IntelliGen: Automatic Driver Synthesis for Fuzz Testing

doi:10.1109/ICSE-SEIP52600.2021.00041

	IntelliGen: Automatic Driver Synthesis for Fuzz Testing
	Mingrui Zhang 1; Jianzhong Liu2 ; Fuchen Ma 1; Huafeng Zhang 3; Yu Jiang 1
	2021
会议录名称	2021 IEEE/ACM 43RD INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING: SOFTWARE ENGINEERING IN PRACTICE (ICSE-SEIP 2021)
ISSN	0270-5257
页码	318-327
发表状态	已发表
DOI	10.1109/ICSE-SEIP52600.2021.00041
摘要	Fuzzing is a technique widely used in vulnerability detection. The process usually involves writing effective fuzz driver programs, which, when done manually, can he extremely labor intensive. Previous attempts at autmiation leave much to he desired, in either degree. of automation or quality of output. In this paper, we propose IntelliGen, a framework that constructs valid fuzz drivers automatically. First, IntelliGen determines a set of entry functions and evaluates their respective chance of exhibiting a vulnerability.. Then, IntelliGen generates fuzz drivers for the entry functions through hierarchical parameter replacement and type inference. We implemented InielliGen and evaluated its effectiveness on rval-worid programs selected from the Android Open-Source Project, Ginigle's fuzzer-test-suite and industrial collaborators. Intel/Wen covered on average 1.08x-2.03x more basic blocks and 1.36x-2.06x more paths over state-of-he-art fuzz driver synthesizers FUDGE and FuzzGen. IntelliGen performed on par with manually written drivers and found 10 more hugs.
会议录编者/会议主办者	IEEE, Assoc Comp Machinery, IEEE Comp Soc, IEEE Tech Council Software Engn, ACM SIGSOFT ; Association for Computing Machinery (ACM) ; IEEE Computer Society ; IEEE Technical Council on Software Engineering (TCSE) ; Special Interest Group on Software Engineering (SIGSOFT)
关键词	Fuzz Testing Fuzz Driver Synthesis Software Analysis Vulnerability Detection Open source software Degrees of automation Driver program Fuzz driver synthesis Labour intensive Open source projects Real world projects Software analysis Type inferences Vulnerability detection
会议名称	43rd IEEE/ACM International Conference on Software Engineering - Software Engineering in Practice (ICSE-SEIP) / 43rd ACM/IEEE International Conference on Software Engineering - New Ideas and Emerging Results (ICSE-NIER)
会议地点	ELECTR NETWORK
会议日期	MAY 25-28, 2021
URL	查看原文
收录类别	CPCI-S ; CPCI ; EI
语种	英语
WOS记录号	WOS:000684234800033
出版者	IEEE COMPUTER SOC
EI入藏号	20213910950462
EI主题词	Software testing
EI分类号	723 Computer Software, Data Handling and Applications ; 723.5 Computer Applications
原始文献类型	Proceedings Paper
来源库	IEEE
引用统计	正在获取...
文献类型	会议论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/128008
专题	信息科学与技术学院_硕士生
作者单位	1.KLISS, BNRist, School of Software, Tsinghua Universiy 2.ShanghaiTech University 3.Huawei Technologies Co. Ltd, Beijing, China
推荐引用方式 GB/T 7714	Mingrui Zhang,Jianzhong Liu,Fuchen Ma,et al. IntelliGen: Automatic Driver Synthesis for Fuzz Testing[C]//IEEE, Assoc Comp Machinery, IEEE Comp Soc, IEEE Tech Council Software Engn, ACM SIGSOFT, Association for Computing Machinery (ACM), IEEE Computer Society, IEEE Technical Council on Software Engineering (TCSE), Special Interest Group on Software Engineering (SIGSOFT):IEEE COMPUTER SOC,2021:318-327.