Morpheus: automatically generating heuristics to detect Android emulators

Yiming Jing, Ziming Zhao, Gail-Joon Ahn, Hongxin Hu
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引用次数: 95

Abstract

Emulator-based dynamic analysis has been widely deployed in Android application stores. While it has been proven effective in vetting applications on a large scale, it can be detected and evaded by recent Android malware strains that carry detection heuristics. Using such heuristics, an application can check the presence or contents of certain artifacts and infer the presence of emulators. However, there exists little work that systematically discovers those heuristics that would be eventually helpful to prevent malicious applications from bypassing emulator-based analysis. To cope with this challenge, we propose a framework called Morpheus that automatically generates such heuristics. Morpheus leverages our insight that an effective detection heuristic must exploit discrepancies observable by an application. To this end, Morpheus analyzes the application sandbox and retrieves observable artifacts from both Android emulators and real devices. Afterwards, Morpheus further analyzes the retrieved artifacts to extract and rank detection heuristics. The evaluation of our proof-of-concept implementation of Morpheus reveals more than 10,000 novel detection heuristics that can be utilized to detect existing emulator-based malware analysis tools. We also discuss the discrepancies in Android emulators and potential countermeasures.
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Morpheus:自动生成启发式检测Android模拟器
基于仿真器的动态分析在Android应用商店中得到了广泛的应用。虽然它已被证明在大规模审查应用程序方面是有效的,但它可以被最近携带检测启发式的Android恶意软件菌株检测和规避。使用这种启发式方法,应用程序可以检查某些工件的存在或内容,并推断模拟器的存在。然而,很少有工作系统地发现这些启发式,这些启发式最终将有助于防止恶意应用程序绕过基于模拟器的分析。为了应对这一挑战,我们提出了一个名为Morpheus的框架,它可以自动生成这种启发式。Morpheus利用了我们的洞察力,即有效的检测启发式必须利用应用程序可观察到的差异。为此,Morpheus分析了应用程序沙箱,并从Android模拟器和真实设备中检索了可观察的工件。然后,Morpheus进一步分析检索到的工件,提取检测启发式并对其进行排序。我们对Morpheus的概念验证实现的评估揭示了超过10,000种新的检测启发式方法,可用于检测现有的基于模拟器的恶意软件分析工具。我们还讨论了Android模拟器的差异和潜在的对策。
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