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霍玮(1981-),男,河北秦皇岛人,博士,副研究员,博士生导师,CCF专业会员,主要研究领域为软件漏洞挖掘,安全评测,基于大数据的软件安全分析,智能终端系统及应用安全分析;贾晓启(1982-),男,博士,研究员,博士生导师,主要研究领域为网络攻防技术,操作系统安全,云计算安全;戴戈(1992-),男,硕士,主要研究领域为软件安全,软件漏洞挖掘;宋振宇(1985-),男,博士,助理研究员,主要研究领域为网络空间安全,网络技术;史记(1990-),男,博士,主要研究领域为软件安全,软件漏洞挖掘;刘宝旭(1972-),男,博士,研究员,博士生导师,CCF专业会员,主要研究领域为网络攻防技术,安全态势感知技术;龚晓锐(1973-),男,高级工程师,主要研究领域为网络攻防,软件逆向分析,Web安全,移动互联网安全;邹维(1964-),男,博士,研究员,博士生导师,CCF高级会员,主要研究领域为软件安全分析理论与技术,网络安全评测.
史记,E-mail:shiji@iie.ac.cn
中国科学院网络测评技术重点实验室资助项目；网络安全防护技术北京市重点实验室资助项目；中国科学院重点实验室基金（CXJJ-17S049）；国家重点研发计划（2016QY071405）
- HUO Wei
HUO Wei
Institute of Information Engineering, The Chinese Academy of Sciences, Beijing 100195, China;Key Laboratory of Network Assessment Technology(Institute of Information Engineering, The Chinese Academy of Science), The Chinese Academy of Sciences, Beijing 100195, China;Beijing Key Laboratory of Network Security and Protection Technology(Institute of Information Engineering, The Chinese Academy of Sciences), Beijing 100195, China;School of Cyber Security, University of Chinese Academy of Sciences, Beijing 100049, China
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在本站中查找 - DAI Ge
DAI Ge
Institute of Information Engineering, The Chinese Academy of Sciences, Beijing 100195, China;Key Laboratory of Network Assessment Technology(Institute of Information Engineering, The Chinese Academy of Science), The Chinese Academy of Sciences, Beijing 100195, China;Beijing Key Laboratory of Network Security and Protection Technology(Institute of Information Engineering, The Chinese Academy of Sciences), Beijing 100195, China;School of Cyber Security, University of Chinese Academy of Sciences, Beijing 100049, China
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在本站中查找 - SHI Ji
SHI Ji
Institute of Information Engineering, The Chinese Academy of Sciences, Beijing 100195, China;Key Laboratory of Network Assessment Technology(Institute of Information Engineering, The Chinese Academy of Science), The Chinese Academy of Sciences, Beijing 100195, China;Beijing Key Laboratory of Network Security and Protection Technology(Institute of Information Engineering, The Chinese Academy of Sciences), Beijing 100195, China;School of Cyber Security, University of Chinese Academy of Sciences, Beijing 100049, China
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在本站中查找 - GONG Xiao-Rui
GONG Xiao-Rui
Institute of Information Engineering, The Chinese Academy of Sciences, Beijing 100195, China;Key Laboratory of Network Assessment Technology(Institute of Information Engineering, The Chinese Academy of Science), The Chinese Academy of Sciences, Beijing 100195, China;Beijing Key Laboratory of Network Security and Protection Technology(Institute of Information Engineering, The Chinese Academy of Sciences), Beijing 100195, China;School of Cyber Security, University of Chinese Academy of Sciences, Beijing 100049, China
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JIA Xiao-Qi
Institute of Information Engineering, The Chinese Academy of Sciences, Beijing 100195, China;Key Laboratory of Network Assessment Technology(Institute of Information Engineering, The Chinese Academy of Science), The Chinese Academy of Sciences, Beijing 100195, China;Beijing Key Laboratory of Network Security and Protection Technology(Institute of Information Engineering, The Chinese Academy of Sciences), Beijing 100195, China;School of Cyber Security, University of Chinese Academy of Sciences, Beijing 100049, China
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在本站中查找 - SONG Zhen-Yu
SONG Zhen-Yu
Institute of Information Engineering, The Chinese Academy of Sciences, Beijing 100195, China;Key Laboratory of Network Assessment Technology(Institute of Information Engineering, The Chinese Academy of Science), The Chinese Academy of Sciences, Beijing 100195, China;Beijing Key Laboratory of Network Security and Protection Technology(Institute of Information Engineering, The Chinese Academy of Sciences), Beijing 100195, China
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在本站中查找 - LIU Bao-Xu
LIU Bao-Xu
Institute of Information Engineering, The Chinese Academy of Sciences, Beijing 100195, China;Key Laboratory of Network Assessment Technology(Institute of Information Engineering, The Chinese Academy of Science), The Chinese Academy of Sciences, Beijing 100195, China;Beijing Key Laboratory of Network Security and Protection Technology(Institute of Information Engineering, The Chinese Academy of Sciences), Beijing 100195, China;School of Cyber Security, University of Chinese Academy of Sciences, Beijing 100049, China
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在本站中查找 - ZOU Wei
ZOU Wei
Institute of Information Engineering, The Chinese Academy of Sciences, Beijing 100195, China;Key Laboratory of Network Assessment Technology(Institute of Information Engineering, The Chinese Academy of Science), The Chinese Academy of Sciences, Beijing 100195, China;Beijing Key Laboratory of Network Security and Protection Technology(Institute of Information Engineering, The Chinese Academy of Sciences), Beijing 100195, China;School of Cyber Security, University of Chinese Academy of Sciences, Beijing 100049, China
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Program of Key Laboratory of Network Assessment Technology, the Chinese Academy of Sciences; Program of Beijing Key Laboratory of Network Security and Protection Technology; Foundation of Key Laboratory of Network Assessment Technology, the Chinese Academy of Sciences (CXJJ-17S049); National Key Research and Development Program of China (2016QY0714 05)
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模糊测试被广泛应用于浏览器的漏洞挖掘，其效果好坏的决定因素之一是测试者编写的测试模式.针对特定测试模式实现成本高、生存时间短等问题，提出了一种基于模式生成的浏览器模糊测试器自动构造方法，通过解析已知漏洞触发样本，自动提取测试模式，对模式中每个模块应用传统的变异策略，完成畸形样本的自动生成.实验结果表明：针对5款浏览器的1 089个已知漏洞触发样本，平均仅用时11.168s即可完成1 089个不同模糊测试器的自动构建，远低于人为编写的时间消耗；随机选取其中10个模糊测试器分别对IE 10、IE 11、Firefox 54.0的全补丁版本进行测试，共产生57个不同的崩溃样本，发现1个高危未知漏洞，证明该方法具有较好的未知漏洞发现能力.
Fuzzing is widely used for browser vulnerability mining,and one of the key factors determining its effectiveness is the test pattern written by the tester.Considering that the test pattern is written with high cost and short survival time,in this article,an automatic construction of fuzzy tester based on pattern-generation is presented.By analyzing the known vulnerability samples and extracting the test pattern automatically,the traditional mutation strategy is then applied to each module in the pattern to complete the automatic generation of the abnormal samples.Experimental results show that in average it takes only 11.168 seconds to finish the automatic construction of 1 089 different fuzzy testers based on 1 089 known vulnerabilities for five browsers,which has much lower time-consumption than that required by testers themselves.Applying on IE 10,IE11 and Firefox 54.0 Web browser with randomly selected 10 fuzzy testers,the new method discovered a total of 57 different bugs,including a high-risk unknown vulnerability.This demonstrates that this method has better capability at finding the unknown vulnerability.
引用本文
霍玮,戴戈,史记,龚晓锐,贾晓启,宋振宇,刘宝旭,邹维.基于模式生成的浏览器模糊测试技术.软件学报,2018,29(5):1275-1287
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- 收稿日期:2017-07-01
- 最后修改日期:2017-08-29
- 录用日期:2017-11-21
- 在线发布日期: 2018-01-09
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