Open Source Project


RISC Zero is a zero-knowledge verifiable general computing platform based on zk-STARKs and the RISC-V microarchitecture.


RISC Zero is an innovative computing platform that leverages the principles of zero-knowledge proofs, specifically utilizing zk-STARKs, within the framework of the RISC-V microarchitecture. The concept of zero-knowledge proofs is a cryptographic method that allows one party, known as the prover, to prove to another party, the verifier, that a certain statement is true, without revealing any information beyond the veracity of the statement itself. zk-STARKs, standing for Zero-Knowledge Scalable Transparent Arguments of Knowledge, are a form of zero-knowledge proof that are designed to be both scalable and transparent, making them well-suited for widespread use.

Incorporating this cryptographic technique with the RISC-V microarchitecture, which is an open standard instruction set architecture (ISA) based on reduced instruction set computing (RISC) principles, RISC Zero offers a platform for general computing that is secure and maintains privacy. The RISC-V architecture is known for its simplicity, efficiency, and scalability, characteristics that are beneficial for a wide range of computing applications.

By combining these technologies, RISC Zero enables the execution of code in a manner that ensures the privacy of the inputs and the internal state of the computation. This means that when a prover executes some code on the RISC Zero platform, they can prove to a verifier that the code was executed correctly and produce the correct output, without disclosing any information about the inputs used or the internal computation process. This feature is particularly valuable in scenarios where the confidentiality of the data is crucial, yet there is also a need to verify the correctness of the computation. For example, it can be used in financial transactions, confidential computing environments, and any application where privacy and security are paramount.

RISC Zero’s approach not only enhances privacy and security in computing but also opens up new possibilities for applications that require data confidentiality without compromising on the correctness and integrity of the computational process.

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