Blockchain's promise of transparency often conflicts with the need for privacy in enterprise and financial applications. Systems handling sensitive data—like medical records or confidential transactions—require confidentiality. However, regulations such as Anti-Money Laundering (AML) laws and the Travel Rule mandate that financial institutions verify identities and monitor transactions. This creates a fundamental tension: how can a system be both private and compliant?
LABS
Guides
How to Align ZK-SNARKs With Compliance
A technical guide for developers on designing ZK-SNARK systems that meet regulatory requirements for auditability and selective disclosure, without compromising core privacy guarantees.
Chainscore © 2026
introduction
ZK-SNARKS & REGULATION
Introduction: The Compliance Challenge for Private Systems
Zero-knowledge proofs offer privacy, but regulatory frameworks demand transparency. This guide explores how to reconcile these opposing forces using ZK-SNARKs.
Zero-knowledge proofs, specifically ZK-SNARKs (Zero-Knowledge Succinct Non-Interactive Argument of Knowledge), provide a cryptographic solution. They allow one party (the prover) to convince another (the verifier) that a statement is true without revealing any underlying information. For example, a user can prove they are over 18 without disclosing their birthdate, or that a transaction is valid without showing the amount or sender. This technology is the foundation for private yet verifiable systems.
The compliance challenge is not about removing privacy but about designing selective disclosure mechanisms. A ZK-SNARK circuit can be programmed to prove compliance with specific rules. A user could generate a proof demonstrating that a private transaction: (1) does not involve a sanctioned address, (2) originates from a KYC-verified identity, and (3) falls within regulatory limits—all without revealing the transaction's details to the public chain. The verifier, often a regulator or a smart contract, only sees the proof's validity.
Implementing this requires careful system design. The trust model shifts from viewing raw data to trusting the correctness of the circuit logic and the setup ceremony. Developers must encode legal and business rules directly into arithmetic circuits. For instance, a circuit for a compliant private transfer might include checks against an on-chain, privacy-preserving sanction list using a Merkle tree, where the user proves non-membership without revealing which list entry they checked.
Several projects are pioneering this approach. Zcash introduced the concept of shielded transactions with viewing keys for auditability. Aztec Network allows developers to build private smart contracts with compliance features baked in. Mina Protocol uses recursive ZK-SNARKs to maintain a constant-sized blockchain, with potential for private credential verification. These implementations show that technical solutions for compliant privacy are actively being built and tested.
The path forward involves collaboration between technologists, legal experts, and regulators. Standards for proof-of-compliance circuits and secure attestation frameworks are needed. By leveraging ZK-SNARKs, we can build systems that uphold individual privacy rights while fulfilling societal obligations for security and accountability, moving beyond the false dichotomy of privacy versus compliance.
prerequisites
FOUNDATIONAL KNOWLEDGE
Prerequisites and Core Assumptions
Before implementing ZK-SNARKs for compliance, you need a solid technical foundation and a clear understanding of the regulatory and cryptographic assumptions involved.
To effectively align ZK-SNARKs with compliance frameworks, you must first establish a strong technical baseline. This includes proficiency in cryptographic primitives like elliptic curve pairings and hash functions, as well as familiarity with zero-knowledge proof concepts (e.g., R1CS, QAP). You should be comfortable with a proving system such as Groth16 or PLONK, often implemented using libraries like circom or snarkjs. A working knowledge of a smart contract platform like Ethereum is also essential, as compliance proofs are typically verified on-chain. This technical stack is non-negotiable for building compliant, verifiable systems.
The core cryptographic assumption underpinning most ZK-SNARKs is the Knowledge of Exponent (KoE) assumption and the security of selected elliptic curves (e.g., BN254, BLS12-381). You must trust that these underlying mathematical problems are computationally hard. Furthermore, a critical prerequisite is the secure generation and handling of the system's trusted setup (Common Reference String or CRS). For compliance, this process often requires a multi-party ceremony with auditable participants to ensure no single entity can generate fraudulent proofs. The integrity of the entire system depends on this initial, verifiably honest setup.
From a compliance perspective, you must define the precise regulatory logic that will be proven. This involves translating legal or policy rules—such as KYC checks, transaction limits, or jurisdictional whitelists—into a computable circuit. The assumptions here are that the circuit correctly encodes the rule and that the private inputs (user data) fed into it are authentic. For instance, a circuit proving a user is over 18 might assume the provided birth date is truthful; oracle or attestation systems are often needed to bridge this trust gap between real-world data and the proof.
Finally, you must architect your system with clear data separation. ZK-SNARKs enable selective disclosure: proving a statement is true without revealing the underlying data. Your application logic must be designed to keep private witness data off-chain while submitting only the proof and public outputs to the immutable ledger. This requires careful state management and often a client-side proving component. The assumption is that users can and will run a proving client, which has implications for usability and decentralization.
key-concepts-text
PRIVACY AND REGULATION
How to Align ZK-SNARKs With Compliance
Zero-Knowledge Succinct Non-Interactive Arguments of Knowledge (ZK-SNARKs) offer powerful privacy, but their opacity can conflict with regulatory requirements. This guide explains how to design compliant ZK systems.
ZK-SNARKs allow a prover to convince a verifier that a statement is true without revealing the underlying data. For compliance, the core challenge is balancing this privacy with the need for auditability. Regulators often require selective disclosure—the ability to reveal specific transaction details under defined conditions, such as a court order. A compliant ZK system must be built with this capability from the start, not added as an afterthought.
The primary technical mechanism for compliance is a trusted setup or a view key. In a trusted setup, a set of cryptographic parameters is generated by multiple parties; if a threshold of these parties cooperates, they can reconstruct information to decrypt specific proofs. A view key is a private key held by a designated entity (e.g., a regulator) that allows them to decrypt the encrypted notes or states within a ZK circuit, enabling transaction tracing without breaking privacy for all users.
Implementing this requires careful circuit design. Your ZK circuit, written in a language like Circom or ZoKrates, must output not just a validity proof but also encrypted logs or commitments. For example, a private transaction circuit could output an encrypted note commitment and a nullifier. The view key holder can decrypt the commitment to see the transaction amount and participants, while the nullifier proves the note was spent without revealing which new note it created.
Real-world protocols demonstrate this balance. Zcash (zcash) implemented the Viewing Key system, allowing users to share transaction details with auditors. Aztec Network uses a Data Availability Committee and escape hatches where, under consensus, transactions can be forced to publish their data to a public rollup. These models show that compliance isn't about removing privacy, but about creating verifiable, conditional transparency.
For developers, the steps are: 1) Define the compliance requirement (e.g., FATF Travel Rule, tax reporting). 2) Design the ZK circuit to output necessary encrypted data or commitments. 3) Implement a secure key management system for view keys or multi-party computation for trusted setup. 4) Integrate an oracle or attestation system to trigger disclosure only upon receiving a valid legal credential. This ensures privacy by default and transparency by necessity.
The future of compliant ZK lies in recursive proofs and proof-carrying data. These allow the aggregation of many private transactions into a single proof that can be audited at a high level for statistical compliance (e.g., total volume, sanctions screening) without inspecting individual data. This aligns with privacy-enhancing technologies (PETs) frameworks advocated by regulators like the UK's ICO, which recognize that privacy and lawful investigation are not mutually exclusive goals.
compliance-patterns
PRIVACY & REGULATION
Technical Patterns for Compliant ZK-SNARKs
Design patterns and cryptographic primitives for building zero-knowledge applications that satisfy regulatory requirements like AML/KYC, sanctions screening, and transaction monitoring.
ARCHITECTURE
Comparison of Compliance Integration Methods for ZK-SNARKs
Methods for embedding regulatory compliance into zero-knowledge proof systems, comparing technical approaches and trade-offs.
| Feature / Metric | On-Chain Verifier | Off-Chain Attestation | Hybrid Proof Composition |
|---|---|---|---|
Proof Verification Location | Smart Contract | Trusted Service | Smart Contract & Service |
Data Privacy for Regulator | |||
User Identity Exposure | Public (ZK) | Private (Regulator) | Private (Regulator) |
Gas Cost per Verification | $15-50 | $0.5-2 | $5-20 |
Latency to Finality | < 1 sec | 2-10 sec | 1-5 sec |
Censorship Resistance | |||
Requires Trusted Third Party | |||
Audit Trail Transparency | Fully Public | Regulator-Only | Selectively Revealable |
implementation-steps
ZK-SNARKS & COMPLIANCE
Step-by-Step Implementation Guide
Practical steps for developers to integrate privacy-preserving ZK-SNARKs with regulatory frameworks like AML and KYC.
ZK-SNARKS & COMPLIANCE
Common Implementation Mistakes and Pitfalls
Integrating zero-knowledge proofs with regulatory frameworks introduces unique technical challenges. This guide addresses frequent developer errors in achieving compliant ZK-SNARK implementations.
A common failure point is the circuit's inability to prove specific statements about private inputs without revealing them. For compliance (e.g., proving age > 18 without revealing birthdate), the circuit must be designed with granular, verifiable predicates.
Key mistakes include:
- Building a circuit that outputs a simple
true/falsefor an entire transaction, lacking the predicate structure for auditors. - Hard-coding compliance rules directly into the circuit logic, making updates impossible without redeploying the entire proving system.
- Not implementing nullifier schemes correctly, which can lead to double-spending of credentials or inability to uniquely identify a compliant action.
Solution: Design circuits using tools like circom or noir to output a cryptographic commitment to the compliant subset of data. The verifier (auditor) can then check this commitment against a known policy. Frameworks like Semaphore or Tornado Cash's note system demonstrate this pattern for anonymity sets, which can be adapted for compliance proofs.
PRACTICAL APPLICATIONS
Implementation Examples by Use Case
Selective Disclosure for Auditors
Regulators often require proof of compliance without exposing sensitive transaction details. ZK-SNARKs enable selective disclosure, where a protocol can prove it adhered to rules like sanctions screening or transaction limits.
Example: Proof of Sanctions Compliance A DeFi protocol can generate a ZK proof that:
- All user addresses in a batch transaction were checked against an OFAC list.
- No sanctioned addresses were included in the transaction.
- The proof reveals only the final compliance status, not the individual addresses checked.
solidity// Simplified interface for a compliance verifier contract interface IComplianceVerifier { function verifySanctionsProof( bytes calldata proof, bytes32 publicInputHash // Hash of the public inputs (e.g., block number, rule ID) ) external view returns (bool); }
This allows auditors to verify compliance on-chain without gaining access to private user data, aligning with privacy regulations like GDPR.
tools-frameworks
ZK-COMPLIANCE
Tools and Frameworks for Development
A curated guide to the libraries, standards, and frameworks that enable developers to build compliant zero-knowledge applications.
resource-links
COMPLIANCE AND ZERO-KNOWLEDGE
Essential Resources and Documentation
These resources help developers align ZK-SNARK-based systems with regulatory requirements such as KYC, AML, and transaction monitoring. Each card focuses on concrete tools or specifications used in production systems to reconcile privacy guarantees with auditability.
ZK-SNARKS & COMPLIANCE
Frequently Asked Questions (FAQ)
Common technical and implementation questions about integrating zero-knowledge proofs with regulatory frameworks like AML, KYC, and transaction monitoring.
A ZK-SNARK (Zero-Knowledge Succinct Non-Interactive Argument of Knowledge) is a cryptographic proof system. It allows one party (the prover) to prove to another (the verifier) that a statement is true without revealing any information beyond the validity of the statement itself.
For compliance, this enables selective disclosure. A user can prove they are over 18, are not on a sanctions list, or that a transaction adheres to rules, without exposing their full identity or transaction history. The core components are:
- Witness: The private input (e.g., user's date of birth).
- Circuit: The public constraint system (e.g., "age >= 18").
- Proof: A small, quickly verifiable cryptographic attestation that the witness satisfies the circuit. Protocols like zkSync and Aztec use ZK-SNARKs to bundle private transactions with public validity proofs that can be audited.
conclusion
IMPLEMENTATION PATH
Conclusion and Next Steps
This guide has outlined the technical and procedural foundations for integrating ZK-SNARKs into compliance frameworks. The next steps involve practical implementation and staying current with evolving standards.
Successfully aligning ZK-SNARKs with compliance requires moving from theory to a production-ready system. Your immediate next steps should be: 1) Finalize the compliance rule set into a formal, machine-readable specification (e.g., using a domain-specific language). 2) Select a proving system like Groth16, Plonk, or Halo2 based on your trust assumptions, proof size, and prover time requirements. 3) Develop and audit the circuit logic that encodes these rules, as this is the most critical security component. A bug in the circuit invalidates all proofs. Consider using frameworks like circom or halo2-lib to accelerate development.
For ongoing operations, you must establish a robust proof management lifecycle. This includes secure proof generation (often off-chain), efficient on-chain verification via a verifier smart contract, and immutable proof storage with solutions like IPFS or Arweave. Monitoring is crucial: track metrics such as average proof generation time, gas cost of verification, and any failed verification attempts, which could indicate attempted fraud or system errors. Tools like Tenderly or OpenZeppelin Defender can help automate and monitor these on-chain interactions.
The regulatory and technological landscape for privacy-enhancing technologies is rapidly evolving. Stay informed about new zero-knowledge proof systems like Nova (for incremental computation) and advancements in recursive proofs. Monitor guidance from bodies like the FATF, which is increasingly examining how technologies like ZK-SNARKs interact with Travel Rule requirements. Engage with industry consortia such as the Zero Knowledge Proof Alliance (ZKPA) to contribute to and learn from shared best practices. The goal is to build a system that is not only compliant today but also adaptable to the standards of tomorrow.