GitHub Security Lab automates C/C++ fuzzing with AI-driven taskflows
GitHub’s Security Lab released Fuzzing Taskflow, an autonomous pipeline for vulnerability discovery in C/C++ repositories. By specifying a GitHub repo, the system—built on its Taskflow Agent—handles entry-point identification, harness creation, AFL++ execution, crash triage, and report generation without human input. The lab reported in January 2026 that the underlying agent framework had…
Key points
- GitHub Security Lab’s Fuzzing Taskflow automates C/C++ fuzzing end-to-end with AI agents, from harness creation to report generation
- Built on Taskflow Agent framework, which previously found 30 real vulnerabilities during CodeQL triage in 2026
- Separates LLM decision-making from tool execution (AFL++, clang) and uses coverage feedback loops with time budgets up to 960 seconds
The tool separates decision-making (handled by LLM agents) from execution (via MCP tools like AFL and clang). It iteratively improves coverage by doubling time budgets (from 30 seconds to 960 seconds) and halting when growth plateaus. GitHub notes the pipeline generates vulnerability reports but does not patch them. Availability, pricing, and regional restrictions are unspecified.
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GitHub Releases Fuzzing Taskflow: Automating C/C++ Vulnerability Discovery with AI
note.com · 12 October 2026
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