通信学报 ›› 2013, Vol. 34 ›› Issue (Z2): 64-68.doi: 10.3969/j.issn.1000-436x.2013.Z2.013

• 网络与信息安全 • 上一篇    下一篇

PyFuzzer:自动化高效内存模糊测试方法

李伟明,于俊清,艾少波   

  1. 华中科技大学 网络与计算中心,湖北 武汉 430074
  • 出版日期:2013-12-25 发布日期:2017-06-16
  • 基金资助:
    国家自然科学基金资助项目

PyFuzzer:automatic in-memory fuzz testing method

Wei-ming LI,Jun-qing YU,Shao-bo AI   

  1. Network and Computation Center,Huazhong University of Science and Technology,Wuhan 430074,China
  • Online:2013-12-25 Published:2017-06-16
  • Supported by:
    The National Natural Science Foundation of China

摘要:

针对传统模糊测试(fuzz testing)耗时、无法绕综合运用静态分析和动态跟踪技术的测试工具—PyFuzzer。整个过程高度自动化,通过WarFTPD、Serv-U等程序过有效性验证等缺陷,提出了基于快速内存模糊测试,进行测试,井和4n FTP Fuzzer进行对比,结果表明PyFuzzer能有效地发掘二进制程序中的各种漏洞,极大地提高了模糊测试的效率。

关键词: 模糊测试, 静态分析, 动态跟踪, 漏洞挖掘

Abstract:

Fuzz Testing is an effective method to mine all kinds of vulnerabilities.But the main drawbacks to current fuzz testing tools are:firstly,it produces high volume testing data and it’s extraordinary time consumption; secondly,if the accessing needs authentication,the greatest part of test data will be abandoned.PyFuzzer,a novel automatic in-memory fuzz testing tool combining static analysis,dynamic analysis and in-memory fuzz testing,was presented.The tool is highly automatic and effective.Compared with 4n FTP Fuzzer in testing WarFTPD and Serv-U,PyFuzzer can discover all vulnerabilities and improve test efficiency greatly.

Key words: fuzz testing, static analysis, dynamic tracking, vulnerabilities excavate

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