Martin Unterguggenberger (Graz University of Technology), Lukas Lamster (Graz University of Technology), David Schrammel (Graz University of Technology), Martin Schwarzl (Cloudflare, Inc.), Stefan Mangard (Graz University of Technology)

Efficient cloud computing relies on in-process isolation to optimize performance by running workloads within a single process. Without heavy-weight process isolation, memory safety errors pose a significant security threat by allowing an adversary to extract or corrupt the private data of other co-located tenants. Existing in-process isolation mechanisms are not suitable for modern cloud requirements, e.g., MPK’s 16 protection domains are insufficient to isolate thousands of cloud workers per process. Consequently, cloud service providers have a strong need for lightweight in-process isolation on commodity x86 machines.

This paper presents TME-Box, a novel isolation technique that enables fine-grained and scalable sandboxing on commodity x86 CPUs. By repurposing Intel TME-MK, which is intended for the encryption of virtual machines, TME-Box offers lightweight and efficient in-process isolation. TME-Box enforces that sandboxes use their designated encryption keys for memory interactions through compiler instrumentation. This cryptographic isolation enables fine-grained access control, from single cache lines to full pages, and supports flexible data relocation. In addition, the design of TME-Box allows the efficient isolation of up to 32K concurrent sandboxes. We present a performance-optimized TME-Box prototype, utilizing x86 segment-based addressing, that showcases geomean performance overheads of 5.2 % for data isolation and 9.7 % for code and data isolation, evaluated with the SPEC CPU2017 benchmark suite.

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Runze Zhang (Georgia Institute of Technology), Mingxuan Yao (Georgia Institute of Technology), Haichuan Xu (Georgia Institute of Technology), Omar Alrawi (Georgia Institute of Technology), Jeman Park (Kyung Hee University), Brendan Saltaformaggio (Georgia Institute of Technology)

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Duanyi Yao (Hong Kong University of Science and Technology), Songze Li (Southeast University), Xueluan Gong (Wuhan University), Sizai Hou (Hong Kong University of Science and Technology), Gaoning Pan (Hangzhou Dianzi University)

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