POWER: Program Option-Aware Fuzzer for High Bug Detection Ability

被引:10
作者
Lee, Ahcheong [1 ]
Ariq, Irfan [1 ]
Kim, Yunho [2 ]
Kim, Moonzoo [3 ]
机构
[1] Korea Adv Inst Sci & Technol, Sch Comp, Daejeon, South Korea
[2] Hanyang Univ, Dept Comp Sci, Seoul, South Korea
[3] Korea Adv Inst Sci & Technol, Sch Comp, VPlusLab Inc, Daejeon, South Korea
来源
2022 IEEE 15TH INTERNATIONAL CONFERENCE ON SOFTWARE TESTING, VERIFICATION AND VALIDATION (ICST 2022) | 2022年
关键词
Automated test generation; fuzzing; program option configurations; dynamic function relevance; crash hug detection; dynamic analysis;
D O I
10.1109/ICST53961.2022.00032
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Most programs with command-line interface (CLI) have dozens of command-line options (e.g., -1, -F, -R for 1s) to alternate the operation of the programs. Thus, depending on the option configurations (i.e., a list of options like -1 -F and -F -R) applied during fuzzing, the lest coverage and crash detection results can vary significantly. In this paper, we propose a novel fuzzing technique POWER that detects more crashes than the cutting-edge fuzzers by actively constructing and carefully selecting various program option configurations. The salient idea of POWER is to enforce diverse executions of a target program by selecting a set of the option configurations each of which is far "different/distant" from the others in the set. Another core idea of POWER is to apply different fuzzing strategies to different input domains (i.e., option configurations and input Ides) to increase testing effectiveness within limited time budget. The experiment results on the 30 real-world programs show that POWER detects significantly more crash bugs than the state-of-the-art fuzzing techniques.
引用
收藏
页码:220 / 231
页数:12
相关论文
共 55 条
[1]  
[Anonymous], TESTING CONFIGURATIO
[2]  
[Anonymous], OSS FUZZ
[3]   Dynamic coupling measurement for object-oriented software [J].
Arisholm, E ;
Briand, LC ;
Foyen, A .
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 2004, 30 (08) :491-506
[4]  
Aschermann C., 2019, Symposium on Network and Distributed System Security, NDSS'19
[5]   Coverage-Based Greybox Fuzzing as Markov Chain [J].
Bohme, Marcel ;
Van-Thuan Pham ;
Roychoudhury, Abhik .
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 2019, 45 (05) :489-506
[6]   Angora: Efficient Fuzzing by Principled Search [J].
Chen, Peng ;
Chen, Hao .
2018 IEEE SYMPOSIUM ON SECURITY AND PRIVACY (SP), 2018, :711-725
[7]   SAVIOR: Towards Bug-Driven Hybrid Testing [J].
Chen, Yaohui ;
Li, Peng ;
Xu, Jun ;
Guo, Shengjian ;
Zhou, Rundong ;
Zhang, Yulong ;
Wei, Tao ;
Lu, Long .
2020 IEEE SYMPOSIUM ON SECURITY AND PRIVACY (SP 2020), 2020, :1580-1596
[8]   PTrix: Efficient Hardware-Assisted Fuzzing for COTS Binary [J].
Chen, Yaohui ;
Mu, Dongliang ;
Xu, Jun ;
Sun, Zhichuang ;
Shen, Wenbo ;
Xing, Xinyu ;
Lu, Long ;
Mao, Bing .
PROCEEDINGS OF THE 2019 ACM ASIA CONFERENCE ON COMPUTER AND COMMUNICATIONS SECURITY (ASIACCS '19), 2019, :633-645
[9]  
Chidamber S., 1991, IEEE T SOFTWARE ENG
[10]   Grey-box Concolic Testing on Binary Code [J].
Choi, Jaeseung ;
Jang, Joonun ;
Han, Choongwoo ;
Cha, Sang Kil .
2019 IEEE/ACM 41ST INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING (ICSE 2019), 2019, :736-747