Reducing Noise: Hybrid Static Application Security Testing–Large Language Model Pipeline for Code Security

Researchers created a hybrid system that combines SAST (static application security testing, which automatically scans code for vulnerabilities) with LLMs (large language models) to better filter and prioritize security alerts. The system reduced false positives (incorrect security warnings) by 91% in real deployments by using AI to intelligently triage findings and generate automated exploit examples.