Who is Confidential Computing Consortium?
Confidential Computing Consortium is an open, cross-industry group that standardizes, promotes, and supports confidential computing technologies that protect data in use through hardware-based trusted execution environments.
- Vendor-neutral consortium focused on confidential computing architectures and adoption
- Technical collaboration around trusted execution environments (confidential computing / security)
- Reference projects, software tooling, and frameworks for confidential workloads (confidential computing / cloud security)
- Guidance, education, and best-practice materials for enterprises evaluating confidential computing (security architecture)
- Community governance, interoperability efforts, and outreach across hardware, cloud, and software providers
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More About Confidential Computing Consortium
The Confidential Computing Consortium is an industry group under the Linux Foundation that focuses on technologies which protect data while it is being processed, commonly referred to as protecting “data in use.” It brings together hardware vendors, cloud service providers, software companies, and research organizations to coordinate work on confidential computing, with an emphasis on trusted execution environments (TEEs) and related primitives that can be applied in enterprise and institutional environments.
The consortium’s work centers on confidential computing (confidential computing / cloud security), a security model in which data and code are isolated from the underlying infrastructure using hardware-based TEEs. These TEEs typically rely on processor extensions and cryptographic attestation protocols to ensure that only authorized code can access protected data, and that external parties can verify the integrity and configuration of that code before sharing sensitive workloads. Through this focus, the consortium targets use cases such as privacy-preserving analytics, secure multiparty computation, confidential Machine Learning (ML), and protection of regulated or proprietary data in shared or outsourced compute environments.
For enterprises, the consortium provides a vendor-neutral forum and technical resources that support evaluation and deployment of confidential computing across public cloud, hybrid, and edge environments. Its projects and reference implementations help architects understand how confidential computing can integrate with existing security controls, identity systems, key management, and workload orchestration. The consortium’s materials often address how TEEs interact with virtual machines, containers, and Kubernetes-based platforms, and how attestation workflows can be wired into admission control, policy engines, and DevSecOps pipelines.
The organization hosts and curates open source projects that implement or support confidential computing (open source security tooling). These include frameworks and SDKs for building TEE-aware applications, libraries for attestation and key provisioning, and integrations that connect confidential workloads to common cloud services. By aligning these projects under a shared governance and technical direction, the consortium encourages consistent approaches to concepts such as enclave lifecycle management, measurement and attestation formats, and interoperability across different hardware technologies.
In the broader enterprise IT landscape, the Confidential Computing Consortium fits into categories such as security architecture, cloud security, and privacy-preserving compute. Its guidance and community work are used by organizations that operate in regulated sectors, handle high-sensitivity data, or run workloads on shared infrastructure where hardware-rooted isolation is required. Through technical documentation, white papers, and cross-vendor collaboration, the consortium supports alignment on terminology, threat models, and reference architectures, which enterprises can use to map confidential computing capabilities into their security and compliance frameworks.
Our description of Confidential Computing Consortium. Updated January 2026.
