MemLock: memory usage guided fuzzing
Cheng Wen, Haijun Wang, Yuekang Li, Shengchao Qin, Yang Liu, Zhiwu Xu, Hongxu Chen, Xiaofei Xie, Geguang Pu, Ting Liu
摘要
Uncontrolled memory consumption is a kind of critical software security weaknesses. It can also become a security-critical vulnerability when attackers can take control of the input to consume a large amount of memory and launch a Denial-of-Service attack. However, detecting such vulnerability is challenging, as the stateof-the-art fuzzing techniques focus on the code coverage but not memory consumption. To this end, we propose a memory usage guided fuzzing technique, named MemLock, to generate the excessive memory consumption inputs and trigger uncontrolled memory consumption bugs. The fuzzing process is guided with memory consumption information so that our approach is general and does not require any domain knowledge. We perform a thorough evaluation for MemLock on 14 widely-used real-world programs. Our experiment results show that MemLock substantially outperforms the state-of-the-art fuzzing techniques, including AFL, AFLfast, PerfFuzz, FairFuzz, Angora and QSYM, in discovering memory consumption bugs. During the experiments, we discovered many previously unknown memory consumption bugs and received 15 new CVEs. CCS CONCEPTS • Security and privacy → Software security engineering.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了最后一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper40
- Typestate-guided fuzzer for discovering use-after-free vulnerabilitiesHaijun Wang, Xiaofei Xie, Yi Li, Cheng Wen 等ICSE 2020 · 被引用 107 次
- Nyx: Greybox Hypervisor Fuzzing using Fast Snapshots and Affine TypesSergej Schumilo, Cornelius Aschermann, Ali Abbasi, Simon Wörner 等USENIX Security 2021 · 被引用 102 次
- Free Lunch for Testing: Fuzzing Deep-Learning Libraries from Open SourceAnjiang Wei, Yinlin Deng, Chenyuan Yang, Lingming ZhangICSE 2022 · 被引用 91 次
- Fuzzing deep-learning libraries via automated relational API inferenceYinlin Deng, Chenyuan Yang, Anjiang Wei, Lingming ZhangFSE 2022 · 被引用 83 次
- Effective Seed Scheduling for Fuzzing with Graph Centrality AnalysisDongdong She, Abhishek Shah, Suman JanaS&P 2022 · 被引用 78 次
它引用的顶会 Paper16
- Coverage-based Greybox Fuzzing as Markov ChainMarcel Böhme, Van-Thuan Pham, Abhik RoychoudhuryCCS 2016 · 被引用 1,026 次
- Driller: Augmenting Fuzzing Through Selective Symbolic ExecutionNick Stephens, John Grosen, Christopher Salls, Andrew Dutcher 等NDSS 2016 · 被引用 1,021 次
- Directed Greybox FuzzingMarcel Böhme, Van-Thuan Pham, Manh-Dung Nguyen, Abhik RoychoudhuryCCS 2017 · 被引用 836 次
- Evaluating Fuzz TestingGeorge Klees, Andrew Ruef, Benji Cooper, Shiyi Wei 等CCS 2018 · 被引用 753 次
- VUzzer: Application-aware Evolutionary FuzzingSanjay Rawat, Vivek Jain, Ashish Kumar, Lucian Cojocar 等NDSS 2017 · 被引用 700 次
相关 Paper
- Prompt Fuzzing for Fuzz Driver GenerationYunlong Lyu, Yuxuan Xie, Peng Chen, Hao ChenCCS 2024 · 被引用 21 次
- GRIMOIRE: Synthesizing Structure while FuzzingTim Blazytko, Cornelius Aschermann, Moritz Schlögel, Ali Abbasi 等USENIX Security 2019 · 被引用 123 次
- FuzzGuard: Filtering out Unreachable Inputs in Directed Grey-box Fuzzing through Deep LearningPeiyuan Zong, Tao Lv, Dawei Wang, Zizhuang Deng 等USENIX Security 2020
- HTFuzz: Heap Operation Sequence Sensitive FuzzingYuanping Yu, Xiangkun Jia, Yuwei Liu, Yanhao Wang 等ASE 2022 · 被引用 14 次
- Fuzzing Error Handling Code using Context-Sensitive Software Fault InjectionZu-Ming Jiang, Jia-Ju Bai, Kangjie Lu, Shi-Min HuUSENIX Security 2020
