scanllm is an open-source Python tool that scans codebases to identify, govern, and visualize AI dependencies. It helps developers and security teams manage AI-related risks, generate SBOMs, and ensure compliance with governance standards. Ideal for teams integrating LLMs and AI components.
In the AI & ML space, scanllm takes a focused approach. It focuses on identifying and managing AI dependencies and security risks in software codebases. scanllm is an open-source project aimed at software developers and security engineers. The project is open source (MIT). It runs on the web, the command line, and API, and it can be self-hosted.
Behind scanllm is Sunil Sharma, and the product first shipped in 2025. The project is developed in the open on GitHub with 48 commits in the last 90 days. Across PulseGate's embedding index, scanllm has few near neighbours, marking it as relatively distinct. Among its 5 catalogued features are AI dependency scanning, governance tools, and visualization. It exposes integrations via a public API.
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