DEV Community case study proposes pre-application safety gate for AI-generated code patches

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A DEV Community article presents a case study for a security gate designed to vet code patches written by AI agents. The gate requires patches to pass a pre-written allowlist and a specific test command before being applied to a codebase. It operates on a "fail-closed" principle, rejecting any patch that modifies forbidden files or lacks the required test command. The study provides a Python script example to implement this review process locally, using only the standard library. The goal is to prevent unintended changes to sensitive files like deployment scripts or environment samples.

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