When Program Analysis Meets Bytecode Search: Targeted and Efficient Inter-procedural Analysis of Modern Android Apps in BackDroid Daoyuan Wu1, Debin Gao2, Robert H. Deng2, and Rocky K. C. Chang3 1The Chinese University of Hong Kong 2Singapore Management University 3The Hong Kong Polytechnic University Contact:
[email protected] Abstract—Widely-used Android static program analysis tools, be successfully analyzed by its underlying FlowDroid tool. e.g., Amandroid and FlowDroid, perform the whole-app inter- Although HSOMiner [53] increased the size of the analyzed procedural analysis that is comprehensive but fundamentally apps, the average app size is still only 8.4MB. Even for difficult to handle modern (large) apps. The average app size has these small apps, AppContext timed out for 16.1% of the increased three to four times over five years. In this paper, we 1,002 apps tested and HSOMiner similarly failed in 8.4% explore a new paradigm of targeted inter-procedural analysis that can skip irrelevant code and focus only on the flows of security- of 3,000 apps, causing a relatively high failure rate. Hence, sensitive sink APIs. To this end, we propose a technique called this is not only a performance issue, but also the detection on-the-fly bytecode search, which searches the disassembled app burden. Additionally, third-party libraries were often ignored. bytecode text just in time when a caller needs to be located. In this For example, Amandroid by default skipped the analysis of way, it guides targeted (and backward) inter-procedural analysis 139 popular libraries, such as AdMob, Flurry, and Facebook.