Inferensys

Glossary

Confidential Consortium Framework (CCF)

An open-source framework for building secure, highly available, and performant multi-party applications that leverage Trusted Execution Environments for tamper-proof, transparent governance.
Governance lead reviewing model governance framework on laptop, policy documents visible, executive office setup.
MULTI-PARTY CONFIDENTIAL COMPUTING

What is Confidential Consortium Framework (CCF)?

An open-source framework for building secure, highly available, and performant multi-party applications that leverage Trusted Execution Environments for tamper-proof, transparent governance.

The Confidential Consortium Framework (CCF) is an open-source platform for building multi-party applications where governance and data are protected by a Trusted Execution Environment (TEE). It provides a high-throughput, low-latency ledger that combines a key-value store with a programmable governance model, ensuring that all operations are executed according to a transparent, auditable constitution agreed upon by the consortium members.

CCF achieves consensus across a network of nodes, each running inside a hardware-enforced enclave that provides data-in-use protection. Through remote attestation, every node cryptographically proves its integrity to users and other members, creating a tamper-proof execution history. This architecture enables mutually distrusting parties to collaborate on sensitive data without revealing it to a central operator, making CCF ideal for auditable supply chains, secure multi-party analytics, and decentralized identity systems.

ARCHITECTURAL PILLARS

Core Characteristics of CCF

The Confidential Consortium Framework is built on a set of core design principles that enable transparent, highly available, and secure multi-party computation governed by a consortium.

01

Decentralized Governance by Consortium

CCF replaces a single administrative root with a constitution—a JavaScript script that defines the rules for membership and operation. All changes to the network, such as adding new members or updating the application code, are governed by member votes recorded on a tamper-proof ledger. This ensures no single operator can unilaterally alter the service, providing transparent, auditable control for all consortium members.

JavaScript
Constitution Language
Multi-Sig
Governance Model
02

Hardware-Enforced Trust with TEEs

Every node in a CCF network runs its core logic inside a Trusted Execution Environment (TEE)—a hardware-isolated enclave. This guarantees the confidentiality and integrity of data and code during execution, protecting it from the host operating system, cloud operators, and other tenants. CCF supports multiple TEE backends, including Intel SGX and AMD SEV-SNP, providing a hardware root of trust for all computations.

SGX & SEV-SNP
Supported TEEs
03

Tamper-Proof Audit Logging

CCF maintains a Merkle tree-based ledger that records every transaction, governance vote, and state change. This cryptographic structure makes the log immutable and append-only; any attempt to tamper with a historical record is immediately detectable. The ledger provides a verifiable audit trail that allows any third party to cryptographically prove the exact sequence of operations and the integrity of the service's history.

Merkle Tree
Ledger Structure
04

High Availability via Crash Fault Tolerance

CCF is designed for Crash Fault Tolerance (CFT) using the Raft consensus protocol. A network of nodes elects a primary that replicates a log of all transactions to a majority of followers. If the primary fails, a new leader is automatically elected, ensuring the service remains available. This architecture provides strong consistency guarantees and is resilient to node failures without sacrificing performance.

Raft
Consensus Protocol
CFT
Fault Model
05

Remote Attestation for Verifiable Trust

Before any client or member interacts with a CCF node, they perform remote attestation. This cryptographic protocol verifies two things: that the node is running genuine CCF code inside a valid TEE, and that it is a recognized member of the consortium. This process establishes a verifiable trust anchor without relying on the reputation of the cloud provider, ensuring the service's integrity from the moment a connection is established.

Cryptographic
Trust Establishment
06

Virtualized Multi-Application Hosting

A single CCF network can host multiple independent, logically isolated applications. Each application has its own private JavaScript runtime and state, managed by a shared governance layer. This multi-tenancy allows a consortium to operate a single infrastructure for diverse use cases—such as a confidential token exchange and a private voting system—while maintaining strict separation between their data and logic.

Isolated
Application Sandboxing
CONFIDENTIAL CONSORTIUM FRAMEWORK

Frequently Asked Questions

Clear, technical answers to the most common questions about the architecture, governance, and security model of the Confidential Consortium Framework.

The Confidential Consortium Framework (CCF) is an open-source framework for building secure, highly available, and performant multi-party applications that leverage Trusted Execution Environments (TEEs) for tamper-proof, transparent governance. It works by executing a defined set of application logic inside a hardware-enforced enclave across a network of nodes. A CCF network is governed by a consortium of members, where all operations—such as adding new members or deploying application code—are subject to a configurable voting policy recorded in an append-only, tamper-proof ledger. The framework combines confidential computing (protecting data in use) with a Byzantine Fault Tolerant (BFT) consensus protocol, ensuring that the service remains available and trustworthy even if a subset of nodes is compromised or malicious. This allows mutually distrusting parties to collaborate on shared data and logic without any single party having unilateral control.

CONFIDENTIAL CONSORTIUM FRAMEWORK

Real-World Applications of CCF

The Confidential Consortium Framework (CCF) enables a new class of multi-party applications where governance, auditability, and data confidentiality are enforced by a hardware-backed Trusted Execution Environment. Below are key application domains where CCF's unique properties—transparent governance, tamper-proof audit logs, and high-throughput confidential compute—solve critical industry problems.

01

Decentralized Identity & Verifiable Credentials

CCF serves as a transparent, decentralized Public Key Infrastructure (PKI) for managing Decentralized Identifiers (DIDs). A consortium of trusted issuers can govern the DID registry, with all state transitions recorded in a tamper-proof, append-only ledger.

  • Key Benefit: Eliminates single points of failure in identity systems.
  • Mechanism: The CCF network acts as a verifiable data registry, where credential revocation lists and DID documents are stored with cryptographic proof of integrity.
  • Example: Government agencies and telecom providers forming a consortium to issue and revoke mobile driver's licenses without a central authority.
Byzantine Fault Tolerant
Governance Model
02

Secure Multi-Party Asset Settlement

Financial market infrastructures use CCF to build atomic settlement networks that bridge disparate ledgers without exposing proprietary trading strategies. The framework's confidential transactions ensure that trade details are visible only to counterparties, while regulators maintain a cryptographic audit trail.

  • Key Benefit: Reduces settlement latency from days to seconds.
  • Mechanism: Smart contracts executed inside the enclave atomically swap digital assets, with the receipts providing non-repudiable proof of execution.
  • Example: A consortium of central and commercial banks operating a wholesale CBDC platform where inter-bank transfers settle instantly with embedded compliance checks.
< 1 sec
Transaction Finality
03

Confidential Federated Learning Aggregation

CCF provides a secure aggregation service for federated learning, replacing the traditional trusted central server with a network of enclaves governed by the data owners themselves. Model updates are decrypted and aggregated entirely within the hardware-protected boundary.

  • Key Benefit: Provides cryptographic proof that the aggregator cannot inspect individual client gradients.
  • Mechanism: Clients encrypt model updates to the CCF enclave; the enclave performs secure weighted averaging and publishes the new global model, with an auditable receipt of the computation.
  • Example: A consortium of hospitals collaboratively training a tumor detection model without any single hospital or the aggregator accessing raw patient data or individual model updates.
Hardware-Backed
Privacy Guarantee
04

Transparent Software Supply Chain Ledger

CCF acts as a universal, immutable ledger for software bill of materials (SBOM) and build attestations. A consortium of software vendors and consumers governs the network, ensuring that no single entity can tamper with the provenance records of critical open-source or proprietary components.

  • Key Benefit: Enables real-time, cryptographically verifiable compliance with Executive Order 14028.
  • Mechanism: Build pipelines submit signed in-toto attestations directly to the CCF network, which validates signatures and records the metadata in a tamper-proof Merkle tree.
  • Example: A consortium of cloud providers and enterprise users maintaining a shared registry of verified container image signatures, ensuring that a compromised CI/CD pipeline cannot rewrite release history.
Immutable
Audit Trail
05

Regulated Confidential Data Exchange

CCF enables data clean rooms where multiple parties can contribute sensitive datasets for joint analysis without revealing raw data to each other or the platform operator. The governance framework ensures that only pre-approved queries are executed.

  • Key Benefit: Enforces data usage policies through code, not just contracts.
  • Mechanism: Analysts submit queries that are executed within the enclave; only the differentially private or aggregated result is released, with a full audit log of who queried what and when.
  • Example: A consortium of retail banks sharing fraud indicators to improve collective detection models without exposing their individual customer transaction histories.
Policy-Enforced
Data Access
06

Decentralized Certificate Transparency

CCF provides a consortium-governed alternative to centralized certificate transparency (CT) logs, eliminating the single-operator trust model. Multiple Certificate Authorities (CAs) and browser vendors jointly operate the log, ensuring no single entity can split-view or tamper with the log.

  • Key Benefit: Prevents a compromised CA from hiding mis-issued certificates.
  • Mechanism: The CCF network maintains a cryptographically consistent, append-only Merkle tree of all issued certificates, with gossip protocols ensuring global visibility.
  • Example: A consortium of browser vendors and CAs operating a next-generation CT log that is resilient to the compromise of any single member.
ARCHITECTURAL COMPARISON

CCF vs. Traditional Blockchains

Key architectural and operational differences between the Confidential Consortium Framework and traditional permissioned or permissionless blockchain platforms.

FeatureConfidential Consortium Framework (CCF)Permissioned Blockchain (e.g., Hyperledger Fabric)Permissionless Blockchain (e.g., Ethereum)

Consensus Model

Crash Fault Tolerant (CFT) with TEE-based integrity

Pluggable (CFT or BFT); typically CFT with ordering service

Byzantine Fault Tolerant (BFT) via Proof-of-Stake or Proof-of-Work

Transaction Confidentiality

Private channels/collections available

Hardware Root of Trust

Governance Mechanism

Member-managed constitution with cryptographic proposals and votes

Policy-based via certificate authorities and channel configs

Off-chain social consensus or token-weighted on-chain voting

Smart Contract Execution Environment

In-enclave; isolated from host OS and operator

In-container or native process; visible to node operator

On-chain virtual machine (EVM); transparent to all validators

Data-in-Use Protection

Typical Throughput

Thousands of transactions per second

Hundreds to thousands of transactions per second

15-30 transactions per second (L1)

Energy Efficiency

High (standard CPU execution)

High (standard CPU execution)

Low (Proof-of-Work); High (Proof-of-Stake)

Prasad Kumkar

About the author

Prasad Kumkar

CEO & MD, Inference Systems

Prasad Kumkar is the CEO & MD of Inference Systems and writes about AI systems architecture, LLM infrastructure, model serving, evaluation, and production deployment. Over 5+ years, he has worked across computer vision models, L5 autonomous vehicle systems, and LLM research, with a focus on taking complex AI ideas into real-world engineering systems.

His work and writing cover AI systems, large language models, AI agents, multimodal systems, autonomous systems, inference optimization, RAG, evaluation, and production AI engineering.