Why Your zk-Circuit Is Leaking Data

A circuit's constraint count and structure leak information about the private inputs. Adversaries can fingerprint transaction types or user behavior by analyzing proof generation time and gas costs.

• Gas cost analysis can reveal if a transaction is a simple transfer vs. a complex swap.
• Proving time variance between different private inputs creates a timing side-channel.
• Mitigation requires uniform-cost circuits, as pioneered by Aztec Network for private DeFi.

Circuit logic that inadvertently makes private data checkable against public state. A malicious verifier can brute-force private values by testing them against the public input.

• Example: A circuit that hashes a private key to a public address, but exposes the hash preimage logic.
• This breaks soundness, allowing fake proofs for invalid states.
• The fix is exhaustive formal verification of all public/private input boundaries, a core tenet of PSE (Privacy & Scaling Explorations) zk-EVM work.

Leakage occurs at ceremony, not runtime. A compromised or manipulated trusted setup (e.g., Perpetual Powers of Tau) creates a toxic waste backdoor, allowing unlimited fake proofs.

• This is a systemic risk for zk-SNARKs like Groth16, used by Zcash and early Loopring.
• zk-STARKs and Halo2 (without trusted setup) are architecturally immune.
• The industry shift is toward transparent setups, but legacy circuits remain a multi-billion dollar attack surface.

Non-standard finite field arithmetic in circuits can leak bits of private data. An attacker observing whether a computation overflows/underflows gains information.

• This is a classic fault injection attack vector, similar to early Ethereum smart contract vulnerabilities.
• Circuits must use strict, bounded arithmetic with no undefined behavior.
• Tools like Zokrates and Circom have added overflow checks, but legacy circuits remain vulnerable.

Prover implementation details—like the order of operations or library dependencies—create a unique signature in the proof. This can deanonymize users across sessions.

• Similar to browser fingerprinting; a prover using arkworks vs. bellman may generate subtly different proofs.
• Breaks the "unlinkability" promise of privacy chains like Mina or Aleo.
• Solution requires standardization of proof systems and deterministic, canonical implementations.

When aggregating proofs (e.g., in zkRollups), the metadata of the composition tree—like which leaf proofs are included—can leak transaction graph data.

• This threatens the privacy of validity-proof-based L2s like zkSync Era and Scroll.
• An observer can infer activity spikes, user clustering, and application usage.
• Mitigation requires privacy-preserving aggregation, an active research area in succinct cryptography.

A circuit's constraints define what is provable, not what is hidden. Poorly designed constraints leak data via public inputs, output variables, and selective reveal.\n- Leak: Proving a balance is >0 reveals it's not zero.\n- Fix: Use range proofs for all private inputs.\n- Audit: Use tools like ZKP-Ranger or Ecne to analyze constraint leakage.

Prover runtime and memory usage are public metadata. Variations can leak information about private witness values, a classic timing/power side-channel attack.\n- Leak: A branching operation's execution time reveals the taken path.\n- Fix: Implement constant-time algorithms for all primitives.\n- Benchmark: Profile prover execution with randomized inputs to detect variance.

Using a vulnerable circuit (e.g., from a library like circomlib) in a recursive stack, like a zkRollup, propagates the flaw. The final proof is valid but carries the data leak.\n- Leak: A flawed Poseidon hash in a Merkle tree leaks leaf pre-images.\n- Fix: Audit and pin dependency versions; use formally verified libraries.\n- Reference: Learn from Aztec's public circuit audits and Scroll's security practices.

A malicious or compromised Structured Reference String (SRS) allows forgery of proofs for any statement, completely breaking the system. This isn't a data leak—it's a total break.\n- Risk: A single participant's toxicity can compromise the entire ceremony.\n- Solution: Use Perpetual Powers of Tau ceremonies or transition to transparent (STARKs) or universal (PLONK) setups where possible.\n- Monitor: Implement real-time proof validity checks on-chain.

In decentralized prover networks like Espresso or RiscZero, the order of proof generation and submission is public. Observing this sequence can leak intent.\n- Leak: Seeing which transaction proof is generated first reveals priority.\n- Mitigation: Use commit-reveal schemes or encrypted mempools for proof submission.\n- Design: Integrate with SUAVE-like architectures for private ordering.

Manual auditing and testing are insufficient. You must formally verify that your circuit's logic matches its specification using tools like Leo, Zokrates, or Halo2's proving system.\n- Process: Write specifications in a language like ACSL, then prove equivalence.\n- Outcome: Guarantees the circuit computes only what you intend, preventing unintended data outputs.\n- Cost: Adds 20-50% dev time but is the only way to achieve high assurance.