Enarx: Confidential Computing with WebAssembly
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Updated
Aug 5, 2024 - Rust
Confidential Computing is the protection of data in use by performing computation in a hardware-based, attested Trusted Execution Environment.
A Trusted Execution Environment (TEE) is an environment that provides a level of assurance of the following three properties: data integrity, data confidentiality, and code integrity.
TEEs may have additional attributes such as code confidentiality, programmability, recoverability, and attestability.
Confidential Computing aims to reduce the ability for the owner/operator/pwner of a platform to access data and code inside TEEs sufficiently such that this path is not an economically or logically viable attack during execution.
Enarx: Confidential Computing with WebAssembly
Apache Teaclave (incubating) SGX SDK helps developers to write Intel SGX applications in the Rust programming language, and also known as Rust SGX SDK.
Apache Teaclave (incubating) is an open source universal secure computing platform, making computation on privacy-sensitive data safe and simple.
Teaclave TrustZone SDK enables safe, functional, and ergonomic development of trustlets.
Main repository for the Veracruz privacy-preserving compute project, an adopted project of the Confidential Compute Consortium (CCC).
Open source toolkit created to enable easy adoption of software enclaves
Nitrogen is a tool for deploying web services to AWS Nitro Enclaves.
Attestation and Secret Delivery Components
Assured confidential execution (ACE) implements VM-based trusted execution environment (TEE) for RISC-V with focus on a formally verified and auditable security monitor.
Libraries and tools for Confidential Computing on Azure
A Confidential Computing-Aware Certificate Authority
A Confidential Computing-Aware Workload Repository
CipherCompute: A more elaborated version of Yao's millionaire problem. Secret compute of KPIs
The authorization and key management module of TrustedFlow
The Supervisionary proof-checking kernel for higher-order logic
CipherCompute: Blind Join for Confidential Data Science and Federated Learning using MPC
A ledger for confidential computing (CC) shims for tracking memory management system calls