오늘은 내일 발표를 준비하느라 코테를 준비하지 못했다...
하지만 논문은 읽었지..
Fuzzing에 대해서 공부중인데 오늘은 아래 논문을 읽었다. 3까지..
fuzzing을 LLM을 이용해 하는 방법이다. tencent 연구원들이 썼다. 굉장히 최근에 나왔다.
이 논문을 읽으면서 또 읽어야 하거나 봐야하는 논문과 링크를 정리해 봤다.
Prompt Fuzzing for Fuzz Driver Generation
https://arxiv.org/abs/2312.17677
Prompt Fuzzing for Fuzz Driver Generation
Crafting high-quality fuzz drivers not only is time-consuming but also requires a deep understanding of the library. However, the state-of-the-art automatic fuzz driver generation techniques fall short of expectations. While fuzz drivers derived from consu
arxiv.org
https://github.com/google/oss-fuzz-gen
GitHub - google/oss-fuzz-gen: LLM powered fuzzing via OSS-Fuzz.
LLM powered fuzzing via OSS-Fuzz. Contribute to google/oss-fuzz-gen development by creating an account on GitHub.
github.com
Coverage-based Greybox Fuzzing as Markov Chain
https://dl.acm.org/doi/abs/10.1145/2976749.2978428
Coverage-based Greybox Fuzzing as Markov Chain | Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Se
CCS '16: Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security October 2016 1924 pages Copyright © 2016 ACM Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted with
dl.acm.org
Hopper:Interpretative Fuzzing for Libraries
https://dl.acm.org/doi/abs/10.1145/3576915.3616610
Hopper: Interpretative Fuzzing for Libraries | Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Secu
ABSTRACT Despite the fact that the state-of-the-art fuzzers can generate inputs efficiently, existing fuzz drivers still cannot adequately cover entries in libraries. Most of these fuzz drivers are crafted manually by developers, and their quality depends
dl.acm.org
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