A Security Analysis of Labeling-Based Control-Flow Integrity Schemes

A Security Analysis of Labeling-Based Control-Flow Integrity Schemes
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DOI:
10.1109/hipcw57629.2022.00011
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发表时间:
2022-12
期刊:
2022 IEEE 29th International Conference on High Performance Computing, Data and Analytics Workshop (HiPCW)
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通讯作者:
David Demicco;Matthew Cole;Shengdun Wang;Aravind Prakash
David Demicco;Matthew Cole;Shengdun Wang;Aravind Prakash
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其他
文献类型:
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作者:
David Demicco;Matthew Cole;Shengdun Wang;Aravind Prakash

文献摘要

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云提供商安全透明的策略执行在云基础设施中至关重要。特别是,控制流完整性(CFI)策略的实施已被广泛接受,以阻止软件引起的攻击。使用低级硬件元数据对CFI策略进行编码是最近的发展。除了将执行从软件转移到硬件以提高性能之外,标记元数据还在防御精度方面提供了其他好处。我们评估了用于CFI策略实施的几种不同的元数据布局,并检查了布局对策略实施后RISC-V二进制中剩余的有效前向边缘数量的影响。此外,我们还将研究基于标记的工具中的相关工作,这些工具提供CFI策略执行,以便了解它们的性能和它们所做的设计权衡。我们评估我们的政策和相关的工作,在空间和精度的权衡前向和后向边缘CFI,发现一些权衡有更高的影响,剩余的前向边缘的数量,特别是返回地址保护。此外,我们报告说,现有的后向边缘保护非常有效,与等效的粗粒度CFI相比,将受保护二进制文件中剩余的后向边缘数量平均减少到0.034%。
Secure and transparent policy enforcement by a cloud provider is crucial in cloud infrastructures. Particularly, enforcement of control-flow integrity (CFI) policy has been widely accepted for stopping software-induced attacks. Using low-level hardware metadata to encode CFI policy is a fairly recent development. Besides moving enforcement out of the software and into the hardware for performance benefit, tagging metadata also offers other benefits in the precision of defenses. We evaluate several different metadata layouts for CFI policy enforcement, and examine the layouts' effects on the number of valid forward edges remaining in a RISC-V binary after policy enforcement. Additionally we look at related work in tag-based tools that provide CFI policy enforcement in order to get a sense of their performance and the design trade-offs they make. We evaluate our policy and the related works in terms of space and precision trade-offs for forward- and backward-edge CFI, finding that some trade-offs have a higher impact on the number of remaining forward edges, notably return address protection. Additionally, we report that existing backward edge protections can be highly effective, reducing the number of remaining backward edges in a protected binary to an average of 0.034% over an equivalent coarse-grained CFI.