Eventpad: Rapid Malware Analysis and Reverse Engineering using Visual Analytics

Abstract

Forensic analysis of malware activity in network environments is a necessary yet very costly and time consuming part of incident response. Vast amounts of data need to be screened, in a very labor-intensive process, looking for signs indicating how the malware at hand behaves inside e.g., a corporate network. We believe that data reduction and visualization techniques can assist security analysts in studying behavioral patterns in network traffic samples (e.g., PCAP). We argue that the discovery of patterns in this traffic can help us to quickly understand how intrusive behavior such as malware activity unfolds and distinguishes itself from the rest of the traffic.In this paper we present a case study of the visual analytics tool EventPad and illustrate how it is used to gain quick insights in the analysis of PCAP traffic using rules, aggregations, and selections. We show the effectiveness of the tool on real-world data sets involving office traffic and ransomware activity.