Zero-knowledge proofs have emerged as one of the most impactful cryptographic primitives available today. Their ability to compress complex computations into succinct, verifiable claims without disclosing sensitive input has opened the door to new layers of blockchain infrastructure. While the mathematics behind ZKPs is sound and highly optimized, real-world implementations often introduce vulnerabilities at the integration points and within the implementations themselves. These concerns may appear between prover and verifier, between circuits and contracts, or between protocol logic and user interaction. They result from implementation decisions, mismodeled assumptions, and overlooked conditions in complex execution flows.
Cantina’s work focuses on these boundaries. Our reviews go beyond validating the cryptographic soundness of a proof. We evaluate how proofs are constructed, interpreted, and enforced across systems. Zero-knowledge proofs begin the security story, but the way they are consumed and applied determines how that story ends.
How Zero-Knowledge Proofs Work in Practice
A zero-knowledge proof is a protocol that allows a prover to convince a verifier that a particular statement is true and that they know a certain solution or secret for the statement, without revealing any information beyond the validity of that statement. For example, the prover can prove “I know the preimage of the hash xxxx.” The existence of the pre-image of the hash is trivial, but the knowledge of such a solution is not.
In blockchain applications, these statements often represent the execution of transactions, state transitions, identity attestations, or cross-chain validations.
Proving systems like PLONK, Halo2, and Groth16 encode these statements into arithmetic circuits. The original PLONK and Halo2 provide circuits with arithmetic gates and wire constraints. PLONK has since evolved, introducing two powerful primitives: custom gates, which model higher-degree relations for efficient hash implementation, and lookups, which support complex operations such as traditional hashes. Today, most Plonkish circuits rely on both.
Producing a valid proof confirms that the circuit’s logic was satisfied under a specific witness. It does not provide any assurance that the system’s full behavior is safe unless the protocol context, contract logic, and input structures are rigorously modeled and enforced.
Expanding the ZKP Landscape: What Systems Are We Securing
Zero-knowledge proofs now support a broad range of applications across blockchain infrastructure and protocol design. At Cantina, our reviews cover systems such as:
- zkRollups that compress Layer 2 execution into verifiable Layer 1 proofs.
- zkBridges that authorize cross-chain asset transfers through succinct validation.
- zkVMs that encapsulate smart contract execution within provable computation circuits.
- ZK identity protocols that manage selective disclosure, nullifier logic, and private attestations.
- ZK machine learning systems where inference outputs are encoded and verified within circuits.
- Privacy-preserving voting protocols that rely on nullifiers, encrypted inputs, and eligibility proofs.
- Light clients that verify block headers and state updates from external chains using ZKPs.
- Web2 social media platforms implementing age verification through ZKPs.
- Gaming applications using ZKPs for fair matchmaking and anti-cheat systems.
- Traditional enterprise systems leveraging ZKPs for secure data sharing.
Each of these systems introduces unique constraints and input domains. They are built on shared proof principles but implemented in distinct ways. Security assurance in this space requires more than proof correctness. It requires verification of system behavior in every state that proof validation enables.
Key Security Considerations for ZKP Systems
Our reviews of production systems have identified several important areas where ZKP implementations can be strengthened. These considerations focus on constraint scope, protocol enforcement, and asynchronous interaction between components.
Ensuring Complete Contract Logic Validation
When implementing withdrawal proofs, it’s crucial to validate all relevant parameters including destination address, token standard, and execution context. This ensures that the protocol processes only intended actions and maintains correct state transitions.
Maintaining State Consistency
When storing claim flags, batch status, or nullifier registries on-chain, implement robust state management that enforces strict update ordering and frequency. This helps prevent claim repetition and maintains protocol pause effectiveness.
Implementing Robust Merkle Tree Validation
For voting systems, bridge claim paths, and synchronizers using Merkle roots, implement comprehensive checks for sibling structure, index bounds, and tree updates. This ensures that inclusion proofs maintain their integrity and prevent manipulation.
Handling Dynamic Token Behavior
Account for dynamic token behaviors such as fee-on-transfer, rebasing, or non-standard transferFrom patterns. Implementing post-transfer reconciliation helps maintain accurate accounting and ensures users receive correct amounts.
Securing Identity and ML Input Validation
In ZK identity and machine learning systems, implement strict bounds on inputs such as model weights, signature lengths, and nullifier freshness. This helps maintain system integrity by preventing malformed inputs from affecting intended logic.
Cantina’s Approach: Full-Scope Reviews for ZK Systems
Cantina’s ZKP reviews operate across multiple layers of protocol architecture. We assess not only the internal constraints of a circuit, but also how those constraints connect to external systems, verifier design, off-chain data, and downstream contract logic.
Our process includes simulation of prover behavior, manipulation of witness construction, targeted constraint evaluation, and modeling of edge-state transitions. We apply this methodology across diverse protocol categories to detect where unsafe outcomes can occur under conditions that appear valid.What We’ve Seen in Real Reviews
In our work, implementation misalignments have appeared across multiple types of protocols. Some of the more common examples include:
Claim Logic That Fails Under Extended Use
In a bridge system that Cantina researchers reviewed, claim flags stored as bitmaps became misaligned after long idle periods and batch rollover. The design permitted index reuse without enforcing sequential uniqueness, allowing for duplicate claims to succeed.
Emergency Controls That Remained Partially Active
A cross-chain protocol introduced a pause function intended to freeze system activity. However, one path through batch state consolidation remained callable, which allowed activity to continue even when the rest of the protocol was halted.
Token Transfers That Skew Accounting Models
A system integrated a token with fee-on-transfer mechanics but failed to model post-transfer balances. This introduced discrepancies between what the proof authorized and what the recipient ultimately received, affecting batch settlement logic.
Nullifier Tracking That Allowed Replay
An identity system using nullifiers assumed freshness without enforcing scope across voting epochs. This made it possible to reuse the same proof for multiple interactions, bypassing participation limits.
Misunderstood Primitives Leading to Signature Forgery
In a multi-signature paper reviewed, a misunderstood primitive allowed a participant to forge the signature of an entire committee.
Why System Integration Matters as Much as Circuit Design
ZKP circuits define correctness over a well-scoped input and constraint space. However, once deployed, those circuits become one component in a broader system. That system includes mutable contract state, asynchronous proofs, dynamic tokens, and live user interaction. Each of these introduces behavior that exists outside the cryptographic guarantees of the proving system.
Cantina’s methodology focuses on this full system model. Our reviews target how constraints are consumed, how proof outputs interact with contracts, and how unexpected edge states create failure surfaces. We treat proof validation as the entry point for deeper enforcement logic.
Securing Zero Knowledge Infrastructure with Cantina
Cantina provides structured, system-aware reviews for protocols using ZKPs across infrastructure, applications, and cryptographic systems. Our work spans circuit analysis, verifier behavior, zkVM execution, proof batching mechanisms, identity protocols, and machine learning integrations.
We align deep technical scope with real-world execution. Proof correctness must translate into secure and enforceable behavior across the entire system lifecycle. This includes circuit logic, contract enforcement, prover assumptions, and state integrity.
If you are building with zero knowledge and your protocol demands security that holds under pressure, we are ready to review it. We are available 24/7 to scope a high signal review or design a targeted competition. Contact us today.