GitHub’s model for secret detection: Finding more secrets with less noise
TL;DR
GitHub’s context-aware secret classifier improves detection quality, raises weighted acceptance by 11.5%, and reduces median scan execution time by 86%. The post GitHub’s model for secret detection: Finding more secrets with less noise appeared first on The GitHub Blog.
Nauti's Take
The practical test for teams running AI workflows is the false-positive rate in their own codebase. The reported gains are strong aggregate metrics, so a small representative repository should be benchmarked against the current detector first, measuring missed secrets, false alarms, and scan time.
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