SoK: SGX.Fail: How Stuff Gets eXposed
Stephan van Schaik, Alexander Seto, Thomas Yurek, Adam Batori, Bader AlBassam, Daniel Genkin, Andrew Miller, Eyal Ronen, Yuval Yarom, Christina Garman
摘要
Intel’s Software Guard Extensions (SGX) promises an isolated execution environment, protected from all software running on the machine. As such, numerous works have sought to leverage SGX to provide confidentiality and integrity guarantees for code running in adversarial environments. In the past few years however, SGX has come under heavy fire, threatened by numerous hardware attacks. With Intel repeatedly patching SGX to regain security while consistently launching new (micro)architectures, it is increasingly difficult to track the applicability of various attack techniques across the SGX design landscape.Thus, in this paper we set out to survey and categorize various SGX attacks, their applicability to different SGX architectures, as well as the information leaked by them. We then set out to explore the effectiveness of SGX’s update mechanisms in preventing attacks on real-world deployments. Here, we study two commercial SGX applications. First, we investigate the SECRET network, an SGX-backed blockchain aiming to provide privacy-preserving smart contracts. Next, we also consider PowerDVD, a UHD Blu-Ray Digital Rights Management (DRM) software licensed to play discs on PCs. We show that in both cases vendors are unable to meet security goals originally envisioned for their products, presumably due to SGX’s long update timelines and the complexities of a manual update process. This in turn forces vendors to make difficult security/usability trade offs, resulting in security compromises.
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引用它的顶会 Paper10
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- IOValve: Leakage-Free I/O Sandbox for Large-Scale Untrusted Data ProcessingSangho Lee, Jules Drean, Yue Tan, Marcus PeinadoCCS 2025 · 被引用 1 次
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- GlitchFHE: Attacking Fully Homomorphic Encryption Using Fault InjectionLakshmi Likhitha Mankali, Mohammed Nabeel, Faiq Raees, Michail Maniatakos 等USENIX Security 2025
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- Meltdown: Reading Kernel Memory from User SpaceMoritz Lipp, Michael Schwarz, Daniel Gruss, Thomas Prescher 等USENIX Security 2018 · 被引用 1,456 次
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- Oblivious Multi-Party Machine Learning on Trusted ProcessorsOlga Ohrimenko, Felix Schuster, Cédric Fournet, Aastha Mehta 等USENIX Security 2016 · 被引用 594 次
- Inferring Fine-grained Control Flow Inside SGX Enclaves with Branch ShadowingSangho Lee, Ming-Wei Shih, Prasun Gera, Taesoo Kim 等USENIX Security 2017 · 被引用 536 次
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