LFX Mentorship Active 2026
LFDT - Implementation of a ZK-SNARK Token Driver for Hyperledger Fabric using gnark
Hyperledger1 Program Years
LFDT - Implementation of a ZK-SNARK Token Driver for Hyperledger Fabric using gnark
About the Organization
<p>This project aims to implement a new privacy-preserving token driver for the Hyperledger Fabric Token SDK. The architecture will follow the blueprint established in the paper "Privacy-preserving auditable token payments in a permissioned blockchain system" (Androulaki et al.), which outlines a token management system tailored for enterprise networks that requires binding tokens to user identities while supporting fine-grained auditing functionalities for AML/KYC compliance.</p><p><br></p><p>While the original paper relies on specific zero-knowledge proofs and commitments, this mentorship project will adapt the cryptographic backend to utilize zk-SNARKs via gnark, a high-performance ZK-SNARK library written in Go by Consensys. The mentee will be responsible for designing the required ZK circuits for minting, transferring, and auditing tokens, and subsequently integrating these circuits into a fully functional token driver within the Fabric Token SDK framework.</p><p><br></p><h3>Learning Objectives</h3><ul><li>Gain a comprehensive understanding of the Hyperledger Fabric Token SDK architecture and the role of token drivers.</li><li>Develop practical expertise in Zero-Knowledge Proofs (zk-SNARKs) and circuit design using the gnark library.</li><li>- Understand the cryptographic mechanisms behind privacy-preserving enterprise blockchains, including UTXO models, Pedersen commitments, and identity-bound token ownership.</li><li>Enhance skills in writing highly optimized, concurrent, and secure Go code for distributed systems.</li></ul><h3>Expected Outcome and Deliverables</h3><ul><li>Fully functional gnark circuits implementing the logic for token issuance, private transfers, and auditor revelation as described in the blueprint paper.</li><li>A new ZK-SNARK token driver completely integrated into the Hyperledger Fabric Token SDK.</li><li>A comprehensive test suite, including unit and integration tests for the driver and circuits.</li><li>- Performance benchmarks evaluating proof generation times, verification times, and transaction throughput compared to existing FTS token drivers.</li><li>Technical documentation detailing the circuit design, driver architecture, and usage instructions.</li></ul><p><br></p><p>Lean more at <a href="https://github.com/LF-Decentralized-Trust-Mentorships/mentorship-program/issues/67" rel="noopener noreferrer" target="_blank">https://github.com/LF-Decentralized-Trust-Mentorships/mentorship-program/issues/67</a></p>
Primary Technologies & Languages
gohyperledger fabriczkpdlt
Technical Topics & Focus Areas
gohyperledger fabriczkpdlt
Participation Years
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Annual Completed Projects History
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LFDT - Implementation of a ZK-SNARK Token Driver for Hyperledger Fabric using gnark Mentorship Project
Intermediate<p>This project aims to implement a new privacy-preserving token driver for the Hyperledger Fabric Token SDK. The architecture will follow the blueprint established in the paper "Privacy-preserving auditable token payments in a permissioned blockchain system" (Androulaki et al.), which outlines a token management system tailored for enterprise networks that requires binding tokens to user identities while supporting fine-grained auditing functionalities for AML/KYC compliance.</p><p><br></p><p>While the original paper relies on specific zero-knowledge proofs and commitments, this mentorship project will adapt the cryptographic backend to utilize zk-SNARKs via gnark, a high-performance ZK-SNARK library written in Go by Consensys. The mentee will be responsible for designing the required ZK circuits for minting, transferring, and auditing tokens, and subsequently integrating these circuits into a fully functional token driver within the Fabric Token SDK framework.</p><p><br></p><h3>Learning Objectives</h3><ul><li>Gain a comprehensive understanding of the Hyperledger Fabric Token SDK architecture and the role of token drivers.</li><li>Develop practical expertise in Zero-Knowledge Proofs (zk-SNARKs) and circuit design using the gnark library.</li><li>- Understand the cryptographic mechanisms behind privacy-preserving enterprise blockchains, including UTXO models, Pedersen commitments, and identity-bound token ownership.</li><li>Enhance skills in writing highly optimized, concurrent, and secure Go code for distributed systems.</li></ul><h3>Expected Outcome and Deliverables</h3><ul><li>Fully functional gnark circuits implementing the logic for token issuance, private transfers, and auditor revelation as described in the blueprint paper.</li><li>A new ZK-SNARK token driver completely integrated into the Hyperledger Fabric Token SDK.</li><li>A comprehensive test suite, including unit and integration tests for the driver and circuits.</li><li>- Performance benchmarks evaluating proof generation times, verification times, and transaction throughput compared to existing FTS token drivers.</li><li>Technical documentation detailing the circuit design, driver architecture, and usage instructions.</li></ul><p><br></p><p>Lean more at <a href="https://github.com/LF-Decentralized-Trust-Mentorships/mentorship-program/issues/67" rel="noopener noreferrer" target="_blank">https://github.com/LF-Decentralized-Trust-Mentorships/mentorship-program/issues/67</a></p>