LLM-based vulnerability prioritization hampered by high false-positive rates

Current large language models struggle to accurately prioritize security vulnerabilities due to a lack of contextual awareness and high false-positive rates. This limitation increases the operational burden on application security teams, indicating that automated AI-driven remediation remains immature for enterprise-grade security workflows.