Implementation · PySyft double-blind evaluations
Sources
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- BA. Trask et al. (2026). Double Blind Evals: Resolving the Dual Confidentiality Dilemma in AI Safety Auditing. Google DeepMind. Source recordSupports: procedure, trust boundary, participants, model, private prompts, hardware, results and limits · §2.5; §3; §4
- COpenMined Team (2026). PySyft used for first double-blind evaluation of a proprietary, frontier-class AI model. OpenMined. Source recordSupports: OpenMined's description of PySyft and the two 2026 evaluations · Executive Summary
- AJ. Chuang et al. (2026). TEE.fail: Breaking Trusted Execution Environments via DDR5 Memory Bus Interposition. 2026 IEEE Symposium on Security and Privacy (SP). Source recordSupports: inherited Intel TDX physical-host attestation forgery and H100 relay; not a PySyft workflow evaluation · Abstract; §8.3; site FAQ
- AJ. De Meulemeester et al. (2026). DDRop: Active Memory Interposer Attacks on Confidential VMs by Dropping DDR5 Writes. 2026 ACM SIGSAC Conference on Computer and Communications Security (CCS '26). Source recordSupports: inherited DDR5 physical-host attack on Intel TDX; not a PySyft workflow evaluation · Threat model; TDX case studies