The article explores the concept of AI-native Static Application Security Testing (SAST) and its potential to enhance traditional security tools. It discusses the limitations of current AI models in bug detection and emphasizes the importance of combining AI with static analysis for better results. The author also outlines a blueprint for integrating AI into security tooling.

This article discusses Datadog's new feature that uses AI to classify vulnerabilities identified by Static Application Security Testing (SAST) as true or false positives. The aim is to streamline the review process, allowing teams to focus on genuine security risks while filtering out distractions.