OSS-Fuzz Gen is a Google project that uses large language models to automatically write fuzz targets for open-source software, extending the reach of the OSS-Fuzz continuous fuzzing service. The open-source project has around 1,400 stars on GitHub and remains in active development in 2026.
Fuzzing finds bugs and security vulnerabilities by feeding programs mutated inputs, but it depends on hand-written fuzz targets that many projects never get around to creating. OSS-Fuzz Gen attacks that bottleneck: it prompts LLMs with a project’s source code and APIs to generate candidate fuzz targets, then compiles, runs, and measures them, keeping the ones that build and measurably improve coverage. The repository includes the generation pipeline, an agent-based approach for iteratively fixing targets that fail to build or run, and a benchmark framework for evaluating how well different models perform at the task across real C and C++ projects. Results from this research have fed back into OSS-Fuzz itself, where LLM-generated targets have increased code coverage and surfaced real vulnerabilities in widely used libraries. Released under the Apache-2.0 license, the project sits at the intersection of AI for code and practical software security.
Free. OSS-Fuzz Gen is fully open source under the Apache-2.0 license; you supply any LLM access used for generation.
Security researchers, OSS-Fuzz maintainers, and AI-for-code researchers interested in using LLMs to scale fuzzing and vulnerability discovery.