DSCRETE: Automatic Rendering of Forensic Information from Memory Images via Application Logic Reuse

Sep 03, 2014

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Abstract

State-of-the-art memory forensics involves signature-based scanning of memory images to uncover data structure instances of interest to investigators. A largely unaddressed challenge is that investigators may not be able to interpret the content of data structure fields, even with a deep understanding of the data structure's syntax and semantics. For example, an investigator may know that a buffer field is holding a photo image, but still cannot display (and hence understand) the image. We call this the data structure content reverse engineering challenge. In this talk, we present DSCRETE, a system that enables automatic interpretation and rendering of in-memory data structure contents. DSCRETE is based on the observation that the application in which a data structure is defined usually contains interpretation and rendering logic to generate human-understandable output for that data structure. Hence DSCRETE aims to identify and reuse such logic in the program's binary and create a "scanner+renderer" tool for scanning and rendering instances of the data structure in a memory image. We will show that DSCRETE is able to recover a variety of application data — e.g., images, figures, screenshots, user accounts, and formatted files and messages — with high accuracy. The raw contents of such data would otherwise be unfathomable to human investigators.