Summary Android is extensively used worldwide by mobile application developers. Android provides applications with a message passing system to communicate within and between them. Due to the risks associated with this system, it is vital to detect its unsafe operations and potential vulnerabilities. To achieve this goal, a new framework, called VAnDroid, based on Model Driven Reverse Engineering (MDRE), is presented that identifies security risks and vulnerabilities related to the Android application communication model. In the proposed framework, some security‐related information included in an Android app is automatically extracted and represented as a domain‐specific model. Then, it is used for analyzing security configurations and identifying vulnerabilities in the corresponding application. The proposed framework is implemented as an Eclipse‐based tool, which automatically identifies the Intent Spoofing and Unauthorized Intent Receipt as two attacks related to the Android application communication model. To evaluate the tool, it has been applied to several real‐world Android applications, including 20 apps from Google Play and 110 apps from the F‐Droid repository. VAnDroid is also compared with several existing analysis tools, and it is shown that it has a number of key advantages over those tools specifically regarding its high correctness, scalability, and usability in discovering vulnerabilities. The results well indicate the effectiveness and capacity of the VAnDroid as a promising approach in the field of Android security.

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Android users install various apps, such as banking apps, on their smart devices dealing with user-sensitive information. The Android framework, via Inter-Component Communication (ICC) mechanism, ensures that app components (inside the same app or on different apps) can communicate. The literature works have shown that this mechanism can cause security issues, such as app security policy violations, especially in the case of Inter-App Communication (IAC). Despite the plethora of research on detecting security issues in IAC, detection techniques face fundamental ICC challenges for improving the precision of static analysis. Challenges include providing comprehensive and scalable modeling of app specification, capturing all potential ICC paths, and enabling more effective IAC analysis. To overcome such challenges, in this paper, we propose a framework called VAnDroid2, as an extension of our previous work, to address the security issues in multiple components at both intra-and inter-app analysis levels. VAnDroid2, based on Model-Driven Reverse Engineering, has extended our previous work as per following: (1) providing a comprehensive Intermediate Representation (IR) of the app which supports extracting all the ICC information from the app, (2) extracting high-level representations of the apps and their interactions by omitting the details that are not relevant to inter-app security analysis, and (3) enabling more effective IAC security analysis. This framework is implemented as an Eclipse-based tool. The results of evaluating VAnDroid2 w.r.t. correctness, scalability, and run-time performance, and comparing with state-of-the-art analysis tools well indicate that VAnDroid2 is a promising framework in the field of Android inter-app security analysis.