InterVRF

InterVRF is an open protocol and ecosystem designed to provide verifiable randomness across multiple blockchain networks. It enables developers on any supported chain to request randomness and receive a cryptographic proof that can be independently verified on-chain or off-chain, without relying on a single centralized source. By combining verifiable random function (VRF) outputs with cross-chain communication, InterVRF aims to deliver unbiased and auditable randomness for interoperable applications.

The architecture centers on a network of independent operator nodes that run threshold VRF signing keys. A randomness beacon aggregates entropy contributions from these operators and produces a VRF output together with a proof. Cross-chain messaging relays carry requests, proofs, and results between participating chains, while on-chain adapters translate the beacon output into chain-native randomness values that smart contracts can consume.

The security model relies on threshold cryptography and a distributed beacon to reduce single-point failure risk. Misbehavior can be deterred through stake-based incentives and verifiable proofs, with slashing or exclusion mechanisms for faulty or colluding participants. InterVRF typically assumes a majority of honest participants and transparent governance to manage updates, keys, and protocol parameters.

Interoperability and governance are central design goals. The protocol is intended to be blockchain-agnostic, providing standard interfaces and proof formats to simplify integration across ecosystems. Open-source reference implementations and test environments are commonly maintained, with governance often managed by a multi-stakeholder foundation or consortium that includes developers, operators, exchanges, and projects seeking cross-chain randomness.

Common use cases include randomness for DeFi protocols, NFT minting and airdrops, on-chain games, lotteries, and governance processes that require unbiased selection across different networks. Limitations include latency dependent on relay quality, reliance on a distributed set of honest participants, and the need for broad ecosystem adoption of adapters and tooling.