in its VS Code approvals and permissions documentation.
How are approvals different from sandboxing?
Sandboxing imposes a technical limit on what a process can do. Approvals decide when the agent must ask before attempting an action. Use both: the sandbox limits blast radius, while approvals give you a chance to inspect high-impact requests.
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| Control | What it governs | What it does not guarantee | Practical use |
|---|---|---|---|
| Filesystem sandbox | Readable and writable paths available to commands or tools | It may not govern non-process integrations, and it is not a full virtual machine | Keep review work read-only; confine implementation writes to the workspace |
| Network policy | Whether commands can reach arbitrary hosts, approved domains, or no network | It does not by itself decide which files an agent can read or change | Disable by default where practical; allow only task-relevant endpoints |
| Terminal approval | Whether a shell command or process launch needs confirmation | Approval does not reduce the command’s sandbox permissions | Review package installation, migrations, deletion, and other consequential commands |
| URL or web approval | Whether fetching a URL requires confirmation | It does not automatically cover every tool or integration that can send data | Approve specific documentation or package hosts as needed |
| Tool or integration approval | Whether built-in tools and external integrations may run | Each integration can have different data handling and side effects | Enable only the connectors required for the task and inspect their scope |
VS Code’s trust-and-safety guidance explains that operating-system isolation can constrain terminal commands and their child processes, while built-in and other non-process tools remain subject to separate permission checks. It also warns that sandboxing is not a virtual machine or a replacement for endpoint security: Understand trust and safety for AI agents.
How do I give an AI coding agent access to my files?
Choose the narrowest filesystem mode that matches the job, then check the actual paths before the first run. Read-only is the default for inspection; workspace-only writes cover most feature and bug-fix work; access outside the workspace should be an explicit exception.
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Use read-only for inspection and explanation
Read-only access lets an agent map the repository, explain code, identify likely defects, propose patches, and review a diff without modifying files. It is the right starting point for an unfamiliar codebase, a security review, or a request such as “tell me why this test fails.” You can copy a proposed patch into a separate branch or worktree after reviewing it.
Use workspace-limited writes for implementation
A workspace-write profile allows edits under the active project directory while keeping unrelated personal files outside the boundary. Confirm that the workspace does not contain secrets, production credentials, mounted company shares, or generated directories that should be immutable. If the project contains several repositories, define the workspace deliberately rather than selecting a broad parent folder.
OpenAI’s agent-security guide documents read-only and workspace-write sandbox examples and notes that local command-line and IDE defaults commonly combine workspace-limited writes with no network access. Defaults vary by product version and environment, so use the guide as a reference and verify the effective setting where your agent runs: Agent approvals & security.
Request broader paths only for a named dependency
Some tasks genuinely need a path outside the repository: a local SDK, a shared test fixture, a build cache, or a generated artifact directory. Grant that path specifically, explain why it is needed, and remove the exception afterward. Do not respond to a vague “permission denied” error by exposing an entire home directory or filesystem.
Should I let a coding agent run terminal commands?
Usually yes for implementation and diagnosis, but begin with a sandbox and approvals that make destructive or boundary-crossing commands visible. Terminal access can read files, execute child processes, install packages, alter databases, and invoke scripts; the command text alone does not tell you the full effect.
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Commands that normally deserve confirmation
- Installing or upgrading packages, language runtimes, compilers, or system tools.
- Running database migrations, deployment scripts, infrastructure changes, or commands that contact production.
- Deleting or mass-renaming files, resetting a repository, changing permissions, or rewriting history.
- Executing downloaded scripts, shell pipelines that pipe network content into an interpreter, or binaries whose provenance is unclear.
- Opening tunnels, changing firewall rules, starting publicly reachable services, or exporting credentials.
Commands that can often be pre-approved inside a safe boundary
Formatting, linting, unit tests, static analysis, and local builds are generally reversible and useful during iteration when they run inside the workspace and do not access production systems. Even then, inspect the command’s scripts: a package task can invoke arbitrary child processes, so treat a familiar label such as “test” as a convenience, not a security guarantee.
Check the child-process boundary
A terminal command can spawn other programs, inherit environment variables, and write to paths indirectly. Confirm that the sandbox applies to child processes and that secrets are not injected into the environment unnecessarily. VS Code’s trust-and-safety documentation describes OS-level isolation for terminal commands in sessions using default tools, while noting that non-process tools follow separate checks: trust and safety guidance.
How do I restrict an AI agent’s network access?
Set network access to off unless the task needs a clearly identified destination. If access is required, prefer an allowlist of package registries, documentation hosts, source-control endpoints, or internal APIs rather than unrestricted outbound connectivity.
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Offline mode is appropriate for code review, refactoring against already checked-in dependencies, handling proprietary source, and reproducing a bug with a locked dependency cache. It reduces accidental data transmission and prevents a compromised dependency or script from reaching an external service.
When a narrow exception is justified
Package resolution, fetching API documentation, downloading a known test fixture, or calling a development API may require network access. Write down the host, port, purpose, and duration before enabling it. If the tool can approve individual URLs, use that control rather than granting all web requests. Remember that a network allowlist does not prevent an authorized endpoint from receiving sensitive data; review what the command or integration sends.
Do not infer network policy from an approval label
Labels such as “autopilot” or “allow all” describe confirmation behavior, not a universal technical boundary. VS Code explicitly cautions that bypassing confirmations does not necessarily remove sandbox restrictions, and the reverse is also true: a prompt does not make an unrestricted network safe. Read the product’s current sandbox and approval documentation before relying on a preset.
How do I approve MCP and other tool integrations safely?
Review each integration as a separate capability. A terminal sandbox may not govern a connector that can read cloud data, send messages, modify tickets, or call an external API.
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Inventory the integration’s capabilities
- What data can it read, and does it include secrets, source code, customer records, or personal information?
- What actions can it take: read-only queries, file writes, publication, deletion, payments, or account changes?
- Where is data sent, how long is it retained, and which identity or credentials does it use?
- Does one approval authorize a single call, a session, a tool family, or future calls?
Separate read and write connectors
Prefer a read-only connector for search, issue lookup, or documentation. Create a distinct write-capable connection for actions such as opening a pull request or changing an issue, and require confirmation immediately before the side effect. If an integration cannot express that separation, treat the whole connector as write-capable.
Keep credentials outside the agent’s normal view
Use short-lived, least-privilege tokens where the platform supports them, and avoid placing long-lived secrets in repository files or broad environment variables. An agent that can read a token can often use it through a different tool, so credential scope must match the filesystem and network scope.
VS Code lists tool approval, URL approval, terminal approval, and sandboxing as distinct controls in its permissions documentation: Manage approvals and permissions. That separation is a useful model even when another harness uses different names.
What permission profile fits each coding task?
Use a task-based profile instead of a permanent “safe” or “full access” mode. The table below describes a practical starting point; the effective behavior depends on the product, harness, operating system, and organizational policy.
| Task | Filesystem | Network | Approvals | Extra checks |
|---|---|---|---|---|
| Explain unfamiliar code | Read-only repository | Off | Prompt for any tool not required to read files | Exclude secrets and personal directories from the workspace |
| Review a pull request | Read-only checkout plus test outputs | Off unless dependencies are missing | Approve test execution if it invokes scripts | Inspect the diff and generated artifacts |
| Implement a feature | Writes limited to the project | Off initially; allow named registries or APIs if required | Prompt for installs, migrations, deletion, and external calls | Use a branch and review every diff |
| Debug a service locally | Workspace writes and designated logs | Allow only the local or development endpoints needed | Prompt for commands that alter data or expose a port | Use synthetic data and bounded log retention |
| Deploy or change infrastructure | Project files plus deployment configuration | Required service endpoints | Require confirmation for every consequential command | Use a separate human-controlled release step |
| Work with a cloud or ticketing connector | Read-only unless edits are essential | Specific connector endpoints | Approve each write operation | Check identity, data scope, and audit logs |
How do I configure a least-privilege setup step by step?
Apply the following sequence in the environment that executes the agent, not merely in a user interface that sends requests to it.
- Define the deliverable. Write down whether the agent must inspect, edit, test, fetch data, or perform an external action. Remove capabilities unrelated to that list.
- Choose the execution context. Identify the local or remote machine, operating system, container, repository, and organization-managed policy. Remote sessions can have different boundaries from local sessions.
- Set the filesystem mode. Select read-only for analysis or workspace-limited writes for implementation. Enumerate any required outside path rather than opening a parent directory.
- Set network access. Start with no network. If a dependency or API requires access, specify the approved hosts and the reason, then turn the exception off when finished.
- Set approval rules. Require confirmation for boundary crossings, package installation, deletion, migrations, deployment, credential use, and external writes. Decide whether an approval is one command or a broader session grant.
- Review integrations. Disable unused connectors. For each enabled tool, record its readable data, writable systems, credentials, destination, and approval behavior.
- Run a harmless probe. Ask the agent to list the workspace, read a known file, and attempt a clearly blocked path or network destination. Confirm that allowed actions work and denied actions fail.
- Inspect changes before accepting them. Review the diff, generated files, command history, and tool calls. Revert unexpected changes, revoke temporary access, and record any exception needed for the next run.
How can I verify that the boundary is real?
Verification should test both what the agent can do and what it cannot do. A green test run is not evidence that the sandbox blocked an unrelated path or integration.
- Filesystem test: confirm a file inside the workspace can be read and, when intended, edited; confirm a file outside the allowed paths is denied.
- Network test: verify that an unapproved host fails and that an explicitly approved development endpoint works.
- Process test: run a harmless command that spawns a child process and check that the same boundary applies.
- Integration test: use a read-only query, then verify that a write action still asks for approval.
- Recovery test: make sure you can stop the session, revoke credentials, restore a clean checkout, and identify all modified files.
Keep the verification record with the project or team policy. Settings can change with product updates, remote execution, or managed controls, so repeat the check when the harness, operating system, or organization policy changes.
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What are the most common permission mistakes?
Most failures come from treating a convenient preset as a complete security model or from widening access to solve an unrelated error.
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An approval prompt tells you that a request needs attention; it does not sanitize the command or narrow its capabilities. Read the exact command, the working directory, inherited variables, destination, and expected side effect before accepting it.
“Workspace write means only source files can change”
Build scripts, package hooks, generated files, and test fixtures may also be writable inside the workspace. Use a branch, inspect the full diff, and protect production configuration and deployment credentials even when they are stored in the repository.
“The terminal sandbox covers every tool”
Non-process tools and external integrations may use their own permission checks. Review them separately, especially when they can upload data or modify a remote system.
“A denied command means the agent needs full access”
First identify the exact missing capability. Add one path, host, command class, or connector at a time, rerun the task, and remove the exception when it is no longer needed. If the requirement is unclear, remain in read-only mode and perform the operation yourself.
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The machine where commands run determines which operating-system controls, filesystems, credentials, and network routes are available. VS Code’s sandboxing documentation emphasizes applying its details to the harness and tools it covers, including remote contexts: Sandbox Copilot agent sessions.
How should teams govern permissions?
Individual developers can choose a narrow profile, but organizations also need a repeatable policy. Define approved profiles, document who may grant exceptions, and make the human release step independent of the coding agent.
- Standard profiles: publish read-only, workspace-write, and deployment profiles with explicit filesystem, network, and integration limits.
- Exception records: capture the task, additional path or host, owner, expiry time, and reason.
- Review gates: require human review for production access, external writes, migrations, and publication.
- Auditability: retain diffs, command approvals, integration calls, and credential-use logs according to your organization’s policy.
- Environment separation: use synthetic or staging data for development and keep production credentials unavailable to ordinary coding sessions.
Organization-managed settings can override local choices. If a control appears unavailable or behaves differently from the product documentation, check the managed policy and the actual execution host rather than assuming the agent ignored your preference.
What should I do when an agent needs more access?
Pause and convert the request into a specific, reviewable change. Ask which file, host, command, or integration is required; what data will cross the boundary; and whether a human can perform that one step instead.
- Read the blocked operation and identify its narrow capability.
- Check whether the task can use a local cache, mock service, read-only export, or separate worktree instead.
- Grant the smallest temporary exception, with an expiry or cleanup step.
- Run only the necessary command, then inspect outputs and changed files.
- Revoke the exception and rotate any credential that may have been exposed.
This approach preserves momentum without turning a one-off dependency download or diagnostic query into permanent unrestricted access.
What does “safe” mean for an AI coding agent?
“Safe” is contextual, not a universal product mode. A profile is safer when its allowed data, actions, destinations, and approvals match the task and remain understandable to the person supervising it.
Before starting, be able to answer four questions: What can the agent read? What can it change? Where can it send data or commands? Which actions will stop for review? After the run, be able to show the diff, revoke temporary access, and restore the workspace. That combination of a technical boundary, deliberate approvals, and reviewable recovery is more reliable than any single preset label.
Frequently Asked Questions
Can an AI coding agent access files outside the repository?
It can only do so if the execution environment and policy grant those paths. If an outside file is needed, expose that specific path temporarily or copy a sanitized version into a controlled workspace; avoid granting an entire home directory.
How can I keep secrets out of an AI coding session?
Do not place long-lived credentials in source files, broad environment variables, or mounted directories the agent can read. Use short-lived, least-privilege credentials where possible, synthetic data for tests, and rotate a token if a tool call may have exposed it.
Should coding-agent permissions be different in CI?
Yes. CI should use a dedicated non-human identity, an isolated checkout, and credentials limited to that pipeline’s job. Keep deployment or publication behind a separate approval gate rather than inheriting a developer’s interactive permissions.
What should I log when an agent changes code?
Record the final diff, commands that were approved, network or integration calls, identity used, and any temporary exception. These records make unexpected changes diagnosable and show which boundary was effective during the run.
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