CacheZoom: How SGX Amplifies The Power of Cache Attacks
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Abstract (arXiv)
In modern computing environments, hardware resources are commonly shared, and parallel computation is widely used. Parallel tasks can cause privacy and security problems if proper isolation is not enforced. Intel proposed SGX to create a trusted execution environment within the processor. SGX relies on the hardware, and claims runtime protection even if the OS and other software components are malicious. However, SGX disregards side-channel attacks. We introduce a powerful cache side-channel attack that provides system adversaries a high resolution channel. Our attack tool named CacheZoom is able to virtually track all memory accesses of SGX enclaves with high spatial and temporal precision. As proof of concept, we demonstrate AES key recovery attacks on commonly used implementations including those that were believed to be resistant in previous scenarios. Our results show that SGX cannot protect critical data sensitive computations, and efficient AES key recovery is possible in a practical environment. In contrast to previous works which require hundreds of measurements, this is the first cache side-channel attack on a real system that can recover AES keys with a minimal number of measurements. We can successfully recover AES keys from T-Table based implementations with as few as ten measurements.
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). First posted on arXiv 20 Mar 2017.
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Citing papers per year: 2021: 2; 2022: 1; 2023: 0; 2024: 2; 2025: 0; 2026: 2.
7 papers.
- 2021Confidential Machine Learning Computation in Untrusted Environments: A Systems Security Perspectivecited by 4
- 2022Edge Security: Challenges and Issuescited by 3
- 2021Automated Side Channel Analysis of Media Software with Manifold Learningcited by 1
- 2024Dynamic Frequency-Based Fingerprinting Attacks against Modern Sandbox Environmentscited by 1
- 2024SoK: Towards Security and Safety of Edge AIcited by 1
- 2026Opal: Private Memory for Personal AIcited by 1
- 2026TrEEStealer: Stealing Decision Trees via Enclave Side Channelscited by 0
- 2026TrEEStealer: Stealing Decision Trees via Enclave Side Channels20 Apr 2026
- 2026Opal: Private Memory for Personal AI2 Apr 2026
- 2024SoK: Towards Security and Safety of Edge AI7 Oct 2024
- 2024Dynamic Frequency-Based Fingerprinting Attacks against Modern Sandbox Environments16 Apr 2024
- 2022Edge Security: Challenges and Issues14 Jun 2022
- 2021Automated Side Channel Analysis of Media Software with Manifold Learning9 Dec 2021
- 2021Confidential Machine Learning Computation in Untrusted Environments: A Systems Security Perspective5 Nov 2021