GitHub Security Lab shows an LLM agent running AI-driven fuzzing for C/C++ projects
Original titleAI-powered fuzzing with the GitHub Security Lab Taskflow Agent
GitHub Security Lab describes the Fuzzing Taskflow, an LLM agent pipeline that identifies entrypoints, writes harnesses, runs AFL++, reads coverage reports, and triages crashes for C/C++ repositories.
The agent makes decisions while MCP tools handle execution, and state is stored in a SQLite database.
The post also warns that the taskflow runs AFL and build commands directly on the host, so it should be used only in disposable environments without elevated privileges.
The post explains how an LLM agent automates fuzzing steps like harness writing, coverage gap chasing, and crash triage, with a runnable workflow and design tradeoffs.
Source: GitHub Blog · AI & ML · github.blogPublished · added here