Android’s flexible communication model allows interactions among third-party apps, but it also leads to inter-app security vulnerabilities. Specifically, malicious apps can eavesdrop on interactions between other apps or exploit the functionality of those apps, which can expose a user’s sensitive information to attackers. While the state-of-the-art tools have focused on detecting inter-app vulnerabilities in Android, they neither accurately analyze realistically large numbers of apps nor effectively deliver the identified issues to users. This paper presents SEALANT, a novel tool that combines static analysis and visualization techniques that, together, enable accurate identification of inter-app vulnerabilities as well as their systematic visualization. SEALANT statically analyzes architectural information
of a given set of apps, infers vulnerable communication channels where inter-app attacks can be launched, and visualizes the identified information in a compositional representation. SEALANT has been demonstrated to accurately identify inter-app
vulnerabilities from hundreds of real-world Android apps and to effectively deliver the identified information to users.
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Amandroid: A Precise and General Inter-component Data Flow Analysis Framework for Security Vetting of Android Apps
We present a new approach to static analysis for security vetting of Android apps and a general framework called Amandroid. Amandroid determines points-to information for all objects in an Android app component in a flow and context-sensitive (user-configurable) way and performs data flow and data dependence analysis for the component. Amandroid also tracks inter-component communication activities. It can stitch the component-level information into the app-level information to perform intra-app or inter-app analysis. In this article, (a) we show that the aforementioned type of comprehensive app analysis is completely feasible in terms of computing resources with modern hardware, (b) we demonstrate that one can easily leverage the results from this general analysis to build various types of specialized security analyses—in many cases the amount of additional coding needed is around 100 lines of code, and (c) the result of those specialized analyses leveraging Amandroid is at least on par and often exceeds prior works designed for the specific problems, which we demonstrate by comparing Amandroid’s results with those of prior works whenever we can obtain the executable of those tools. Since Amandroid’s analysis directly handles inter-component control and data flows, it can be used to address security problems that result from interactions among multiple components from either the same or different apps. Amandroid’s analysis is sound in that it can provide assurance of the absence of the specified security problems in an app with well-specified and reasonable assumptions on Android runtime system and its library.
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- Award ID(s):
- 1718214
- NSF-PAR ID:
- 10063123
- Date Published:
- Journal Name:
- ACM transactions on information and system security
- Volume:
- 21
- Issue:
- 3
- ISSN:
- 1094-9224
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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