GitHub adopts cheaper AI model to catch secrets developers leave in code

GitHub has trained a credential classifier to improve generic secret detection and reduce false alerts. The new pipeline cut median post-push scan execution time by 86% and model serving costs by more than 98% compared with its previous large language model (LLM) pipeline. GitHub’s secret scanning covers two stages of development. Push protection checks changes before a push is accepted, helping developers prevent credential leaks. Post-push scanning examines repository content and creates alerts for potential … More → The post GitHub adopts cheaper AI model to catch secrets developers leave in code appeared first on Help Net Security .