Secure your code at scale with AI-driven vulnerability management

This article explores using Large Language Models (LLMs) to improve the accuracy of static code analysis tools by reducing false positives. Researchers found LLMs can effectively differentiate between genuine bugs and harmless code patterns flagged by static analyzers, significantly lowering noise and developer effort. This approach promises to make static analysis more practical and useful in real-world software development.