PyTrigger: A System to Trigger & Extract User-Activated Malware Behavior

Abstract

We introduce PyTrigger, a dynamic malware analysis system that automatically exercises a malware binary extracting its behavioral profile even when specific user activity or input is required. To accomplish this, we developed a novel user activity record and playback framework and a new behavior extraction approach. Unlike existing research, the activity recording and playback includes the context of every object in addition to traditional keyboard and mouse actions. The addition of the context makes the playback more accurate and avoids dependencies and pitfalls that come with pure mouse and keyboard replay. Moreover, playback can become more efficient by condensing common activities into a single action. After playback, PyTrigger analyzes the system trace using a combination of multiple states and behavior differencing to accurately extract the malware behavior and user triggered behavior from the complete system trace log. We present the algorithms, architecture and evaluate the PyTrigger prototype using 3994 real malware samples. Results and analysis are presented showing PyTrigger extracts additional behavior in 21% of the samples.