AI-powered fuzzing with the GitHub Security Lab Taskflow Agent
GitHub Security Lab's Taskflow Agent autonomously fuzzes C/C++ repositories with AFL++ and writes vulnerability reports.
GitHub Security Lab published the Fuzzing Taskflow, an LLM agent pipeline that fuzzes a C/C++ GitHub repository end to end. Given an owner/repo slug, it finds entry points, writes harnesses, runs AFL++, iterates on coverage, triages crashes, and drafts a report per unique bug. It defaults to Claude Sonnet 5 and executes afl-fuzz, clang, and model-chosen build commands on the host without a container.
- Agent writes harnesses, runs AFL++, reads coverage, and files bug reports.
- Default model is Claude Sonnet 5; pipeline state is stored in SQLite.
- Each harness is built as both an AFL binary and a coverage binary.
- Campaigns run on the host with no container; use a disposable environment.
- Vendors
- GitHub
- Products
- Taskflow AgentAFL++
- Organizations
- GitHub Security Lab
- AI models
- Claude Sonnet 5
From the original article
9 min read at github.blog
In this blog post, I explain how to use the new fuzzing taskflow based on the GitHub Security Lab Taskflow Agent AI framework. The post AI-powered fuzzing with the GitHub Security Lab Taskflow Agent appeared first on The GitHub Blog.
By Antonio Morales · github.blog
A short excerpt; the article and its images belong to the publisher. Summary, key facts and assessment above are AI-written from the article and can be wrong.