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

• Published in: 2017 IEEE International Conference on Software Testing, Verification and Validation (ICST) pp. 492 - 499
• Main Authors: Junjie Tang, Xingmin Cui, Ziming Zhao, Shanqing Guo, Xinshun Xu, Chengyu Hu, Tao Ban, Bing Mao
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.03.2017
• Subjects: Android; Androids; Electronic mail; Facebook; Humanoid robots; Intent; Registers; static and dynamic analysis; Target tracking; vulnerability
• DOI: 10.1109/ICST.2017.56

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.