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The popularity of mobile devices like smartphones and tablets has increased significantly in the last few years with many millions of sold devices. This growth also has its drawbacks: attackers have realized that smartphones are an attractive target and in the last months many different kinds of malicious software (short: malware) for such devices have emerged. This worrisome development has the potential to hamper the prospering ecosystem of mobile devices and the potential for damage is huge.Considering these aspects, it is evident that malicious apps need to be detected early on in order to prevent further distribution and infections. This implies that it is necessary to develop techniques capable of detecting malicious apps in an automated way. In this paper, we present SAAF, a Static Android Analysis Framework for Android apps. SAAF analyzes smali code, a disassembled version of the DEX format used by Android's Java VM implementation. Our goal is to create program slices in order to perform data-flow analyses to backtrack parameters used by a given method. This helps us to identify suspicious code regions in an automated way. Several other analysis techniques such as visualization of control flow graphs or identification of ad-related code are also implemented in SAAF. In this paper, we report on program slicing for Android and present results obtained by using this technique to analyze more than 136,000 benign and about 6,100 malicious apps. |
