Aztec zk-SNARKs for Private Attestations vs Public Attestations

Aztec's zk-SNARK-based attestations excel at providing cryptographically guaranteed privacy by default. Transactions and the data within them are encrypted and validated via succinct zero-knowledge proofs, shielding user identity and sensitive data from public view. This is critical for use cases like private credit scoring or confidential employee verification, where leaking attestation details could have severe consequences. The trade-off is complexity and cost; generating a zk-SNARK proof is computationally intensive, currently costing more gas and requiring specialized tooling like the Aztec Noir language and Aztec Sandbox for development.

Public attestation protocols like Ethereum Attestation Service (EAS) or Verax take a different approach by broadcasting attestation data on-chain. This strategy maximizes transparency, auditability, and composability, allowing any dApp to freely read and build upon the attestation graph. For example, a public reputation score from EAS can be seamlessly integrated by a Gitcoin Grants round or a Safe{Wallet} governance module. The resulting trade-off is a complete lack of data privacy; all attestations are visible, which can lead to unintended correlation and profiling of user identities.

The key trade-off is between cryptographic privacy and open composability. Aztec's model, leveraging its zk-rollup architecture, is superior for applications handling sensitive personal data (KYC, medical records, private voting) where privacy is non-negotiable. Public attestation frameworks are the definitive choice for building open reputation systems, sybil-resistant airdrops, or transparent credentialing where network effects and permissionless innovation are the primary goals. Your architectural choice fundamentally dictates who can see your data and who can build on top of it.

Aztec's zk-SNARKs excel at providing on-chain privacy and programmability for attestations because they use zero-knowledge proofs to shield data while maintaining verifiable correctness. For example, protocols like zk.money have demonstrated the ability to process private transactions with finality in under 30 seconds, proving the viability for sensitive financial attestations. This approach is ideal for use cases requiring confidentiality, such as private voting, salary payments, or undisclosed credit scoring, where data must be both immutable and hidden from public view.

Public attestations on L1/L2s like Ethereum, Arbitrum, or Base take a different approach by prioritizing maximum transparency, composability, and lower development overhead. This results in a trade-off: while attestation data (e.g., from EAS - Ethereum Attestation Service) is openly verifiable and can be seamlessly integrated by any downstream dApp, it sacrifices user and business confidentiality. The ecosystem benefits from high liquidity and established tooling, with platforms like Optimism's AttestationStation facilitating millions of low-cost, public data points.

The key architectural trade-off is between data opacity and ecosystem reach. Aztec's current mainnet throughput is limited compared to public rollups, often cited in the 10-20 TPS range for simple transactions, while a public attestation on Optimism can be submitted for a fraction of a cent. Furthermore, building on Aztec requires expertise in Noir and zero-knowledge circuit design, a steeper barrier than using standard Solidity and public SDKs.

Consider Aztec zk-SNARKs if your protocol's core value depends on privacy-by-default—such as for private governance, confidential enterprise workflows, or discreet identity verification. The cost and complexity are justified when leaking attestation data would break the product or violate regulations (e.g., GDPR).

Choose public attestations on a high-throughput L2 if your priority is maximum adoption, low cost, and open composability. This is the superior path for reputation systems, transparent credentials, content provenance, and any application where the network effect and auditability of public data provide more value than confidentiality.