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AI assistants are writing C sooner than anybody can evaluation it, however SAST scanners which were used to catch bugs like integer and buffer overflows have struggled with C code<\/a>.<\/p>\n Endor Labs\u2019 AI SAST scans run sooner than build-based SAST scans, and in accordance with checks it has run, AI SAST caught 96 of 102 recognized vulnerabilities in 4 embedded C tasks, which was 48 occasions the following finest buildless pattern-based SAST instrument, the corporate wrote. Endor\u2019s instrument isn’t primarily based on patterns however quite it makes use of AI to motive in regards to the code as a safety engineer would, and the corporate mentioned it outperformed 4 SAST instruments and frontier fashions Claude and Codex in benchmark trials<\/a>.<\/p>\n As Endor defined, \u201cthe hole comes all the way down to how the 2 normal approaches work, and every one fails the alternative method. A frontier mannequin pointed at a repo causes nicely in regards to the code it reads, but it surely solely reads a slice. A sample scanner reads each file however causes about none of them, so it flags what code resembles quite than what it does, and buries you in false positives. AI SAST pairs deterministic program evaluation (the identical call-graph and reachability engine we constructed for SCA) with LLM reasoning.\u201d<\/p>\n This system evaluation maps the entire codebase and traces how information strikes by means of it; the fashions motive over that structured context as an alternative of uncooked textual content. You get protection a mannequin alone can\u2019t attain, with much less of the noise a sample engine can\u2019t assist (see the whitepaper<\/a>\u00a0for extra particulars on how AI SAST works).<\/p>\nThe way it handles what patterns can\u2019t<\/h2>\n