Security Researcher Builds SAST Scanner for AI-Generated Code and Audits 3,800 Public Repositories
A developer released AigisSAST, a lightweight open-source static analysis tool written in pure Python with no external dependencies, specifically tuned to detect common mistakes made by AI coding assistants. The scanner was run across roughly 3,800 repositories ranging from small pet projects to popular open-source platforms. It identified thousands of potential secrets and misconfigurations, yet manual review reduced the number of genuine leaks to approximately 30 cases, mostly Telegram bot tokens, database credentials, and committed .env files. The project also examined 471 production-grade Telegram bots handling payments and VPN services, uncovering 31 repositories that exposed real credentials either in current code or in Git history. AigisSAST includes 21 detection rules, 193 regression tests, automatic remediation via the fix command, and seamless integration with GitHub Actions. The author deliberately avoided validating any discovered keys to stay within ethical research boundaries.
HabrOct 8, 2026Translated from Russian