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I got tired of 200 noisy SAST alerts, so I built an AI engine that auto-writes Git patches

A developer built BugZ AI, an open-source vulnerability scanner and automated patching engine that generates exact Git patch files to fix security issues. The tool uses Next.js, Convex, Clerk, and AI APIs from Gemini and OpenAI to validate and produce syntactically correct patches, reducing noise from traditional SAST tools. The MVP is live at bugz-ai.vercel.app.

read2 min views1 publishedAug 11, 2026

Traditional security tools like SonarQube or Snyk are great at one thing: throwing a wall of 200 warnings at you, half of which are false positives, and leaving you to figure out how to manually fix them.

I wanted a faster, more actionable security workflow for my own projects. Instead of just flagging a line number and saying "potential memory leak here," I wanted a tool that synthesizes an exact .patch diff file I can review and apply in seconds.

So I built BugZ AI—an open-source vulnerability scanner and automated patching engine.

The Architecture & Stack

To keep the UI real-time and snappy while LLMs crunch through repository files, I used this stack:

Frontend: Next.js (App Router) + Tailwind CSS for a dark-mode, terminal-focused UI. Backend & Database: Convex. Handling real-time scan state updates and streaming execution logs to the UI without managing WebSockets manually was ridiculously clean with Convex.

Authentication: Clerk for zero-friction user management.

AI Engine: Gemini / OpenAI APIs with structured JSON output enforcement to guarantee valid unified Git patch syntax.

Key Challenge: Generating Valid Git Patches

Getting an LLM to explain a bug is easy. Getting an LLM to generate a syntactically correct .patch file that git apply won't reject is the hard part.

To solve this, the pipeline:

Parses the raw AST / code context.

Prompts the LLM with strict unified diff formatting constraints.

Validates line counts and chunk headers (@@ -line,count +line,count @@) before presenting the patch file in the UI.

How it looks in action

When you import a repo or paste code snippets into BugZ:

It runs a deep security audit looking for async state bugs, unhandled API edge cases, or injection vulnerabilities.

It streams live execution logs directly to your dashboard.

It generates a executable .patch file that you can inspect side-by-side or copy straight to your terminal.

Try it out & Feedback BugZ is live in early MVP stage right now. I'd love to hear your thoughts, bug reports, or ideas on how to improve the patch syntax generation!

Live Demo: bugz-ai.vercel.app Stack Highlights: Next.js, Convex, Clerk, Tailwind, AI APIs

Drop your thoughts in the comments below! What SAST tool features do you wish existed in your daily dev workflow?

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