A Novel Method Makes Concolic System More Effective

Hongliang Liang, Zhengyu Li, Minhuan Huang, Xiaoxiao Pei
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Abstract

Fuzzing is attractive for finding vulnerabilities in binary programs. However, when the application's input space is huge, fuzzing cannot deal with it well. For discovering vulnerabilities more effective, researchers came up concolic testing, and there are much researches on it recently. A common limitation of concolic systems designed to create inputs is that they often concentrate on path-coverage and struggle to exercise deeper paths in the executable under test, but ignore to find those test cases which can trigger the vulnerabilities. In this paper, we present TSM, a novel method for finding potential vulnerabilities in concolic systems, which can help concolic systems more effective for hunting vulnerabilities. We implemented TSM method on a wide-used concolic testing tool-Fuzzgrind, and the evaluation experiments show that TSM can make Fuzzgrind hunt bugs quickly in real-world software, which are hardly found ever before.
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一种新的方法使圆锥系统更有效
模糊测试对于发现二进制程序中的漏洞很有吸引力。然而,当应用程序的输入空间很大时,模糊分析不能很好地处理它。为了更有效地发现漏洞,研究者们提出了集合测试,近年来对集合测试进行了大量的研究。设计用于创建输入的concolic系统的一个常见限制是,它们通常专注于路径覆盖,并努力在被测试的可执行文件中执行更深层次的路径,但忽略了发现那些可能触发漏洞的测试用例。本文提出了一种基于TSM的安全漏洞检测方法,可以帮助安全漏洞检测系统更有效地寻找安全漏洞。我们将TSM方法应用于广泛使用的集成测试工具Fuzzgrind上,评估实验表明TSM方法可以使Fuzzgrind快速地在实际软件中发现以前很难发现的bug。
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