Automated Deobfuscation of Android Native Binary Code

Kan Zeliang,Wang Haoyu,Wu Lei,Guo Yao, Luo Daniel Xiapu

arxiv(2019)

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摘要
With the popularity of Android apps, different techniques have been proposed to enhance app protection. As an effective approach to prevent reverse engineering, obfuscation can be used to serve both benign and malicious purposes. In recent years, more and more sensitive logic or data have been implemented as obfuscated native code because of the limitations of Java bytecode. As a result, native code obfuscation becomes a great obstacle for security analysis to understand the complicated logic. In this paper, we propose DiANa, an automated system to facilitate the deobfuscation of native binary code in Android apps. Specifically, given a binary obfuscated by Obfuscator-LLVM (the most popular native code obfuscator), DiANa is capable of recovering the original Control Flow Graph. To the best of our knowledge, DiANa is the first system that aims to tackle the problem of Android native binary deobfuscation. We have applied DiANa in different scenarios, and the experimental results demonstrate the effectiveness of DiANa based on generic similarity comparison metrics.
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