Poster: Evaluating Analysis Tools for Android Apps: Status Quo and Robustness Against Obfuscation

Johannes Hoffmann, Teemu Rytilahti, Marcel Winandy, Giorgio Giacinto, Thorsten Holz

Pro­cee­dings of the ACM Con­fe­rence on Data and Ap­p­li­ca­ti­on Se­cu­ri­ty and Pri­va­cy (ACM CO­DAS­PY) 2016


The recent past has shown that Android smartphones became the most popular target for malware authors. Malware families offer a variety of features that allow, among the others, to steal arbitrary data and to cause significant monetary losses. This circumstances led to the development of many different analysis methods that are aimed to assess the absence of potential harm or malicious behavior in mobile apps. In return, malware authors devised more sophisticated methods to write mobile malware that attempt to thwart such analyses. In this work, we briefly describe assumptions analysis tools rely on to detect malicious content and behavior. We then present results of a new obfuscation framework that aims to break such assumptions, thus modifying Android apps to avoid them being analyzed by the targeted systems. We use our framework to evaluate the robustness of static and dynamic analysis systems for Android apps against such transformations.