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About this paper
Yanbang Sun, Quan Luo, Yuelin Wang, Qian Chen, Benjin Liu, Ruiqi Chen, Qing Huang, Xiaohong Li and 1 more
SemFuzz is a black-box fuzzing framework that employs large language models to automatically extract and formalize semantic rules from network protocol RFCs, enabling the generation of intent-driven test cases to uncover deep semantic vulnerabilities. The framework successfully identified 10 confirmed vulnerabilities, including 5 previously unknown ones and 4 CVEs, across seven widely used protocol implementations.
Key insights
- Automatically extracting and formalizing semantic rules from natural language RFCs using LLMs effectively guides precise, semantics-aware test case generation for protocol boundary conditions.
- The translation of mutation strategies into high-level action sequences is crucial for generating syntactically valid yet semantically targeted test cases, particularly for complex binary protocols.
- The overall architectural design and semantics-aware framework of SemFuzz contribute more to its effectiveness in vulnerability detection than the specific choice of the underlying large language model.
Summary by alphaXiv.
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