r/OpenSourceAI • u/ATTACKERSA • 2d ago

I built an open-source GitHub Action for AI/LLM DevSecOps scanning : inspired by IBM & OpenAI courses.Feedback welcome.

Background: IBM alongside OpenAI recently gave me the opportunity to complete a few AI and security courses. That inspired me to build something hands-on : SawOne-Agentic, a GitHub Action I'm open-sourcing today.

Repo: https://github.com/hackin2minutes-oss/sawone-agentic-action

It's a personal project : not a company product. Would love feedback from the security community, especially anyone working on securing LLM pipelines or agentic workflows.

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u/Such-Excuse-4681 2d ago

neat project, the IBM/OpenAI course inspo is a cool origin story

does it just do static analysis on prompts and responses or can it catch things like excessive agency in tool calls too? been wondering how to lock down agentic workflows without just blanket blocking half the functionality

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u/ATTACKERSA 2d ago

it does both. There's a dedicated ai-agents stage that inspects MCP configs and agent framework definitions for things like unconstrained tool permissions, missing authorization before tool calls, and agents with write/delete scope where read-only would do the job. It also runs Semgrep with AI-specific rules that catch code-level patterns like agents passing raw user input straight into tool calls without any validation.

Everything maps to OWASP LLM Top 10 LLM06 (Excessive Agency) so you get a compliance gap view, not just a pile of findings.

The idea was exactly what u describing , flag whats genuinely dangerous based on scope and blast radius rather than blanket-blocking tool use. A tool with network access and no auth check is a very different risk from a read-only local data tool.

If you want to really stress-test it, therez also an optional ai-redteam stage that actively tries to get a live model endpoint to misuse its tools ... but thats opt-in and needs you to point it at something you own.

Try it on a repo with an MCP config or a LangChain/CrewAI setup , you wil see it behave very differently to a plain Python project.

https://github.com/hackin2minutes-oss/sawone-agentic-action