GOLDENEYE: Efficiently and Effectively Unveiling Malware’s Targeted Environment Zhaoyan Xu1, Jialong Zhang1, Guofei Gu1, and Zhiqiang Lin2 1Texas A&M University, College Station, TX fz0x0427, jialong,
[email protected] 2The University of Texas at Dallas, Richardson, TX
[email protected] Abstract. A critical challenge when combating malware threat is how to effi- ciently and effectively identify the targeted victim’s environment, given an un- known malware sample. Unfortunately, existing malware analysis techniques ei- ther use a limited, fixed set of analysis environments (not effective) or employ ex- pensive, time-consuming multi-path exploration (not efficient), making them not well-suited to solve this challenge. As such, this paper proposes a new dynamic analysis scheme to deal with this problem by applying the concept of speculative execution in this new context. Specifically, by providing multiple dynamically created, parallel, and virtual environment spaces, we speculatively execute a mal- ware sample and adaptively switch to the right environment during the analysis. Interestingly, while our approach appears to trade space for speed, we show that it can actually use less memory space and achieve much higher speed than existing schemes. We have implemented a prototype system, GOLDENEYE, and evalu- ated it with a large real-world malware dataset. The experimental results show that GOLDENEYE outperforms existing solutions and can effectively and effi- ciently expose malware’s targeted environment, thereby speeding up the analysis in the critical battle against the emerging targeted malware threat. Keywords: Dynamic Malware Analysis, Speculative Execution 1 Introduction In the past few years, we have witnessed a new evolution of malware attacks from blindly or randomly attacking all of the Internet machines to targeting only specific systems, with a great deal of diversity among the victims, including government, mil- itary, business, education, and civil society networks [17,24].