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The reliable way to stop an AI agent from deleting or overwriting important files is defense in depth: run it in a deny-by-default sandbox, expose only a disposable project directory, give it a separate least-privilege identity, require approval for destructive or out-of-scope commands, isolate work with Git branches or worktrees, and keep snapshots or immutable backups for anything Git does not track.
These controls solve different problems. A sandbox limits what the process can reach; path rules decide which files it may read or change; approval gates decide whether a risky operation may run; Git and snapshots provide recovery after an allowed operation still goes wrong. Treat project files and tool output as untrusted input because prompt injection can persuade an agent to issue harmful commands.
Why one safety switch is not enough
An agent can damage data through several paths: a shell command such as rm -rf, an editor that saves over the wrong path, a script that recursively renames files, a credential that grants access outside the project, or instructions hidden in a file that manipulate the model. Blocking only one path leaves the others open.
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- Execution isolation: run the agent in a sandbox or container with a controlled filesystem and network.
- Path policy: deny access by default, then allow only the project paths required for the task.
- Authorization: pause for human approval before deletion, overwrite, privilege changes, or commands outside the workspace.
- Identity and credentials: use a dedicated account and narrowly scoped tokens rather than your personal or production credentials.
- Versioned work: use a separate Git branch or worktree and create checkpoints before risky edits.
- Recovery: retain snapshots or immutable artifacts for generated and untracked files.
- Auditability: record what the agent requested, what was approved, which paths changed, and how to roll back.
Configure all layers before granting the agent write access. If a platform cannot provide a layer, compensate with a stricter layer elsewhere—for example, a read-only mount plus mandatory approval when the platform has weak path rules.
Put the agent in a disposable sandbox
A sandbox is an isolated execution environment that can include a filesystem, shell, installed packages, mounted data, exposed ports, snapshots, and controlled access to external systems. OpenAI’s sandbox guidance explains how to separate the compute boundary from a trusted harness and use narrow credentials and mounts: OpenAI sandbox documentation.
Expose only a task workspace
Create a fresh directory or container for each task when practical. Mount the repository the agent must edit, but do not mount your entire home directory. Keep operating-system configuration, SSH keys, browser profiles, cloud credentials, password stores, production data, and backup locations outside the sandbox. If the agent needs reference material, mount a copy as read-only instead of exposing the original.
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Keep the approval service, policy files, and credential broker outside the agent’s writable filesystem. The agent should request an operation through the trusted harness; it should not be able to modify the code that decides whether the operation is allowed. A disposable environment also makes it possible to destroy and recreate the workspace after a suspicious run.
Control network access
Allow outbound connections only when the task needs them, and restrict destinations where your platform supports egress policies. Package installation, source control, and API calls should use narrowly scoped credentials. A filesystem sandbox does not by itself prevent data exfiltration through the network, so evaluate network controls separately.
Use deny-by-default path permissions
Path-level rules are the most direct way to prevent an otherwise authorized command from touching the wrong files. GitHub’s Copilot CLI documentation describes deny-by-default local sandboxing with read/write, read-only, and denied paths: GitHub Copilot CLI local sandboxing. VS Code documents the same categories and specifies that denied paths take precedence over read-only, which takes precedence over read/write: VS Code agent sandboxing.
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| Rule | Use it for | Effect |
|---|---|---|
| Read/write | The disposable project directory and narrowly selected build outputs | The agent may inspect and modify content within the path |
| Read-only | Reference documentation, dependency caches, or a baseline copy | The agent may inspect content but writes are rejected |
| Denied | Secrets, production paths, home-directory configuration, backup stores, and policy files | The agent cannot read or write the path |
Make the policy narrow and explicit
Start with no writable paths, then add the smallest directory that satisfies the task. Prefer a single repository subdirectory over a broad parent such as your home directory. Deny sensitive paths explicitly even if a broader allow rule exists, because the documented precedence makes a deny rule the strongest guard.
Watch for path aliases
Test absolute paths, relative paths, symbolic links, mounted volumes, and alternate spellings before relying on a policy. A rule for project/ must not accidentally expose a symlink that points to a secrets directory. Include generated directories in the policy rather than assuming the agent will only edit source files.
Require approval for destructive actions
Isolation and approval are separate controls. VS Code explains that approvals determine whether an action runs automatically or needs confirmation, while sandboxing limits the filesystem and network resources available to supported operations: VS Code agent sandboxing. Configure both.
Actions that should stop for confirmation
- Deleting one or more files, especially recursive deletion such as
rm -rorrm -rf. - Overwriting an existing file when the proposed diff is not already approved.
- Mass renames, moves, permission changes, or formatters that affect many paths.
git reset --hard, history rewrites, force pushes, and branch deletion.- Changing ownership, adding accounts, using
sudo, or modifying security policy. - Commands that access a path outside the approved workspace or open a network connection not listed in the task.
- Installing packages or running scripts whose source has not been reviewed.
Make the approval request reviewable
Show the exact command, working directory, resolved paths, identity, requested credentials, and an estimate of affected files. For an overwrite, display the before-and-after diff. Reject vague requests such as “clean up the project” unless the agent first proposes a concrete file list. Approval should be per operation or a tightly bounded batch, not a blanket “allow everything for this session.”
Use a human-in-the-loop policy
Microsoft’s agent-security guidance identifies per-tool permissions, per-action authorization checks, human approval for high-impact actions, sandboxing, and audit logging as complementary responsibilities: Microsoft shared responsibility for AI agents. Apply that model even for a local coding agent: automatic execution for low-risk reads and tests, confirmation for writes, and a hard block for credentials, production systems, and privilege escalation.
Run under a least-privilege identity
Create a dedicated operating-system account or service identity for the agent. Give it ownership or write permission only in the disposable workspace. Remove interactive access to your home directory, backup volume, production mounts, and system administration tools. A separate identity ensures that a prompt injection cannot inherit the permissions of your personal account.
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Scope credentials to the task
Issue short-lived, task-specific tokens with the minimum repository, package, or API permissions required. Keep secrets in a credential broker or injected environment that the agent cannot read back or write to disk. Never place long-lived private keys, cloud administrator tokens, or production connection strings in the mounted project directory.
Limit tool capabilities
Expose only the tools needed for the assignment. A code-editing task normally needs file reads, writes inside the workspace, and test execution; it rarely needs arbitrary process spawning, system package management, or unrestricted network access. Log every tool invocation, including denied attempts, so policy gaps become visible.
Isolate code changes with Git worktrees and checkpoints
A separate branch or worktree keeps the agent’s edits away from your primary checkout and makes review straightforward. Git’s worktree command can create a linked checkout and branch in one step:
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Checkpoint before the agent starts
- Commit or stash all intentional human changes in the main checkout.
- Create the worktree with the command above and verify the branch name with
git status. - Record the commit identifier as the rollback point.
- Tell the agent to operate only inside the worktree path.
- After the run, inspect
git diff,git diff --stat, and the list of untracked files before staging anything.
Git refuses to remove an unclean worktree unless forced, and git worktree lock protects a worktree from pruning. Use the lock when the worktree must remain available during a long task: Git worktree documentation.
Keep commits small and attributable
Ask the agent to make logically separate commits or leave changes unstaged for review. Small checkpoints let you revert one change without discarding unrelated work. Do not allow an agent to amend or rewrite reviewed commits unless that operation is explicitly approved.
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Restore tracked files from a known-good commit
For a tracked file, restore the content from a selected tree with:
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git restore --source=<known-good-commit> -- path/to/fileTo replace both the index and working-tree copy, include --staged --worktree:
git restore --source=<known-good-commit> --staged --worktree -- path/to/fileReview the resulting diff before committing. The command and its options are documented in Git restore documentation.
Protect untracked and generated files
Git cannot restore a file it never tracked. Build outputs, generated assets, local configuration, and uncommitted new files require a sandbox snapshot, an immutable artifact, or an external backup. OpenAI’s files and artifacts environment documentation describes file handling and artifact storage considerations: OpenAI files and artifacts.
Snapshot before high-risk operations
Create a snapshot immediately before bulk transformations, dependency upgrades, migrations, or automated refactors. Retain at least one copy that the agent cannot modify, and verify that restoration works before trusting the snapshot as a recovery plan. A backup that is mounted read/write in the same sandbox can be deleted along with the original.
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Every file, issue description, web page, test output, and generated log is untrusted input. Cloudflare warns that a file can contain text intended to steer a model into deleting other files and recommends checking tool results before acting outside the workspace and requiring approval for tools with side effects: Cloudflare filesystem tools guidance.
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Use a safe interpretation loop
- Have the agent identify instructions found in files separately from the user’s stated task.
- Ignore requests embedded in content that ask for secrets, policy changes, destructive commands, or unrelated uploads.
- Ask the agent to list intended paths and commands before execution.
- Review the list and the diff, then approve only the necessary operations.
- Investigate any attempt to leave the workspace, disable safeguards, or alter approval configuration.
Do not treat a plausible-looking README, test fixture, or tool response as an authorization source. Policy comes from the trusted task definition and approval layer, not from data the agent is analyzing.
Log the complete action chain
When an incident occurs, a command log alone is not enough. Record:
- The agent and operating-system identity.
- The user request, policy version, and tool call requested.
- The authorization decision, approver, timestamp, and reason for approval or denial.
- The resolved paths, mounts, network destinations, and credentials used.
- Command output, exit status, resulting diff, and files created or deleted.
- The commit, snapshot, or immutable artifact that provides rollback.
Microsoft includes action audit logging and monitoring in its agent responsibility model: Microsoft shared responsibility for AI agents. Store logs outside the agent’s writable workspace and protect them from alteration.
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When choosing an agent runtime or coding platform, compare controls rather than relying on a “safe mode” label.
| Control to compare | Questions to ask | Why it matters |
|---|---|---|
| Filesystem isolation | Is the agent in a container or separate host? Can it reach home directories or mounted volumes? | Defines the maximum blast radius of a command. |
| Path-rule granularity | Can you set read/write, read-only, and denied paths? Which rule wins on conflicts? | Fine-grained, deny-by-default rules prevent accidental broad access. |
| Destructive-command approval | Are deletion, overwrite, privilege changes, and out-of-workspace commands intercepted? | Provides a human decision point before irreversible effects. |
| Identity and credentials | Can the agent use a separate identity and short-lived, scoped tokens? | Limits access if the model or a tool is compromised. |
| Network egress | Can destinations, ports, and package registries be restricted and logged? | Reduces exfiltration and supply-chain risk. |
| Snapshots and rollback | Are snapshots available, immutable, and restorable for untracked files? | Protects data Git cannot recover. |
| Audit detail | Does the system retain commands, approvals, paths, diffs, and outcomes? | Enables incident investigation and policy tuning. |
| Disposable testing | Can you recreate the environment and test policies without touching production? | Lets you validate safeguards before granting write access. |
A practical rollout checklist
- Define the exact task and the only directories it needs.
- Create a disposable workspace or isolated container.
- Set all paths to denied, then allow the minimum project path as read/write.
- Mount references and baselines read-only; keep secrets and backups unmounted.
- Create a dedicated identity with no administrative privileges.
- Issue only short-lived credentials required for the task and restrict network destinations.
- Create a Git branch or worktree and record a known-good commit.
- Take a snapshot or immutable copy that the agent cannot alter.
- Configure approval for deletion, overwrite, mass changes, privilege escalation, and out-of-scope commands.
- Run a harmless test that verifies denied paths, read-only mounts, approval prompts, and logging.
- Start the agent, inspect proposed commands, and approve operations individually.
- Review the diff, tests, untracked files, logs, and snapshot status before merging or copying results elsewhere.
Troubleshooting common failure modes
The agent says a needed file is inaccessible
Check the resolved absolute path, symbolic links, mount configuration, and rule precedence. Add only the specific directory required, preferably read-only first, then rerun the harmless test. Do not respond by granting access to the entire home directory.
A formatter changed hundreds of files
Stop the run, preserve the current worktree for inspection, and compare the diff with the known-good commit. Restore selected tracked files with git restore, or discard and recreate the disposable worktree if the changes are broadly unwanted. Add an approval threshold for operations affecting more than the expected file count.
An untracked file was overwritten
Git cannot recover it unless a snapshot, immutable artifact, filesystem snapshot, or external backup exists. Locate the latest protected copy, restore it into a clean worktree, and then add a policy that requires approval before overwriting untracked paths.
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The agent attempted a command outside the workspace
Deny the request and inspect the triggering file, tool output, or prompt for injection. Review logs for earlier attempts, rotate any credential that may have been exposed, and rerun the task in a fresh environment with tighter network and path rules.
A backup disappeared with the project
The backup was not isolated from the agent. Rebuild from an immutable or offline copy, then move future snapshots outside all writable mounts and verify that the agent identity cannot delete them.
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