A step in a new direction: NVIDIA GPU kernel driver memory forensics

IF 2 4区 医学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS
Christopher J. Bowen , Andrew Case , Ibrahim Baggili , Golden G. Richard III
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Abstract

In the ever-expanding landscape of computation, graphics processing units have become one of the most essential types of devices for personal and commercial needs. Nearly all modern computers have one or more dedicated GPUs due to advancements in artificial intelligence, high-performance computing, 3D graphics rendering, and the growing demand for enhanced gaming experiences. As the GPU industry continues to grow, forensic investigations will need to incorporate these devices, given that they have large amounts of VRAM, computing power, and are used to process highly sensitive data. Past research has also shown that malware can hide its payloads within these devices and out of the view of traditional memory forensics. While memory forensics research aims to address the critical threat of memory-only malware, no current work focuses on video memory malware and the malicious use of the GPU. Our work investigates the largest GPU manufacturer, NVIDIA, by examining the newly released open-source GPU kernel modules for the development of forensic tool creation. We extend our impact by creating symbol mappings between open and closed-source NVIDIA software that enables researchers to develop tools for both “flavors” of software. We specifically focus our research on artifacts found in RAM, providing the foundational methods to detect and map NVIDIA Object Compiler Structures for forensic investigations. As a part of our analysis and evaluation, we examined the similarities between open-and-closed kernel modules by collecting structure sizes and class IDs to understand the similarities and differences. A standalone tool, NVSYMMAP, and Volatility plugins were created with this foundation to automate this process and provide forensic investigators with knowledge involving processes that utilized the GPU.

向新方向迈进:英伟达™(NVIDIA®)GPU 内核驱动程序内存取证
在不断扩大的计算领域,图形处理器已成为满足个人和商业需求的最基本设备之一。由于人工智能、高性能计算、3D 图形渲染的进步,以及对增强游戏体验日益增长的需求,几乎所有现代计算机都配备了一个或多个专用 GPU。随着 GPU 行业的不断发展,鉴于这些设备拥有大量的 VRAM 和计算能力,并用于处理高度敏感的数据,因此取证调查将需要结合这些设备。过去的研究还表明,恶意软件可以将其有效载荷隐藏在这些设备中,而不在传统内存取证的视野之内。虽然内存取证研究旨在解决纯内存恶意软件的严重威胁,但目前还没有任何研究关注视频内存恶意软件和对 GPU 的恶意使用。我们的工作通过研究新发布的开源 GPU 内核模块,调查了最大的 GPU 制造商英伟达公司,以开发取证工具的创建。我们在开放源代码和封闭源代码的英伟达软件之间创建了符号映射,使研究人员能够为这两种 "口味 "的软件开发工具,从而扩大了我们的影响。我们将研究重点特别放在 RAM 中发现的人工制品上,为取证调查提供了检测和映射英伟达对象编译器结构的基础方法。作为分析和评估的一部分,我们通过收集结构大小和类 ID 来了解开放式和封闭式内核模块之间的异同。在此基础上,我们创建了独立工具 NVSYMMAP 和 Volatility 插件,以自动执行该流程,并为法证调查人员提供涉及使用 GPU 的进程的知识。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
5.90
自引率
15.00%
发文量
87
审稿时长
76 days
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