NIVAnalyzer: A Tool for Automatically Detecting and Verifying Next-Intent Vulnerabilities in Android Apps

Junjie Tang, Xingmin Cui, Ziming Zhao, Shanqing Guo, Xin-Shun Xu, Chengyu Hu, Tao Ban, Bing Mao
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引用次数: 8

Abstract

In the Android system design, any app can start another app's public components to facilitate code reuse by sending an asynchronous message called Intent. In addition, Android also allows an app to have private components that should only be visible to the app itself. However, malicious apps can bypass this system protection and directly invoke private components in vulnerable apps through a class of newly discovered vulnerability, which is called next-intent vulnerability. In this paper, we design an intent flow analysis strategy which accurately tracks the intent in smali code to statically detect next-intent vulnerabilities efficiently and effectively on a large scale. We further propose an automated approach to dynamically verify the discovered vulnerabilities by generating exploit apps. Then we implement a tool named NIVAnalyzer and evaluate it on 20,000 apps downloaded from Google Play. As the result, we successfully confirms 190 vulnerable apps, some of which even have millions of downloads. We also confirmed that an open-source project and a third-party SDK, which are still used by other apps, have next intent vulnerabilities.
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NIVAnalyzer:用于自动检测和验证Android应用程序中的下一个意图漏洞的工具
在Android系统设计中,任何应用都可以通过发送一个名为Intent的异步消息来启动另一个应用的公共组件,从而促进代码重用。此外,Android还允许应用程序拥有私有组件,这些组件应该只对应用程序本身可见。然而,恶意应用可以绕过这种系统保护,通过一类新发现的漏洞直接调用易受攻击应用中的私有组件,这类漏洞被称为下一意图漏洞。在本文中,我们设计了一种意图流分析策略,能够准确地跟踪小代码中的意图,从而在大范围内高效地静态检测下一个意图漏洞。我们进一步提出了一种自动化的方法,通过生成利用应用程序来动态验证发现的漏洞。然后我们实现了一个名为NIVAnalyzer的工具,并在从Google Play下载的2万个应用程序中对其进行了评估。结果,我们成功确认了190个易受攻击的应用程序,其中一些甚至有数百万的下载量。我们还确认了一个开源项目和第三方SDK,它们仍然被其他应用程序使用,有下一个意图漏洞。
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