AI SAST refers to static application security testing where an AI reasons about code rather than matching patterns. Two distinct approaches exist: AI-native SAST (reasoning-based, finds IDORs, business logic flaws, broken access control) and AI-augmented SAST (traditional rule-based scanner with AI triage/autofix bolted on). AI-native SAST fills the gap between deterministic SAST and pentesting — it reads source code like a senior engineer, traces cross-file references, and catches logic flaws that have no syntactic signature. It's more expensive per scan than traditional SAST but cheaper than AI pentesting, making it best suited for high-stakes changes and release audits rather than every commit. The recommended layered approach: deterministic SAST on every commit, AI SAST on critical code paths, and AI pentesting against deployed environments for runtime validation.
