Your coding agent should run routine work only inside a defined boundary: decide both which actions it may take without approval and which files, network resources, and credentials its environment can reach. For everyday work in a local project, a narrow writable project area with approval required for actions outside it is a practical starting point. Use stronger isolation for untrusted code.
Approval and sandboxing control different risks
An approval policy determines when the agent pauses or requests review. A sandbox limits what the agent’s commands can access, such as files and network resources. One does not replace the other: frequent prompts do not prevent a command from reaching sensitive resources once approved, and a sandbox does not necessarily decide which actions require your confirmation.
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OpenAI’s Codex documentation puts the distinction plainly: “The sandbox defines which files and network resources ChatGPT can access.” Its approval settings determine when the agent pauses. A prompt telling an agent to be careful is not an enforced boundary; check the actual controls provided by the product and environment.
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Choose a boundary for routine local work
For a project you trust, allow the agent to read and edit only the project area it needs, while requiring approval when it needs to work beyond that boundary. Limit outbound network access to what the task requires, and avoid exposing unrelated files or credentials. This balances automation with a meaningful point at which you can review a higher-impact action.
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Before allowing a request, consider what it changes and what it can reach—not just whether the command looks familiar. A command that installs a dependency, runs a project script, or contacts a service may have effects beyond the visible edit. Review the proposed action and its context before approving it.
How Codex describes its controls
OpenAI documents separate sandbox modes and approval policies for Codex. The common sandbox modes listed are read-only, workspace-write, and danger-full-access; documented approval policies include on-request and never. OpenAI describes workspace-write with on-request as a lower-risk local automation preset. danger-full-access together with never removes filesystem and network sandbox boundaries.
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These names do not guarantee that every Codex client exposes identical options or defaults. The available controls can depend on the client, execution environment, local configuration, and organization requirements. Verify the selected mode in the specific surface you use rather than assuming a setting from another setup applies.
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How Claude Code describes its controls
Anthropic documents several Claude Code permission modes: manual/default, acceptEdits, plan, auto, dontAsk, and bypassPermissions. Their behavior is specific to Claude Code and should not be treated as a one-to-one match for another agent’s settings.
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In manual mode, Claude Code generally asks before Bash commands, with built-in read-only commands as an exception; reads in configured working directories do not require a prompt. Permission rules can allow, ask about, or deny actions. Anthropic says the order is deny, then ask, then allow, and that “Permission rules are enforced by Claude Code, not by the model.”
Anthropic recommends using bypassPermissions only in an isolated environment, such as a container or virtual machine, where the tool cannot cause damage. Skipping prompts is not a substitute for limiting what the process can access.
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Why an allowlist is not a complete safety boundary
An allowlist can approve commands that appear safe while missing how the shell or the surrounding environment changes their meaning. In an article posted August 18, 2026, Docker described CVE-2026-22708 as a Cursor Auto-Run allowlist bypass. Docker reported that shell built-ins such as export, typeset, and declare could alter environment variables before a later approved command ran, potentially causing unintended behavior.
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1Repair Windows errors before they cause bigger problems2Fix the driver behind crashes, sound loss and screen glitches3Clear out junk files and repair common Windows errorsDocker’s account says Pillar Security disclosed the flaw on January 14, 2026, and that Cursor rated it High and patched it in version 2.3. This is Docker’s vendor-authored account, not an independent assessment of the vulnerability; patch status is time-sensitive. The practical lesson is that command approval rules should not be your only boundary. Restrict the environment and resources the agent can reach as well.
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What isolation changes—and what it does not
Docker’s documentation describes its Sandboxes as microVMs with a separate kernel and a network policy boundary. Those controls can separate agent execution from the host, but the actual exposure depends on what is mounted, forwarded, and allowed by the configuration. Docker is a vendor discussing its own product, so treat its architecture and protection claims as vendor documentation.
Quick Recap
- Workspace: Docker says a direct workspace mount is read-write, so changes are visible on the host. Clone mode instead uses a private clone. Know which mode is active before running an agent.
- Network: Outbound TCP follows network policy. Check which destinations are allowed and whether other protocols or services are accessible under the actual configuration.
- Credentials: A forwarded SSH-agent socket can let sandbox processes request signatures without giving them the private keys. That still grants the process a way to authenticate through the agent; forwarding is not the same as having no credential access.
- Shared resources: Supported agents may share a skills store. A shared path or socket can connect sandbox activity to resources outside the private execution environment, so inspect those exceptions.
Check these settings before enabling unattended work
- Confirm the active permission mode and sandbox for the client and environment you are using.
- Limit writable locations to the project or task area; determine whether edits affect the host working tree or a private clone.
- Restrict network access to necessary destinations, and check which protocols the policy covers.
- Keep untrusted code away from host credentials and other sensitive resources; inspect forwarded sockets and shared stores.
- Check which permission rules are allowed, require approval, or are denied, and how broadly each rule applies.
- Review changes and decisions, and make sure you can discard or restore the environment if execution goes wrong.
- Use a more isolated environment for untrusted repositories or inputs, rather than relying on an allowlist or model instruction alone.
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