Typestate-Guided Fuzzer for Discovering Use-after-Free Vulnerabilities
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Yi Li | Yang Liu | Cheng Wen | Xiaofei Xie | Hongxu Chen | Haijun Wang | Yulei Sui | Shengchao Qin | Yuekang Li | Xiaofei Xie | S. Qin | Yi Li | Yulei Sui | Yuekang Li | Yang Liu | Hongxu Chen | Haijun Wang | Cheng Wen
[1] Erik van der Kouwe,et al. DangSan: Scalable Use-after-free Detection , 2017, EuroSys.
[2] Abhik Roychoudhury,et al. Directed Greybox Fuzzing , 2017, CCS.
[3] Abhik Roychoudhury,et al. Coverage-Based Greybox Fuzzing as Markov Chain , 2016, IEEE Transactions on Software Engineering.
[4] Chao Zhang,et al. CollAFL: Path Sensitive Fuzzing , 2018, 2018 IEEE Symposium on Security and Privacy (SP).
[5] Meng Xu,et al. QSYM : A Practical Concolic Execution Engine Tailored for Hybrid Fuzzing , 2018, USENIX Security Symposium.
[6] Dawn Xiaodong Song,et al. PerfFuzz: automatically generating pathological inputs , 2018, ISSTA.
[7] Juanru Li,et al. From Collision To Exploitation: Unleashing Use-After-Free Vulnerabilities in Linux Kernel , 2015, CCS.
[8] Shiping Chen,et al. Machine-Learning-Guided Typestate Analysis for Static Use-After-Free Detection , 2017, ACSAC.
[9] Crispan Cowan,et al. StackGuard: Automatic Adaptive Detection and Prevention of Buffer-Overflow Attacks , 1998, USENIX Security Symposium.
[10] Anja Feldmann,et al. Static Program Analysis as a Fuzzing Aid , 2017, RAID.
[11] Rongxin Wu,et al. Pinpoint: fast and precise sparse value flow analysis for million lines of code , 2018, PLDI.
[12] Shiping Chen,et al. Spatio-Temporal Context Reduction: A Pointer-Analysis-Based Static Approach for Detecting Use-After-Free Vulnerabilities , 2018, 2018 IEEE/ACM 40th International Conference on Software Engineering (ICSE).
[13] Eran Yahav,et al. Typestate verification: Abstraction techniques and complexity results , 2005, Sci. Comput. Program..
[14] Per Larsen,et al. Losing Control: On the Effectiveness of Control-Flow Integrity under Stack Attacks , 2015, CCS.
[15] Yang Liu,et al. MEMLOCK: Memory Usage Guided Fuzzing , 2020, 2020 IEEE/ACM 42nd International Conference on Software Engineering (ICSE).
[16] Wenke Lee,et al. Preventing Use-after-free with Dangling Pointers Nullification , 2015, NDSS.
[17] Yang Liu,et al. Steelix: program-state based binary fuzzing , 2017, ESEC/SIGSOFT FSE.
[18] Jingling Xue,et al. SVF: interprocedural static value-flow analysis in LLVM , 2016, CC.
[19] Hao Chen,et al. Angora: Efficient Fuzzing by Principled Search , 2018, 2018 IEEE Symposium on Security and Privacy (SP).
[20] Thorsten Holz,et al. REDQUEEN: Fuzzing with Input-to-State Correspondence , 2019, NDSS.
[21] Jin Song Dong,et al. Explaining Regressions via Alignment Slicing and Mending , 2021, IEEE Transactions on Software Engineering.
[22] Peng Li,et al. SAVIOR: Towards Bug-Driven Hybrid Testing , 2019, 2020 IEEE Symposium on Security and Privacy (SP).
[23] Shuvendu K. Lahiri,et al. Angelic Verification: Precise Verification Modulo Unknowns , 2015, CAV.
[24] Eran Yahav,et al. Effective typestate verification in the presence of aliasing , 2006, TSEM.
[25] Yves Younan,et al. FreeSentry: protecting against use-after-free vulnerabilities due to dangling pointers , 2015, NDSS.
[26] Christopher Krügel,et al. Driller: Augmenting Fuzzing Through Selective Symbolic Execution , 2016, NDSS.
[27] Xi Wang,et al. Linux kernel vulnerabilities: state-of-the-art defenses and open problems , 2011, APSys.
[28] Bihuan Chen,et al. Hawkeye: Towards a Desired Directed Grey-box Fuzzer , 2018, CCS.
[29] Zhenbang Chen,et al. Regular Property Guided Dynamic Symbolic Execution , 2015, 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering.
[30] Zhenbang Chen,et al. Symbolic Verification of Regular Properties , 2018, 2018 IEEE/ACM 40th International Conference on Software Engineering (ICSE).
[31] Andy Podgurski,et al. Measuring the strength of information flows in programs , 2009, TSEM.
[32] Angelos D. Keromytis,et al. SlowFuzz: Automated Domain-Independent Detection of Algorithmic Complexity Vulnerabilities , 2017, CCS.
[33] Herbert Bos,et al. VUzzer: Application-aware Evolutionary Fuzzing , 2017, NDSS.
[34] Chao Zhang,et al. MOPT: Optimized Mutation Scheduling for Fuzzers , 2019, USENIX Security Symposium.
[35] Shengchao Qin,et al. Locating vulnerabilities in binaries via memory layout recovering , 2019, ESEC/SIGSOFT FSE.
[36] Sukyoung Ryu,et al. SAFEWAPI: web API misuse detector for web applications , 2014, SIGSOFT FSE.
[37] Qinghua Zheng,et al. Dependence Guided Symbolic Execution , 2017, IEEE Transactions on Software Engineering.
[38] Yang Liu,et al. FOT: a versatile, configurable, extensible fuzzing framework , 2018, ESEC/SIGSOFT FSE.
[39] Koushik Sen,et al. FairFuzz: A Targeted Mutation Strategy for Increasing Greybox Fuzz Testing Coverage , 2018, 2018 33rd IEEE/ACM International Conference on Automated Software Engineering (ASE).
[40] Juan Caballero,et al. Undangle: early detection of dangling pointers in use-after-free and double-free vulnerabilities , 2012, ISSTA 2012.
[41] Dawn Xiaodong Song,et al. SoK: Eternal War in Memory , 2013, 2013 IEEE Symposium on Security and Privacy.
[42] Andrew Ruef,et al. Evaluating Fuzz Testing , 2018, CCS.
[43] Yang Liu,et al. Cerebro: context-aware adaptive fuzzing for effective vulnerability detection , 2019, ESEC/SIGSOFT FSE.
[44] Xiangyu Zhang,et al. ProFuzzer: On-the-fly Input Type Probing for Better Zero-Day Vulnerability Discovery , 2019, 2019 IEEE Symposium on Security and Privacy (SP).