论文标题
SOK:如何不构建下一代T恤恶意软件?
SoK: How Not to Architect Your Next-Generation TEE Malware?
论文作者
论文摘要
除了英特尔的SGX技术外,还讨论了如何使用信任的计算技术来掩盖恶意软件。过去的研究展示了利用闪烁,值得信赖的平台模块以及最近与飞地集成的恶意活动的示例方法。我们观察到两种与SGX相关的恶意软件开发方法的模棱两可方法,这对于系统化其细节至关重要。一种方法是将核心SGX生态系统用于掩护恶意软件。可能影响大量系统。第二种方法是创建一个自定义的飞地,而不是遵守SGX的基本假设,以这些错误的假设创建了恶意软件行为的演示代码;保持本地,没有任何影响。我们检查了恶意软件在现实情况下的目标和恶意软件逃避技术的最新技术。我们提出了维护SGX辅助恶意软件并从反恶意软件机制中逃避的多个局限性。这些限制使SGX飞地成为实现成功的恶意软件活动的糟糕选择。我们将十二个误解(神话)系统化,概述了使用SGX过度拟合损失的效果如何削弱恶意软件的现有能力。我们通过将恶意软件的SGX援助与非SGX恶意软件进行比较(即,我们的论文中的恶意软件)发现了差异。我们得出的结论是,硬件飞地的使用不会增加先前存在的攻击表面,没有新的感染向量,也不会为恶意软件的隐身性贡献任何新方法。
Besides Intel's SGX technology, there are long-running discussions on how trusted computing technologies can be used to cloak malware. Past research showed example methods of malicious activities utilising Flicker, Trusted Platform Module, and recently integrating with enclaves. We observe two ambiguous methodologies of malware development being associated with SGX, and it is crucial to systematise their details. One methodology is to use the core SGX ecosystem to cloak malware; potentially affecting a large number of systems. The second methodology is to create a custom enclave not adhering to base assumptions of SGX, creating a demonstration code of malware behaviour with these incorrect assumptions; remaining local without any impact. We examine what malware aims to do in real-world scenarios and state-of-art techniques in malware evasion. We present multiple limitations of maintaining the SGX-assisted malware and evading it from anti-malware mechanisms. The limitations make SGX enclaves a poor choice for achieving a successful malware campaign. We systematise twelve misconceptions (myths) outlining how an overfit-malware using SGX weakens malware's existing abilities. We find the differences by comparing SGX assistance for malware with non-SGX malware (i.e., malware in the wild in our paper). We conclude that the use of hardware enclaves does not increase the preexisting attack surface, enables no new infection vector, and does not contribute any new methods to the stealthiness of malware.