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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NDSS Symposium 2025 Welcome and Opening Remarks

General Chairs: David Balenson, USC Information Sciences Institute and Heng Yin, University of California, Riverside Program Chairs: Christina Pöpper, New York University Abu Dhabi and Hamed Okhravi, MIT Lincoln Laboratory Artifact Evaluation Chairs: Daniele Cono D’Elia, Sapienza University and Mathy Vanhoef, KU Leuven

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SNITCH: Leveraging IP Geolocation for Active VPN Detection

Tomer Schwartz (Data and Security Laboratory Fujitsu Research of Europe Ltd), Ofir Manor (Data and Security Laboratory Fujitsu Research of Europe Ltd), Andikan Otung (Data and Security Laboratory Fujitsu Research of Europe Ltd)

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LAMP: Lightweight Approaches for Latency Minimization in Mixnets with...

Mahdi Rahimi (KU Leuven), Piyush Kumar Sharma (University of Michigan), Claudia Diaz (KU Leuven)

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ReDAN: An Empirical Study on Remote DoS Attacks against...

Xuewei Feng (Tsinghua University), Yuxiang Yang (Tsinghua University), Qi Li (Tsinghua University), Xingxiang Zhan (Zhongguancun Lab), Kun Sun (George Mason University), Ziqiang Wang (Southeast University), Ao Wang (Southeast University), Ganqiu Du (China Software Testing Center), Ke Xu (Tsinghua University)

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