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GitHub's new secret detection model improves accuracy and speed

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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.

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