oss-fuzz-gen and PromeFuzz
These are competitors—both use LLMs to automatically generate fuzzing harnesses, with oss-fuzz-gen being Google's production-grade framework integrated with OSS-Fuzz infrastructure, while PromeFuzz offers an alternative knowledge-driven approach for the same core problem.
About oss-fuzz-gen
google/oss-fuzz-gen
LLM powered fuzzing via OSS-Fuzz.
This framework helps software security teams automate and enhance their fuzz testing efforts by using Large Language Models (LLMs) to generate new fuzz targets for C, C++, Java, and Python projects. It takes existing project code and an LLM as input, then outputs new fuzzing code and detailed reports on its effectiveness, including crash discovery and code coverage. This is intended for security engineers and quality assurance professionals focused on identifying vulnerabilities in open-source and proprietary software.
About PromeFuzz
pvz122/PromeFuzz
PromeFuzz: A Knowledge-Driven Approach to Fuzzing Harness Generation with Large Language Models
PromeFuzz helps software developers and security engineers automatically generate robust test cases, known as fuzzing harnesses, for C and C++ libraries. It takes a library's source code, documentation, and API usage patterns as input, then creates effective fuzzing harnesses that can uncover hidden vulnerabilities and improve code coverage. This is ideal for those responsible for software quality assurance and security testing.
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