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1Clear out junk files and repair common Windows errors2Fix the driver behind crashes, sound loss and screen glitches3Repair Windows errors before they cause bigger problems“Should I give Codex full access?” skips three things: what the task is, how much access that task needs, and how much oversight you want while it runs. Start with the work. Then pick the sandbox and approval settings that fit it. This is an editorial recommendation built on how OpenAI documents the two controls, not a universal best setting.
Two controls, two jobs
OpenAI’s Running Codex safely at OpenAI (May 8, 2026) describes the sandbox as the technical boundary: where Codex can write, whether it can reach the network, and which paths are protected. Approval policy decides when Codex has to stop and ask before crossing that boundary. The page puts it plainly: “Approvals and sandboxing work together.” The page is an official statement and does not name an individual author.
“Full access” is therefore not one switch. It blurs a wide boundary with a lack of prompts, and those are separate decisions. A tight sandbox with frequent prompts, a wide sandbox with prompts, and a wide sandbox with none are three different risk profiles.
Ask these five questions instead
OpenAI’s materials establish these as the dimensions that matter. Exact options change by version and surface, so check the one you use.
#1 Best Overall
| Question | What it determines |
|---|---|
| Which files must Codex write? | Writable scope: one folder, one branch, or more |
| Does the task need the network? | Whether network access is off, or granted per request |
| Should actions outside the boundary need your approval? | Approval policy |
| How closely will you watch? | How much ongoing human oversight the workflow assumes |
| Which interface and managed configuration apply? | The CLI, app and cloud do not necessarily share identical boundaries |
What the defaults look like
Codex app
OpenAI’s Introducing the Codex app says the app uses configurable system-level sandboxing. By default, agents are limited to editing the working folder or branch and must ask permission for elevated actions such as network access. That article was published roughly eight months before this one was written, so recheck current app behavior.
Codex CLI
The OpenAI Help Center’s CLI getting-started page describes Full Auto as autonomous operation inside a sandboxed, network-disabled environment scoped to the current directory. Despite the name, that is not unbounded access. The same page advises confirming that the sandbox can reach the directories your task needs, which is often the real fix when a task fails on a permissions problem, rather than loosening everything. It also answers the common question “How do I change approval modes?”
Version-specific note for newer CLIs
The Help Center page Using Codex with your ChatGPT plan covers the question “Why does Codex fail to start with approval_policy = “untrusted”?” For CLI 0.149.0 and later, it says approval_policy = "untrusted" is unsupported. It offers a restrictive alternative: sandbox_mode = "read-only" with approval_policy = "on-request". This is version-specific, so check which CLI version you run.
Why wider access is a real trade-off
OpenAI’s product safety material (Introducing upgrades to Codex) treats default sandboxing and disabled network access as risk-reduction measures. Widening either removes a safeguard. Sometimes that is justified: an install step may need the network, or a refactor may span several directories. The point is to grant the specific capability the task needs, not everything at once.
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Reducing approval fatigue without removing the boundary
Constant prompts push people toward blanket access. OpenAI Alignment’s April 30, 2026 post on Auto-review describes another option. OpenAI reports that Codex sessions in Auto-review mode stop for human approval “roughly 200x less often” than in manual approval mode, and that Auto-review approves “around 99%” of the small fraction of actions it reviews. Both figures are OpenAI’s own, describe that Codex deployment, and are not independent evaluations or measurements of AI coding agents in general.
The practical reading: fewer interruptions do not require dropping the sandbox. An extra review layer is a different tool from removing the boundary.
Rank #4
A practical way to choose
- Write down the task and the files it must change.
- Start from the restrictive end, such as read-only with on-request approval, or the app’s folder-or-branch default.
- If Codex stalls, identify what it was blocked on: a directory, the network, or a protected path.
- Grant only that capability, ideally for that session.
- If you are on a managed or team setup, check what your administrators have configured, since managed controls can govern network access.
OpenAI’s materials do not establish a universal best setting, and no independent comparative testing of these configurations was found. Treat the sequence above as a reasoned starting point, not a benchmarked rule.
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