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Happer: Unpacking Android Apps via a Hardware-Assisted Approach

机译:Happer:通过硬件辅助方法打开Android应用程序

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Malware authors are abusing packers (or runtime-based obfuscators) to protect malicious apps from being analyzed. Although many unpacking tools have been proposed, they can be easily impeded by the anti-analysis methods adopted by the packers, and they fail to effectively collect the hidden Dex data due to the evolving protection strategies of packers. Consequently, many packing behaviors are unknown to analysts and packed malware can circumvent the inspection. To fill the gap, in this paper, we propose a novel hardware-assisted approach that first monitors the packing behaviors and then selects the proper approach to unpack the packed apps. Moreover, we develop a prototype named Happerwith a domain-specific language named behavior description language (BDL) for the ease of extending Happerafter tackling several technical challenges. We conduct extensive experiments with 12 commercial Android packers and more than 24k Android apps to evaluate Happer. The results show that Happerobserved 27 packing behaviors, 17 of which have not been elaborated by previous studies. Based on the observed packing behaviors, Happeradopted proper approaches to collect all the hidden Dex data and assembled them to valid Dex files.
机译:恶意软件作者正在滥用包装器(或基于运行时的obfuscators)来保护恶意应用程序正在分析。虽然已经提出了许多拆包工具,但是封装器采用的反分析方法可以容易地阻碍,并且由于包装机的不断变化的保护策略,它们未能有效地收集隐藏的DEX数据。因此,许多包装行为对分析师未知,并且包装恶意软件可以绕过检查。为了填补差距,在本文中,我们提出了一种新颖的硬件辅助方法,首先监视包装行为,然后选择要解压缩的应用程序的正确方法。此外,我们开发一个名为Happerwith的原型名为Happerwith命名的行为描述语言(BDL),便于扩展Happerofter解决多项技术挑战。我们通过12个商用Android封装机和超过24K个Android应用程序进行广泛的实验来评估哈普佩。结果表明,先前研究尚未详细阐述27个包装行为,其中17个包装行为尚未阐述。基于观察到的包装行为,HAPPERADOPTED正确的方法来收集所有隐藏的DEX数据并将它们组装到有效的DEX文件。

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