Confidential Computing Consortium (CCC)

The CCC standardizes the use of hardware-based TEEs to protect data in use. A TEE is a secure area within a main processor that guarantees code and data loaded inside is protected with respect to confidentiality and integrity.

• Intel SGX: Application-level enclaves for fine-grained memory encryption
• Intel TDX: Full VM-level confidentiality isolating entire workloads from the hypervisor
• AMD SEV-SNP: Memory integrity protection preventing malicious hypervisor attacks
• ARM CCA: Realm-based isolation for ARM architecture processors

These technologies form the foundational hardware layer that the CCC's software ecosystem builds upon.

The CCC hosts and governs critical open-source projects that abstract hardware complexity. The Open Enclave SDK is a consortium-governed framework enabling developers to write TEE applications once and deploy across multiple hardware backends.

• Single codebase for Intel SGX and AMD SEV targets
• Standardized APIs for enclave lifecycle management
• Built-in cryptographic attestation primitives
• Integration with existing CI/CD pipelines

This abstraction layer is essential for avoiding vendor lock-in and enabling portable confidential computing workloads.

Gramine (formerly Graphene) is a CCC project that allows unmodified Linux applications to run inside Intel SGX enclaves. It bridges the gap between standard POSIX APIs and the constrained enclave environment without requiring application rewrites.

• Runs unmodified Python, Java, and C/C++ applications
• Handles system call translation into enclave-compatible operations
• Supports multi-process applications within a single enclave
• Enables legacy AI workloads to gain confidential computing protections

Gramine dramatically lowers the barrier to entry for organizations adopting TEE technology.

The CCC drives standardization of attestation—the cryptographic process of verifying a TEE's identity and integrity before releasing secrets or accepting computation results. This is the trust anchor for all confidential computing workflows.

• Hardware Attestation: Verifies the CPU manufacturer and TEE type
• Firmware Measurement: Validates the TEE's boot chain has not been tampered with
• Software Measurement: Confirms the exact code loaded matches a known hash
• SPIRE Integration: The SPIFFE Runtime Environment provides attestation-based workload identity

Without standardized attestation, remote parties cannot verify that a claimed TEE is genuine.

The CCC operates under a vendor-neutral governance model within the Linux Foundation, ensuring no single entity controls the direction of confidential computing standards. Premier members include Intel, AMD, ARM, Google, Microsoft, and Alibaba.

• Technical Advisory Council (TAC) oversees project lifecycle
• End User Advisory Council provides practitioner feedback
• Open contribution model with Apache 2.0 licensing
• Regular Technical Meetings and annual Confidential Computing Summit

This governance structure ensures that TEE standards evolve based on real-world enterprise requirements rather than any single vendor's roadmap.

A growing focus of the CCC is Confidential AI—ensuring that proprietary model weights and inference data remain encrypted during computation. The consortium defines patterns for running AI workloads entirely within TEEs.

• Model Provenance Attestation: Cryptographically verifies the exact model loaded in a TEE
• Confidential RAG: Retrieval and generation both occur within an enclave
• Secure GPU Attestation: Extends TEE verification to NVIDIA confidential computing GPUs
• Confidential Inference Services: Model endpoints invisible to cloud providers

These patterns protect intellectual property in AI models while ensuring client data privacy during inference.