Auto classifier blocking daybreak blue building temporary scripts to probe the impact of changes

Open 💬 2 comments Opened Aug 12, 2026 by discorev
💡 Likely answer: A maintainer (github-actions[bot], contributor) responded on this thread — see the highlighted reply below.

What version of Codex CLI is running?

codex-cli 0.147.0

What subscription do you have?

Pro 20x

Which model were you using?

gpt-daybreak-blue-latest

What platform is your computer?

Darwin 25.6.0 arm64 arm

What terminal emulator and version are you using (if applicable)?

_No response_

Codex doctor report

What issue are you seeing?

Following the release of the new daybreak blue model and per the release announcement "We are strongly encouraging Daybreak customers using Codex to switch from full-access mode to auto-review mode" I have codex configured to use auto_review.

approval_policy = "on-request"
approvals_reviewer = "auto_review"

I was using daybreak to make changes to a scanner that gates if JavaScript is safe or represents a known or unknown risk. The scanner was resolving to unknown risk in an area that should have been gated to known risk and other areas that should have been gated to safe. Daybreak had successfully evaluated the potential risk and was using a temporary script to evaluate possible changes. The auto-classifier rejected this local script as "not fixing the production issue" until all attempts were exhausted.

What steps can reproduce the bug?

Uploaded thread: 019ff2f0-8320-77a2-97ea-affebacf4066

What is the expected behavior?

I would expect the classifier not to prevent a cyber-aware model being able to use diagnostic to probe changes prior to implementation in a security critical path.

Additional information

_No response_

View original on GitHub ↗

2 Comments

github-actions[bot] contributor · 16 days ago

Potential duplicates detected. Please review them and close your issue if it is a duplicate.

  • #37930
  • #37854

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discorev · 16 days ago

Neither are duplicates. My issue is around the auto-reviewer against behavior rather than user messages and is not about cyber refusals.