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The safest way to let an AI agent edit code is to assume that a bad command, a misunderstood request, or prompt injection could make it delete or overwrite anything it can reach. Put the agent in a deny-by-default sandbox, expose only a disposable project directory, run it with a separate least-privilege identity, and require approval for destructive actions. Add a Git worktree, frequent checkpoints, and snapshots or immutable artifacts so an error is both contained and recoverable.
Isolation and approval solve different problems: a sandbox limits what the process can access, while an approval gate decides whether a risky operation is allowed to run. You need both.
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What can go wrong when an AI agent edits files?
An agent can remove files deliberately, but accidental damage is more common. It may interpret “clean up” as deleting files, apply a broad search-and-replace to the wrong directory, regenerate a configuration file with missing settings, or run a migration against a production checkout. A command that looks harmless in a prompt can expand through shell globbing, recursive options, symlinks, or a script with side effects.
There is also a trust problem. Source files, issue descriptions, documentation, test fixtures, and command output can contain instructions written to steer the model. Cloudflare documents this prompt-injection risk for filesystem tools: a file can tell an agent to delete other files or perform another harmful action. Treat both files and tool output as untrusted input, and inspect results before allowing an action with side effects. See Cloudflare’s filesystem guidance.
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The blast radius is determined by access, not by the agent’s stated intention. If its process can write your home directory, SSH keys, cloud credentials, production checkouts, and backups, one mistaken tool call can affect all of them. If it can write only a disposable worktree, the same mistake is usually limited to that worktree.
The defense-in-depth control stack
Use several independent controls. A single permission prompt or a single Git commit is not a complete safety system.
1. Isolate the process in a sandbox
Run the agent inside a container, virtual machine, or another deny-by-default execution boundary. OpenAI describes a sandbox as an isolated, Unix-like environment with a filesystem, shell, installed packages, mounted data, exposed ports, snapshots, and controlled access to external systems. Its sandbox documentation also describes separating the compute boundary from a trusted harness and using narrow credentials and mounts.
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- Read-write: the disposable project directory and any explicitly approved build cache.
- Read-only: reference documentation, dependency caches, or source snapshots that the agent must inspect but must not modify.
- Denied: credentials, operating-system paths, other users’ files, production directories, backup repositories, and the host’s control socket.
Network access is part of the boundary. If the task does not need the network, disable it. If it does, allow only the package registries, APIs, or hosts required for that task, and keep credentials scoped to that environment.
2. Apply path-level permissions
Sandboxing is stronger when the policy names paths explicitly. GitHub’s Copilot CLI documentation describes read/write, read-only, and denied paths in a deny-by-default model: understanding local sandboxing. Visual Studio Code documents the same categories and states that denied paths take precedence over read-only, which takes precedence over read/write: agent sandboxing.
Use the narrowest rule that works. A project’s source and test folders may be writable; a checked-in deployment manifest may be read-only until a human reviews a proposed change; ~/.ssh, cloud credential directories, and backup locations should be denied. Be explicit about generated directories: if they can be recreated, put them in the disposable workspace rather than granting access to a shared cache.
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| Resource | Recommended access | Reason |
|---|---|---|
| Disposable project worktree | Read/write | The agent needs to create and test changes here. |
| Reference repository or specification | Read-only | It can inspect the material without changing the source of truth. |
| Operating-system directories | Denied | Prevents system-wide changes and accidental deletion outside the task. |
| Home-directory configuration and secrets | Denied | Protects SSH keys, tokens, shell configuration, and personal data. |
| Production checkout and deployment state | Denied | Keeps development automation away from live systems. |
| Backup or snapshot destination | Read-only or denied | Stops an agent from destroying the recovery copy along with the working files. |
3. Use a separate least-privilege identity
Run the agent as a dedicated operating-system user or service identity, not as your administrator account. Give that identity only the repository permissions and environment variables required for the task. Do not pass broad cloud credentials into the process; use short-lived, task-scoped credentials where your platform supports them.
Microsoft’s agent-security guidance lists per-tool permissions, per-action authorization checks, human approval for high-impact actions, sandboxing, and audit logging as responsibilities for a secure agent deployment. Review those controls in Microsoft’s shared-responsibility guidance for AI agents.
4. Separate approval from isolation
Approval prompts are not a substitute for a sandbox. An approved command can still affect every path the process can reach. Conversely, a sandbox without approvals may allow an agent to erase the entire workspace automatically.
Require a human decision before:
- Deleting files or directories, especially recursive deletes.
- Overwriting an existing file, replacing a generated artifact, or applying a mass rename.
- Running
git reset --hard, changing branches, rewriting history, or force-pushing. - Changing ownership, permissions, user identity, firewall rules, or sandbox settings.
- Executing a command outside the approved workspace.
- Making network requests that are not on the allowlist or using a new credential.
- Deploying, publishing, or modifying a live database or service.
Show the exact command, working directory, affected paths, and a short explanation in the approval request. “The agent wants to clean up” is not enough information to authorize a recursive delete.
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5. Keep identity, path, and network logs
Record the agent identity, requested tool call, authorization decision, paths touched, command output, resulting diff, and rollback point. Logs should be outside the agent’s writable workspace so the process cannot silently rewrite its history. Microsoft explicitly includes action audit logging and monitoring in its agent-security responsibilities.
Build a safe coding workflow
The following sequence keeps risky edits reviewable and makes recovery predictable.
Step 1: Classify the files before starting
Write down what the task needs to read and what it may change. Separate source code, tests, generated output, local configuration, secrets, and deployment files. If a file is not required, do not mount it. If a file must be inspected but not changed, mark it read-only.
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Pay special attention to symlinks and scripts. A writable link can point outside the apparent project, and a build script can write to paths that are not obvious from the command line. Resolve those paths during your preflight check and keep the target outside the agent’s allowed area.
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From a clean, trusted clone, create a linked worktree and a dedicated branch:
git worktree add ../agent-task -b agent-taskPoint the sandbox at ../agent-task, not at your primary checkout. A worktree gives the agent its own working directory while retaining normal Git history for review. When the task is complete, inspect the branch and merge only the approved changes.
If the worktree must remain on disk while another process might prune it, lock it:
git worktree lock ../agent-taskGit refuses to remove an unclean worktree unless forced, and git worktree lock protects a worktree from pruning. The complete command reference is in the Git worktree documentation.
Step 3: Make a known-good checkpoint
Commit or tag the starting state before the agent runs. Keep the commit identifier in your run log. For high-risk tasks, create a snapshot of the entire disposable workspace as well. Git covers tracked files; it does not automatically preserve untracked uploads, generated output, ignored files, or data stored outside the repository.
Step 4: Configure the sandbox policy
Set the project worktree to read/write, reference material to read-only, and everything else to denied. Put the policy under version control or store it with the run record so another person can reproduce the same boundary. Test the policy with harmless reads and writes before giving the agent a real task:
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- Read a file that should be accessible.
- Create and delete a temporary file inside the disposable worktree.
- Attempt to read a denied secret path and confirm that the operation is blocked.
- Attempt to write a read-only path and confirm that it is blocked.
- Attempt to access a path outside the workspace and confirm that it is blocked.
A failed boundary test is a stop condition. Do not rely on the agent to remember the policy in its prompt.
Step 5: Start with a narrow task contract
Tell the agent the allowed directory, expected files, test command, and forbidden operations. Ask it to list intended file changes before applying them. Require a dry run for migrations, formatters, bulk renames, and code-generation commands. This does not replace technical controls, but it makes unexpected behavior easier to spot.
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Keep automatic execution for low-impact reads, tests, and writes inside the disposable worktree. Pause for approval when the agent proposes deletion, overwrite, privilege change, network access outside the allowlist, or a command that resolves outside the workspace. Review the command and its path expansion, not just the natural-language explanation.
Step 7: Review the resulting diff
After each meaningful unit of work, inspect the list of changed files and the diff. Look for unexpected binary changes, permission changes, deleted files, generated secrets, modified lockfiles, and edits outside the stated scope. Run tests in the sandbox, then have a human approve the branch before merging it into the primary checkout.
Step 8: Tear down and preserve evidence
When the task ends, revoke temporary credentials, archive the audit record, and remove the disposable workspace only after its diff and artifacts are preserved. Do not let the agent delete the only copy of its own logs or snapshots.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to recover from an accidental overwrite or deletion
Tracked files
If a tracked file was changed or deleted, restore it from a known-good commit. To restore a single path:
git restore --source=<known-good-commit> -- path/to/fileGit can restore the index and working tree as well; choose the scope deliberately and inspect the result before committing. The command’s options and behavior are documented in Git restore.
If several files were affected, first save any legitimate changes you need to keep, identify the last trusted commit, and restore only the damaged paths. Avoid an indiscriminate hard reset when you have not separated good work from bad work.
Untracked and generated files
Git cannot restore files it never tracked. Use a sandbox snapshot, an immutable build artifact, or an external backup for generated output, uploads, local databases, and ignored files. OpenAI’s files and artifacts documentation describes preserving files and artifacts in an agent environment; the exact retention and snapshot behavior depends on the environment you use.
When the agent reached outside the workspace
Stop the process, revoke its credentials, and preserve logs before investigating. Determine which identity ran the command, which paths and services were touched, and whether any secrets were exposed. Restore from a trusted snapshot, rotate affected credentials, and tighten the boundary before rerunning the task. Do not simply restart the agent with the same permissions.
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Comparing implementation choices
When evaluating a coding-agent runtime or building your own harness, compare the controls that determine blast radius and recoverability.
| Comparison axis | Questions to ask |
|---|---|
| Filesystem isolation | Is the process in a container, virtual machine, or equivalent boundary? Can it reach host paths, sockets, or other users? |
| Path-rule granularity | Can you define read/write, read-only, and denied paths? Which rule wins when paths overlap? |
| Destructive-action approvals | Are deletion, overwrite, privilege changes, deployment, and out-of-workspace commands individually gated? |
| Identity and credentials | Does the agent use a separate identity with narrowly scoped, revocable credentials? |
| Network egress | Can you disable networking or allow only specific hosts and ports? |
| Snapshots and rollback | Are untracked files and generated artifacts captured, and can a workspace be restored atomically? |
| Audit detail | Does the log include the requested command, decision, identity, paths, output, diff, and rollback point? |
| Disposable testing | Can you test the policy on a fresh environment before exposing important data? |
Common weak approaches and their fixes
“The prompt says never delete files”
Instruction-following is not an enforcement boundary. A later prompt, a malicious file, or a tool error can override the intended behavior. Enforce deletion rules in the sandbox and approval layer.
“Git is the backup”
Git is excellent for tracked source, but it does not protect ignored files, untracked artifacts, external directories, or the backup repository itself. Keep snapshots or immutable artifacts for those items.
“I will approve everything manually”
Approval fatigue causes people to accept dangerous prompts without reading them. Reduce the number of prompts by denying unnecessary paths, then reserve approval for actions that truly need judgment. Show concrete commands and affected paths.
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Temporary access still permits damage during the access window. Time limits help, but pair them with least privilege, path restrictions, and snapshots. Revoke credentials immediately after the task.
“The workspace is isolated, so prompt injection does not matter”
Isolation limits the blast radius; it does not make injected instructions trustworthy. Inspect files and tool output, especially when they request deletion, secret disclosure, or a new network destination.
A practical preflight checklist
- The agent runs under a separate, least-privilege identity.
- The process is inside a deny-by-default sandbox or container.
- Only a disposable project directory is mounted read/write.
- Secrets, home configuration, production paths, and backups are denied or read-only.
- Network access is disabled or limited to an explicit allowlist.
- Deletion, overwrite, privilege changes, deployment, and out-of-workspace commands require approval.
- A clean Git worktree and branch exist for the task.
- A known-good commit and, where needed, a workspace snapshot exist before execution.
- Boundary tests confirm that denied and read-only paths are actually blocked.
- Audit logs are stored outside the agent’s writable workspace.
- A human will review the diff and test results before merging.
- Untracked and generated files have a separate recovery plan.
These controls work together: isolation limits reach, permissions limit actions, approvals stop high-impact operations, and checkpoints make recovery practical. If any one layer fails, the remaining layers should still keep the agent’s mistake from becoming a system-wide incident.
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