Using LLMs to Find and Prioritize Vulnerabilities Is No Easy Task

Recent large language models (AI systems trained on huge amounts of text data) struggle when used to find and prioritize security vulnerabilities (weaknesses in software that attackers can exploit) because they produce many false positives (incorrect alerts about problems that don't actually exist) and ignore the context of security scans, creating extra work for application security professionals.