Witness: Detecting Vulnerabilities in Android Apps Extensively and Verifiably

Hongliang Liang, Tianqi Yang, Lin Jiang, Yixiu Chen, Zhuosi Xie
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引用次数: 2

Abstract

Existing studies on detecting vulnerabilities in apps have two main disadvantages: one is that some studies are limited to detecting a certain vulnerability and lack comprehensive analysis; the other is the lack of valid evidence for vulnerability verification, which leads to high false alarms rate and requires massive manual efforts. We propose the concept of vulnerability pattern to abstract the characteristics of different attacks, e.g., their prerequisites and attack paths, so as to support detecting multiple kinds of vulnerabilities. Also, we present a zero false alarms framework which can find vulnerability instances precisely and generate test cases and triggers to validate the findings, by combing static analysis and dynamic binary instrumentation techniques. We implement our method in a tool named Witness, which currently can detect 8 different types of vulnerabilities and is extensible to support more. Evaluated on 3211 popular apps, Witness successfully detected 243 vulnerability instances, with better precision and more proofs than four existing tools.
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见证:广泛且可验证地检测Android应用程序中的漏洞
现有的应用漏洞检测研究主要存在两大不足:一是部分研究局限于检测某个漏洞,缺乏全面分析;二是缺乏有效的漏洞验证证据,导致虚警率高,需要大量的人工工作。我们提出了漏洞模式的概念,对不同攻击的特征进行抽象,如攻击的前提条件、攻击路径等,从而支持检测多种漏洞。同时,结合静态分析和动态二进制检测技术,提出了一个零虚警框架,该框架可以精确地发现漏洞实例,并生成测试用例和触发器来验证发现的漏洞。我们在一个名为Witness的工具中实现了我们的方法,该工具目前可以检测8种不同类型的漏洞,并且可以扩展以支持更多。在3211个流行的应用程序中,Witness成功检测到243个漏洞实例,比现有的四个工具具有更高的精度和更多的证据。
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