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The safest useful setup is two-layered: first define the technical boundary (which files the agent may read or change, and whether it can reach the network), then define approval behavior (which actions must stop for review). Use read-only access for inspection, workspace-limited writes for ordinary implementation, and deliberate approval for anything that leaves the workspace, uses the network, or triggers an external side effect.
Do not treat an approval prompt as a security boundary. A prompt controls whether you confirm an action; sandboxing controls what the process can technically reach. Choose both for the specific task, verify the effective policy in the environment that actually runs commands, and expand access only when a concrete requirement justifies it.
What permissions are you actually choosing?
An AI coding agent usually operates through several different capabilities rather than one master permission. The important choices are the filesystem, network, command execution, URL fetching, external tool integrations, and the approval policy applied to each. Visual Studio Code documents approvals and sandboxing as separate controls, including permission levels, terminal approval, URL approval, tool approval, and sandboxing (Microsoft’s approvals documentation).
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- Technical boundary: the paths, processes, hosts, and data the agent can reach.
- Human gate: the actions that pause for confirmation, and whether a confirmation applies only once or more broadly.
These layers complement each other. If a command is approved, the sandbox can still restrict it. Conversely, a generous sandbox can leave too much power available even if prompts are enabled. The right profile is therefore a task decision, not a personality setting such as “safe” or “autopilot.”
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How should access change with the task?
Start with the smallest capability that can complete the job, then add one permission at a time. Inspection, implementation, dependency work, and deployment have different risk profiles.
| Decision axis | What to inspect | Practical starting point |
|---|---|---|
| Filesystem | Read paths, write paths, and whether access extends outside the repository | Read-only for inspection; workspace-only writes for coding |
| Network | Whether commands can reach arbitrary hosts, approved domains, or no network | Off by default where practical; allow only task-relevant access |
| Approval behavior | Which commands and actions prompt, and whether approval is one-time or broader | Require review for boundary-crossing or consequential actions |
| Tool integrations | Tool capabilities, data sent, side effects, and approval scope | Enable only integrations needed for the task; review each separately |
| Review and reversibility | Whether diffs can be inspected and changes reverted before merge or commit | Review changes before accepting them, especially in unfamiliar repositories |
| Execution context | Local versus cloud, operating system, harness, and managed policy | Check the effective settings in the environment that actually runs commands |
This is a decision framework, not a universal preset. A test that only explains a code path needs less access than a task that installs a package, calls a staging API, or edits deployment configuration.
For review, explanation, or documentation
Use read-only access. The agent can inspect source, configuration, and history without being able to overwrite them. Keep terminal execution either disabled or subject to approval if the inspection requires commands. This profile is appropriate for code review, architecture questions, security triage, and generating a change plan.
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Use workspace-limited writes. The agent can modify project files while remaining unable to write arbitrary locations such as a home directory or unrelated repositories. OpenAI’s security guide describes read-only and workspace-write modes and notes that local CLI and IDE defaults commonly use no network access with writes limited to the active workspace; confirm the current product and environment before relying on those defaults (OpenAI’s Agent approvals & security guide).
For dependency, build, or integration work
Keep filesystem writes narrow, then grant only the network or tool access required for the specific operation. For example, a package installation may need a package host, while a local refactor needs neither network nor external tools. Remove the temporary allowance when the operation is complete.
How do I give an AI coding agent access to my files?
Define a path boundary before deciding whether the agent may write. The boundary should correspond to the project it is meant to change, not simply to the account that launched it.
1. Identify the read set
List the files needed to understand the task: source directories, tests, build configuration, and relevant documentation. Exclude unrelated repositories, personal documents, credentials, production exports, and generated data unless the task genuinely requires them. A narrower read set reduces accidental disclosure as well as accidental edits.
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2. Choose the write set
For inspection, make the entire session read-only. For implementation, allow writes only in the active workspace or a disposable checkout. Keep generated artifacts, caches, and build output outside the writable set when your harness permits that distinction. If the agent must update a shared configuration file, treat that as a deliberate expansion and review the resulting diff immediately.
3. Separate source changes from repository administration
Writing source files is different from changing hooks, credentials, CI definitions, deployment manifests, or version-control metadata. Require a review for those areas even when ordinary source edits are allowed. A workspace boundary limits location; it does not tell you whether a file’s contents have a high operational impact.
4. Confirm the boundary from the running environment
Read the effective configuration on the machine or remote session that executes commands. A local editor, a remote development host, a container, and a managed organization policy can expose different paths. Do not infer the real boundary from a label shown in a different product or from a remembered default.
Should I let a coding agent run terminal commands?
Allow terminal commands only when they add value that file access cannot provide, and keep approval and sandboxing independent. Commands can compile code, run tests, inspect dependencies, or alter the system, so classify them by side effect rather than treating every command as equivalent.
Commands that are usually easy to review
- Reading files, listing project directories, and checking version information.
- Running deterministic unit tests or linters that write only to disposable build output.
- Formatting code when the resulting diff is visible and reversible.
Even these commands can be unsafe in an unfamiliar repository if scripts execute hooks or child processes. Review the command and its working directory before approving it.
Commands that deserve an explicit gate
- Installing or upgrading dependencies.
- Deleting files, rewriting history, or changing repository hooks.
- Reading environment variables, credential stores, or files outside the workspace.
- Starting services that listen on a network interface or modifying system configuration.
- Publishing artifacts, opening pull requests, deploying, or sending data to a third party.
Visual Studio Code’s approvals documentation distinguishes terminal approval from other approval categories and warns that modes such as “Allow all” and “Autopilot” skip confirmation prompts (Microsoft, Manage approvals and permissions). If you choose a broad approval mode for a controlled experiment, compensate with a tight sandbox and a disposable environment; do not describe the prompt setting itself as containment.
How do I restrict an AI agent’s network access?
Assume no network unless the task has a named destination and a reason to contact it. Network access can expose source code, credentials, prompts, and build data, while downloads can introduce unreviewed code or change a reproducible build.
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Use a deny-by-default starting point
For local analysis, tests that use checked-in fixtures, and most refactors, disable network access. If a tool offers an allowlist, name the required hosts rather than granting arbitrary outbound access. Record why each host is needed and remove it after the task.
Distinguish URL approval from terminal networking
A direct URL-fetching tool and a shell command such as a package manager are different routes to the network. An approval for one does not automatically govern the other. Review URL approval, terminal approval, and any integration-specific policy separately; Visual Studio Code lists these as distinct controls (approvals and permissions).
Plan for remote execution
The host that runs the command determines the practical network boundary. A remote workspace may have routes, proxies, mounted credentials, or organization controls that do not exist on a laptop. Microsoft’s sandboxing guidance specifically emphasizes the execution machine and remote sessions, so verify the policy where the process actually runs (Sandbox Copilot agent sessions).
How should I review MCP and other tool integrations?
Give every integration its own capability review. An MCP server, URL fetcher, database connector, issue tracker, or deployment tool may read data, write data, or trigger an external action that is outside the terminal sandbox.
Inventory each tool
- What inputs can it receive, including source code, prompts, environment data, or file contents?
- What outputs or side effects can it create?
- Where does the data go, and how long might it be retained?
- Does it run locally, on a remote service, or through a managed organizational account?
- What approval check applies to each operation?
Enable only task-relevant operations
Prefer a read-only operation when a write operation is not required. If a connector exposes many methods, disable or withhold the ones that create, delete, publish, or change permissions. Keep credentials scoped to the same minimum capability; an approval prompt cannot reduce the privileges already held by the integration.
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Test integrations with harmless data
Before connecting production records or proprietary repositories, use a disposable project and synthetic values. Confirm what the agent displays before a call, what the tool returns afterward, and whether the operation is reversible. Treat a successful test as evidence about that configuration only, not as a guarantee for another host or account.
Visual Studio Code’s trust-and-safety guidance notes that built-in and other non-process tools remain subject to separate permission checks, even when terminal processes are sandboxed (Understand trust and safety for AI agents). Review those checks instead of assuming the terminal policy covers an MCP server.
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What approval policy should I choose?
Match the prompt policy to the consequence of the action. A useful default is to allow low-impact inspection, request confirmation for changes, and require a fresh review for boundary crossings or irreversible operations.
Use prompts for decisions a person can meaningfully inspect
A prompt is valuable when it shows the proposed command, target path, tool, or destination clearly enough for you to decide. Pause for package installation, network access, writes outside the workspace, credential use, data transmission, deployment, and destructive changes. Do not approve a vague request merely because the agent says it is needed.
Do not use prompts as your only control
Approval bypasses and unattended runs are sometimes useful in a disposable environment, but they do not make an unrestricted process safe. Microsoft explains that sandboxing can continue to restrict terminal commands even when approvals are bypassed, and also cautions that sandboxing is not a virtual machine or a replacement for endpoint security (trust and safety guidance).
Prefer narrow, temporary approvals
If the task needs one network host or one external tool, approve that operation rather than enabling a broad category for the rest of the session. Revoke the exception when the task ends. For unattended automation, move the work into an isolated runner with limited credentials and a reviewable output instead of silently widening a developer workstation’s permissions.
How do I verify the effective policy before trusting it?
Labels and defaults can differ by product version, operating system, harness, remote mode, and organization policy. Verification should be an explicit step before the agent handles sensitive code.
- Locate the active settings. Check the agent’s permission, sandbox, terminal, URL, and tool-integration panels in the product that is executing the session.
- Check for managed overrides. Organization policy may force a stricter or broader setting than a user can see or change.
- Identify the execution host. Determine whether commands run locally, in a container, on a remote development machine, or in a cloud service.
- Confirm filesystem reach. Verify which paths are readable and writable, including mounted directories and temporary locations.
- Confirm network reach. Establish whether outbound connections are disabled, allowlisted, proxied, or unrestricted.
- Check each tool separately. Record the approval behavior and data scope for URL fetchers, MCP servers, built-in tools, and terminal commands.
- Run a harmless probe. Use a disposable workspace and a benign file or host to confirm that the observed behavior matches the intended policy.
OpenAI’s guide and Microsoft’s documentation describe common configurations, but both are product-specific. Treat their examples as a map to the controls, then verify the settings for the version and environment you are using (OpenAI; Visual Studio Code approvals).
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- Read-only filesystem access.
- No network unless a documented lookup is necessary.
- Terminal disabled or approval required for every command.
- No write-capable external integrations.
- Human review of any generated patch before it is applied.
Implementing a feature in a trusted local project
- Read and write limited to the active workspace.
- Network disabled for the initial implementation.
- Approval for dependency installation, scripts with side effects, and changes to hooks or deployment files.
- Diff review before commit or merge.
Updating dependencies
- Workspace writes only.
- Temporary access to the organization’s approved package hosts.
- Approval for install, upgrade, lockfile, and post-install scripts.
- Revoke network access after the dependency change and inspect the complete diff.
Working with a staging API
- Use a separate staging credential with the minimum API scope.
- Allow only the required endpoint or connector.
- Require approval for requests that create, modify, or delete records.
- Use synthetic or non-sensitive data whenever possible and keep production credentials unavailable.
What commonly goes wrong, and how can I recover?
The agent cannot complete a harmless task
First determine whether the failure is a missing filesystem path, a blocked network request, a terminal approval, or a disabled integration. Grant the smallest missing capability, retry once, and then return to the original boundary. Avoid switching to an unrestricted profile just to discover which control caused the failure.
A command asks for access outside the workspace
Stop and inspect why. It may be a legitimate cache, compiler, or credential lookup, or it may be an unnecessary script behavior. Prefer redirecting the operation into the workspace or a disposable directory; if an outside path is essential, approve that specific path and review its contents afterward.
An approved tool produces an unexpected side effect
Revoke the integration, preserve the logs or returned data needed to understand what happened, and inspect repository and account changes. Rotate any credential that may have been exposed. Reconfigure the tool with read-only methods or narrower credentials before reconnecting it.
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The policy differs between laptop and remote session
Compare the effective host, mounts, operating-system controls, organization settings, and agent harness. Recreate the intended boundary on the host that will run the work; do not assume a local test proves the remote session is equivalent.
What is the final checklist before enabling an agent?
- The task has a named purpose and an explicit stop condition.
- Read paths and write paths are listed, with unrelated and sensitive locations excluded.
- Network access is off or limited to documented destinations.
- Terminal, URL, MCP, and other tool approvals have been reviewed separately.
- Destructive, publishing, deployment, credential, and boundary-crossing actions require confirmation.
- The execution host and any managed policy are known.
- Changes can be inspected and reverted before they reach a shared branch or service.
- Temporary exceptions have an owner and a removal point.
The practical rule is simple: constrain what the agent can reach, then decide what it must ask before acting. Read-only is the right starting point for understanding code; workspace-only writes are the usual next step for implementation; network and consequential tools should be added only for a named requirement.
Frequently Asked Questions
Can an AI coding agent read my environment variables or secret files?
Only if the effective filesystem, process, or tool policy exposes them. Keep secret paths and sensitive environment variables outside the agent’s readable scope, use short-lived task credentials, and inspect command lines and tool inputs for accidental disclosure.
Does workspace-write access protect my Git history?
It limits where files may be changed, but it does not automatically make every version-control operation harmless. Treat history rewrites, hook changes, force pushes, and commits as separate consequential actions that deserve review.
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Connect it first to a disposable project containing synthetic data and grant only read operations. Observe the data it receives and returns, test whether writes can be reversed, and enable broader methods only after the behavior matches the task.
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Recheck it whenever the repository, agent version, execution host, organization policy, or connected tools change. A profile that was appropriate for a local refactor may be excessive for a shared repository or a remote session.
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