adversarial-pr-review

Perform a security review on a GitHub pull request by analyzing the real diff at a pinned head SHA to spot exploitable changes. This process examines changed files for attack surfaces like auth, parsing, secrets, network calls, and resource limits before merging.

Adversarial threat modeling for pull request diffs is a review technique that generates security candidates based on exploitable changes, then attempts refutation by testing reachability, existing guards, and pre-existing context so only durable issues survive reporting.

Yes, you can use an automated security review to post comment-only feedback on a PR. It produces inline review threads and a summary without approving, requesting changes, or merging the pull request.

Yes, pull request security analysis applies to governed GitHub repositories when changes touch auth, parsing, secrets, network access, cryptography, or resource safety, ensuring exploitable modifications are flagged before integration.

The best way to find security bugs in a dependency or auth change is to run a hostile-eyes review that grounds on a pinned head SHA, applies diff-aware threat modeling, and refutes each candidate finding before reporting.

Security reviews report false positives on pull requests when findings skip refutation. Testing each candidate for reachability, existing guards, and pre-existing context ensures only durable, exploitable issues survive the final reporting stage.