Context-aware security testing of Android applications : Detecting exploitable vulnerabilities through Android model-based security testing

Sammanfattning: This master’s thesis explores ways to uncover and exploit vulnerabilities in Android applications by introducing a novel approach to security testing. The research question focuses on discovering an effective method for detecting vulnerabilities related to the context of an application. The study begins by reviewing recent papers on Android security flaws affecting application in order to guide our tool creation. Thus, we are able to introduce three Domain Specific Languages (DSLs) for Model-Based Security Testing (MBST): Context Definition Language (CDL), Context-Driven Modelling Language (CDML), and Vulnerability Pattern (VPat). These languages provide a fresh perspective on evaluating the security of Android apps by accounting for the dynamic context that is present on smartphones and can greatly impact user security. The result of this work is the development of VPatChecker[1], a tool that detects vulnerabilities and creates abstract exploits by integrating an application model, a context model, and a set of vulnerability patterns. This set of vulnerability patterns can be defined to represent a wide array of vulnerabilities, allowing the tool to be indefinitely updated with each new CVE. The tool was evaluated on the GHERA benchmark, showing that at least 38% (out of a total of 60) of the vulnerabilities in the benchmark can be modelled and detected. The research underscores the importance of considering context in Android security testing and presents a viable and extendable solution for identifying vulnerabilities through MBST and DSLs.