一种新的跨用户内核空间检测不可信执行流的动态分析基础结构

J. Hong, Xuhua Ding
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引用次数: 7

摘要

代码插装和基于硬件的事件捕获是动态恶意软件分析系统中使用的两种主要方法。在本文中,我们提出了一种新的方法,称为执行流仪表(EFI),其中分析器的执行流在用户模式和内核模式下与目标流交错,在运行时分析器灵活选择的节点上。我们还提出OASIS作为系统基础设施来实现EFI,它具有当前两种方法的优点,但没有它们的缺点。尽管安全且透明地与目标隔离,分析器还是以与检测代码相同的本机方式对其进行自省和控制。我们已经实现了OASIS的原型,并通过包括性能和反分析基准测试在内的各种实验对其进行了严格的评估。我们还进行了两个EFI案例研究。第一个是跨空间控制流跟踪器,第二个包括两个EFI工具与Google Syzkaller协同工作。一个工具根据内核崩溃报告进行动态事后分析;另一个则探讨了恶意内核空间设备驱动程序的行为,该驱动程序可以逃避Syzkaller日志记录。研究表明,EFI分析器非常适合在用户模式或内核模式下对恶意线程进行细粒度的按需动态分析。开发敏捷EFI工具很容易,因为它们是用户空间程序。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Novel Dynamic Analysis Infrastructure to Instrument Untrusted Execution Flow Across User-Kernel Spaces
Code instrumentation and hardware based event trapping are two primary approaches used in dynamic malware analysis systems. In this paper, we propose a new approach called Execution Flow Instrumentation (EFI) where the analyzer execution flow is interleaved with the target flow in user- and kernel-mode, at junctures flexibly chosen by the analyzer at runtime. We also propose OASIS as the system infrastructure to realize EFI with virtues of the current two approaches, however without their drawbacks. Despite being securely and transparently isolated from the target, the analyzer introspects and controls it in the same native way as instrumentation code. We have implemented a prototype of OASIS and rigorously evaluated it with various experiments including performance and anti-analysis benchmark tests. We have also conducted two EFI case studies. The first is a cross-space control flow tracer and the second includes two EFI tools working in tandem with Google Syzkaller. One tool makes a dynamic postmortem analysis according to a kernel crash report; and the other explores the behavior of a malicious kernel space device driver which evades Syzkaller logging. The studies show that EFI analyzers are well-suited for fine-grained on-demand dynamic analysis upon a malicious thread in user or kernel mode. It is easy to develop agile EFI tools as they are user-space programs.
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