Wiz security researchers employed AI-powered reverse engineering to discover a high-severity vulnerability in GitHub that manual analysis would have been prohibitively expensive and time-consuming to uncover. The vulnerability class and affected component remain under embargo pending patching, but the discovery demonstrates a shift in vulnerability research methodology. Machine learning acceleration reduces the engineering burden of analyzing compiled binaries and proprietary code without source access. GitHub has been notified and is preparing a fix. This approach scales vulnerability research beyond the constraints of manual code review. Organizations defending against supply chain attacks should monitor GitHub's security advisory channels for details once disclosure occurs. The technique signals that AI tooling reshapes the economics of finding zero-days, potentially accelerating both offensive and defensive research cycles.