Constellation is the first Confidential Kubernetes. Constellation shields entire Kubernetes clusters from the (cloud) infrastructure using confidential computing.
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Updated
Aug 7, 2024 - Go
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.
Constellation is the first Confidential Kubernetes. Constellation shields entire Kubernetes clusters from the (cloud) infrastructure using confidential computing.
MarbleRun is the control plane for confidential computing. Deploy, scale, and verify your confidential microservices on vanilla Kubernetes. 100% Go, 100% cloud native, 100% confidential.
Attestation and Secret Delivery Components
A Confidential Computing-Aware Workload Repository
The authorization and key management module of TrustedFlow
Scripts for secure deployments of the Anjuna Policy Manager
Enarx: Confidential Computing with WebAssembly
Regorus - A fast, lightweight Rego (OPA policy language) interpreter written in Rust.
Reference code for creating and verifying a GCE firmware signed reference value message.
A unified framework for privacy-preserving data analysis and machine learning
Key provider middleware
A privacy-preserving computing system based on TEE.
Unified API to Access TCG Compliant measurement, event log, quote in Confidential Computing Environment.
A curated list of resources for learning about Trusted Execution Environments (TEEs) in the context of blockchains.
MPyC: Multiparty Computation in Python
A platform that enables users to perform private benchmarking of machine learning models. The platform facilitates the evaluation of models based on different trust levels between the model owners and the dataset owners.
Versatile framework for multi-party computation
Template repository for CCF apps
Kubernetes Trusted Platform Module (TPM) DaemonSet