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Confidential Computing

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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.

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Themxhiguy / AegisEdgeAI

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🔒 Secure AI at the edge by binding user, device, and workload identities to ensure integrity, compliance, and trusted operations in real-time.

trusted-platform-module hardware-security-module zero-trust kubernetes-security workload-identity confidential-computing measured-boot llm workload-identity-federation model-context-protocol cryptographic-verification hardware-root-of-trust spiffe-spire verifiable-geofencing
  • Updated Dec 18, 2025
  • Python

lfedgeai / AegisSovereignAI

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AegisSovereignAI: The Trust Integration Layer for the LF AI & Data Ecosystem. Verifiable identity, hardware integrity, and sovereignty for the Distributed Enterprise - from Silicon to Prompt.

trusted-platform-module hardware-security-module zero-trust kubernetes-security workload-identity confidential-computing measured-boot llm workload-identity-federation model-context-protocol cryptographic-verification hardware-root-of-trust spiffe-spire verifiable-geofencing
  • Updated Dec 17, 2025
  • Go
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github.com/topics/confidential-computing
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confidential-container tee trusted-execution trusted-execution-environment