GitHub's new secret detection model improves accuracy and speed
GitHub has developed a context-aware classifier for detecting secrets in code. The new model increases weighted acceptance of detected secrets by 11.5%. It also reduces the median scan execution time by 86%. The improvements aim to find more genuine security issues while generating fewer false positives.
This is an AI-generated summary. ShortSingh links to the original source for the complete article.


Discussion (0)
Log in to join the discussion and vote.
Log in