RATScope: Recording and Reconstructing Missing RAT Semantic Behaviors for Forensic Analysis on Windows
Runqing Yang, Xutong Chen, Haitao Xu, Yueqiang Cheng, Chunlin Xiong, Linqi Ruan, Mohammad Kavousi, Zhenyuan Li, Liheng Xu, Yan Chen
Abstract
Remote Access Trojan (RAT) attacks have become an extensively prevailing and serious threat to enterprise security. A forensic system targeting RAT attacks is needed to record and reconstruct fine-grained semantic behaviors of RATs. However, existing forensic systems suffer from various issues such as intrusive instrumentation, nontrivial recording overhead, and RAT behavior blindness. In this article, we first conduct a large-scale study of a representative set of real-world RAT families active from 1999 to 2016. This is the first study to understand the landscape of RATs in the literature. Based on the study, we then propose <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RATScope</small> , an instrumentation-free RAT forensic system targeting Windows platform. Specifically, <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RATScope</small> offers an audit logging module to efficiently record system logs by leveraging Event Tracing for Windows (ETW), and provides a novel program behavior modeling technique to reconstruct semantic behaviors of RATs accurately. We implement a prototype of <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RATScope</small> and evaluate the recording overhead and the behavior identification accuracy. The results show that the audit logging module only incurs 3.7 percent runtime overhead on average. Our system can achieve around 90 percent true positive rate in the cross-family experiment, around 80 percent true positive rate in the two-year spanning temporal experiment, and near <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">zero</i> false positive rate.