LLMs can be used to analyze code and automatically identify the potential attack surface. They can also generate the corresponding test harnesses needed for self-learning AI. Self-learning AI can then “attack” these entry points while continuously refining test cases based on coverage feedback. When combined, these two forms of AI provide a more automated and scalable testing model, enabling development teams to secure self-written code, third-party components, and AI-generated code at scale.