Mascara: A Novel Attack Leveraging Android Virtualization
This addresses a security vulnerability in Android systems for users and developers, but it is incremental as it builds on known virtualization techniques.
The authors tackled the problem of Android virtualization being exploited for attacks by proposing Mascara, a novel attack that bypasses existing detection mechanisms, achieving full feasibility against any Android app and demonstrating effectiveness against popular apps like Telegram, Amazon Music, and Alamo with a compilation time of less than 10 seconds for generating 100 malicious add-ons.
Android virtualization enables an app to create a virtual environment, in which other apps can run. Originally designed to overcome the limitations of mobile apps dimensions, malicious developers soon started exploiting this technique to design novel attacks. As a consequence, researchers proposed new defence mechanisms that enable apps to detect whether they are running in a virtual environment. In this paper, we propose Mascara, the first attack that exploits the virtualization technique in a new way, achieving the full feasibility against any Android app and proving the ineffectiveness of existing countermeasures. Mascara is executed by a malicious app, that looks like the add-on of the victim app. As for any other add-on, our malicious one can be installed as a standard Android app, but, after the installation, it launches Mascara against the victim app. The malicious add-on is generated by Mascarer, the framework we designed and developed to automate the whole process. Concerning Mascara, we evaluated its effectiveness against three popular apps (i.e., Telegram, Amazon Music and Alamo) and its capability to bypass existing mechanisms for virtual environments detection. We analyzed the efficiency of our attack by measuring the overhead introduced at runtime by the virtualization technique and the compilation time required by Mascarer to generate 100 malicious add-ons (i.e., less than 10 sec). Finally, we designed a robust approach that detects virtual environments by inspecting the fields values of ArtMethod data structures in the Android Runtime (ART) environment.