I spent last weekend dissecting the Solvency protocol—a ZK-rollup bridge that raised $12M in seed funding last month. The pitch was clean: use zero-knowledge proofs to verify cross-chain state without intermediaries. But after auditing their EVM contract and reading their whitepaper twice, I found something troubling. Their proof verification contract includes a fallback oracle call. Not a fallback for invalid proofs—a fallback for every transaction if the proof generation takes longer than 10 seconds.
This is not a bug. It is a design compromise. The team calls it a “latency smoothing mechanism.” I call it a backdoor that nullifies the entire zero-knowledge security model. Math doesn’t care about your marketing timeline.
Let’s rewind. The promise of ZK-bridges is that you only need to trust the correctness of the proof system—no need to trust a validator set or an oracle. You verify the proof on-chain, and the state transition is cryptographically enforced. That is the entire value proposition. If you introduce an oracle fallback path, you reintroduce the very trust assumption you claimed to eliminate.
Context Solvency’s architecture is not unique. It follows the standard pattern: a relayer submits a batch of transactions to a L1 contract, along with a zk-SNARK proof attesting to the correct execution of the batch. The L1 contract verifies the proof using a pre-deployed verifier. If valid, the contract updates the L2 state root. The problem appears when the relayer fails to generate a proof within a predefined time window. The whitepaper states that the contract will accept a “signed commitment” from a set of pre-approved validators instead. That commitment is essentially a multisig oracle output.
Why would they do this? The answer is cost. Generating a ZK proof for a batch of hundreds of transactions can take minutes. In a bull market where users expect near-instant finality, the team chose speed over trustlessness.
Core Analysis I pulled the actual Solidity code from their GitHub (commit hash a7f3c9b). The relevant function is finalizeBatch(bytes memory _proof, bytes memory _publicInputs). A snippet that matters:
function finalizeBatch(bytes memory _proof, bytes memory _publicInputs) external {
require(batchExists[keccak256(_publicInputs)], "batch not submitted");
// Try to verify ZK proof
if (verifier.verify(_proof, _publicInputs)) {
applyStateTransition(_publicInputs);
} else {
// Fallback: check if validators have signed the same state root
require(isSignedByMajority(_publicInputs), "invalid proof or insufficient signatures");
applyStateTransition(_publicInputs);
}
}This is a textbook example of a “bypass route.” The else branch allows a state transition to occur even when the ZK proof fails. The contract does not differentiate between a malicious proof and an expired proof—it just checks for validator signatures. In practice, any relay that runs out of time will submit a proof that fails (because it’s incomplete), triggering the fallback. The validators are the same entities that run the L2 sequencer nodes. So essentially, the bridge security collapses to that of a multisig—exactly what ZK was supposed to replace.
But it gets worse. I traced the signing logic. The validator set is defined by a multi-sig wallet controlled by the foundation. The foundation multisig can add or remove validators with a 3/5 majority. So the fallback path is ultimately controlled by five people. And because the fallback is invoked silently (no explicit event is emitted when the fallback is used), users cannot easily distinguish between a ZK-verified transaction and a multisig-authorized one.
Contrarian Angle Many defenders of this design will argue that the fallback is only used in rare cases where proof generation fails due to a bug or high load. They claim that in practice, the ZK path will be used 99.9% of the time. I hear this argument often, and it is dangerously shallow.
First, “rare” is not a security parameter. Trustless systems are built to withstand adversarial conditions. An attacker could deliberately cause high load on the relayer by submitting many dummy transactions, forcing proof times to exceed the threshold. Alternatively, they could trigger a bug in the proof generation—many ZK circuits have edge cases that cause the prover to fail. Once the fallback is active, the attacker can then bribe or compromise the validator set. The attack surface is no longer just the ZK circuit; it is now the entire validator set plus the relayer plus the fallback contract.
Second, this design creates a subtle incentive problem. The foundation controls both the validators and the smart contract upgrade key. If the validator set is ever compromised, the foundation could simply remove malicious validators—but that requires the same 3/5 signature to perform the removal. And if the foundation itself is compromised, the fallback becomes a direct withdrawal mechanism.
Privacy is a protocol, not a policy. You cannot claim privacy (or trustlessness) as a goal and then rely on a policy of “we will not use the fallback.” The protocol must enforce the guarantee at the code level. This code does not.
Takeaway Solvency is not a malicious project. The team is honest and technically skilled. But they optimized for a bull market user expectation (instant finality) at the cost of their core value proposition. I have seen this pattern before: during the 2021 NFT boom, many mint contracts had fallback oracle price feeds for gas estimation—which were later exploited in the MEV wars. The fallback becomes the primary target.
I predict that within six months, someone will exploit the fallback path in a production ZK-bridge. The economics are too tempting: if you can force a proof timeout by congestion, you only need to control 3 of 5 validators to drain the bridge. And controlling three validators is cheaper than breaking a zk-SNARK.
My advice to developers: if your ZK system needs a fallback, you are building a fallback system, not a ZK system. Strip it out. Redesign for slower finality with proper cryptographic challenges. Do not let speed compromise your security model.
Based on my experience auditing Zcash’s shielded pool and participating in the 0x protocol deep dive, I have learned that true robustness comes from removing escape hatches, not adding them. The most secure protocols are the ones that force the adversary to break the math—and math doesn’t.
