使用虚拟机自省进行恶意软件分析的内存取证

Chin-Wei Tien, Jian-Wei Liao, Shun-Chieh Chang, S. Kuo
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引用次数: 20

摘要

安全沙箱是一种通常用于检测高级恶意软件的技术。然而,当前的沙箱高度依赖于VM管理程序类型和版本。因此,在本文中,我们引入了一种新的沙盒设计,使用内存取证技术来提供独立于VM管理程序的无代理沙盒解决方案。特别是,我们利用VM自省方法来监视恶意软件在VM之外运行内存数据,并分析其系统行为,如进程、文件、注册表和网络活动。我们使用20个高级和8个基于脚本的恶意软件样本来评估该方法的可行性。我们进一步演示了如何从内存中分析恶意软件行为,并使用三种不同的沙盒类型验证结果。结果表明,我们可以分析可疑的恶意软件活动,这也有助于网络安全防御。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Memory forensics using virtual machine introspection for Malware analysis
A security sandbox is a technology that is often used to detect advanced malware. However, current sandboxes are highly dependent on VM hypervisor types and versions. Thus, in this paper, we introduce a new sandbox design, using memory forensics techniques, to provide an agentless sandbox solution that is independent of the VM hypervisor. In particular, we leverage the VM introspection method to monitor malware running memory data outside the VM and analyze its system behaviors, such as process, file, registry, and network activities. We evaluate the feasibility of this method using 20 advanced and 8 script-based malware samples. We furthermore demonstrate how to analyze malware behavior from memory and verify the results with three different sandbox types. The results show that we can analyze suspicious malware activities, which is also helpful for cyber security defense.
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