AppTrace: Dynamic trace on Android devices
Lingzhi Qiu, Zixiong Zhang, Ziyi Shen, Guozi Sun · 2015
Mass vulnerabilities involved in the Android alternative applications could threaten the security of the launched device or users data. To analyze the alternative applications, generally, researchers would like to observe applications' runtime features first. Then they need to decompile the target application and read the complicated code to figure out what the application really does. Traditional dynamic analysis methodology, for instance, the TaintDroid, uses dynamic taint tracking technique to mark information at source APIs. However, TaintDroid is limited to constraint on requiring target application to run in custom sandbox that might be not compatible with all the Android versions. For solving this problem and helping analysts to have insight into the runtime behavior, this paper presents AppTrace, a novel dynamic analysis system that uses dynamic instrumentation technique to trace member methods of target application that could be deployed in any version above Android 4.0. The paper presents an evaluation of AppTrace with 8 apps from Google Play as well as 50 open source apps from F-Droid. The results show that AppTrace could trace methods of target applications successfully and notify users effectively when some sensitive APIs are invoked.