GitHub deploys ModernBERT-based context-aware classifier to reduce secret scanning noise
GitHub replaced an LLM-heavy secret-scanning pipeline with a two-stage system: fast regex candidate generation followed by a fine-tuned ModernBERT classifier that evaluates each candidate plus surrounding context. The new pipeline yields an 86% faster median post-push scan execution time, over 98% lower serving cost versus the previous LLM-based approach, and an 11.5% improvement in user acceptance by reducing false positives.