GitHub says new secret classifier cuts scan time and false positives

GitHub said its new context-aware secret classifier is improving secret scanning quality while lowering execution costs, with a two-stage pipeline that combines deterministic regex candidate generation and a fine-tuned ModernBERT model for context-based classification. In a post published on Oct. 13, 2026, GitHub described the scanner as a replacement for a previous LLM-based pipeline in the secret detection stack. The company said the new system produced an 11.5% improvement in repository owner-weighted acceptance, an 86% reduction in median post-push scan execution time, and more than 98% lower serving cost versus the remote LLM approach.

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