awesome-confidential-computing
github.com/bpradipt/awesome-confidential-computing ↗Collection of resources on Confidential Computing
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Installation instructions →What's inside
Products and Offerings
- Acurast - Confidential compute on smartphone TEEs
Confidential compute on smartphone TEEs
- AWS Confidential Computing Offerings
- Azure Confidential Computing Offerings
- CCC / Linux Foundation Study on Confidential Computing AdoptionMarket and Adoption Studies
- Google Confidential Computing Offerings
- IBMCloud Confidential Computing Offerings
Hardware with CC support
CC Software Stack (Active and Open source)
- Apache Teaclave
- CNCF Confidential Containers
- Ego
- Enarx
- Gramine Library OS
- Hypervisor (ARM64 S-EL2 SPMC)
ARM64 Type-1 bare-metal hypervisor and S-EL2 SPMC in no_std Rust. Implements FF-A v1.1 memory sharing with Stage-2 PTE page ownership tracking (pKVM-compatible), manages Secure Partitions at S-EL1, and coexists with pKVM at NS-EL2
Attestation
Security Threats and Vulnerabilities
- A Survey of RISC-V Secure Enclaves and TEE Vulnerabilities (2025)Attack Surveys and Analysis
- BadRAMSide-Channel Attacks
- CounterSEVeillance - Performance Counter Attacks on AMD SEV-SNPSide-Channel Attacks
Performance Counter Attacks on AMD SEV-SNP
- Heracles - Chosen Plaintext Attack on AMD SEV-SNP (2025)Side-Channel Attacks
Chosen Plaintext Attack on AMD SEV-SNP (2025)
- TEE.Fail - DDR5 Memory Bus Attack on Intel SGX/TDX and AMD SEV-SNP (2025)Side-Channel Attacks
DDR5 Memory Bus Attack on Intel SGX/TDX and AMD SEV-SNP (2025)
- TEE Security Analysis - Trust Issues in Execution EnvironmentsAttack Surveys and Analysis
Trust Issues in Execution Environments
Misc
Confidential AI
- Confidential AI - Private, verifiable AI inference, agents, and training. Hosted and self-hosted.
Private, verifiable AI inference, agents, and training. Hosted and self-hosted.
- Confidential Inference Directory
Compare TEE-based AI inference providers by models, pricing, and live attestation evidence.
- dstack
- Google Confidential Accelerators for AI Workloads
- NVIDIA Confidential Computing for Secure AI
- NVIDIA Secure AI Whitepaper (Blackwell & Hopper)
Academic Papers
- Confidential Computing across Edge-to-Cloud for ML: A Survey
- CoVE: Confidential Computing on RISC-V Platforms
- Efficient Privacy-Preserving ML with Lightweight TEE (PETS 2024)
- GATOR-V: Production-Grade TEE for RISC-V
- Keystone: An Open Framework for Architecting TEEs
- NVIDIA GPU Confidential Computing Demystified
Showing a sample of 87 resources. View the full list on GitHub →