Multi-model smart-contract security
AI Consensus Audit runs your contract past a panel of independent frontier models, then keeps only the findings they agree on. Fewer blind spots. Fewer false alarms. A clear verdict before you ever pay for a manual audit.
Any chain · any smart-contract language · pay per scan in crypto
The problem
The last few years proved AI can read a smart contract and flag real vulnerabilities. What it can't do reliably, on its own, is catch most of them — one model, however good, quietly misses the bugs that fall outside how it happens to reason. In production, a lone AI auditor tends to surface only a fraction of what a full review would find. That gap is exactly where funds get drained.
Consensus closes the gap. When several independent models each examine your code and only the issues they converge on are surfaced, you get higher coverage and far less noise than any one of them alone.
How it works
Paste a contract or link a repository — on any chain, in any language.
Several independent frontier models audit your code in parallel — each hunting vulnerabilities, logic flaws, and economic exploits from its own angle.
We reconcile every model's findings into one ranked report: a Consensus Score, the issues the panel agrees are real, an architecture map, and suggested fixes.
What every scan gives you
A single 0–100 confidence read on your contract's safety, derived from how strongly the model panel agrees.
Every issue, sorted by severity and by how many models flagged it, so you fix what matters first.
Not just what is wrong, but why it matters and what an attacker could do with it.
An auto-generated diagram of your contracts and how they call each other.
The properties your contract should always hold, surfaced as a starting point for testing.
Reconnect and every code change is re-reviewed, so a fix never quietly introduces a new hole.
Why consensus
Any one model has strengths and blind spots. Put several independent ones on the same code and two useful things happen: the vulnerabilities all of them see become high-confidence findings you can trust, and the ones only a single model imagines get filtered out as noise. You end up with broader coverage than any individual auditor and a shorter list of false positives to chase. It's the principle that makes a panel of reviewers better than one — applied by machines, in minutes, on every commit.
Every chain. Every language.
Most automated scanners are wired to a single virtual machine — miss that VM and you're out of luck. Ours isn't a tool bolted to one chain; it's a panel of general AI models that read code. Solidity, Rust, Move, Cairo, Vyper — EVM chains, Solana, Cosmos, Move-based chains, and whatever ships next — if it's a smart contract, the panel can review it.
Measured, not marketed
We measure ourselves against public, independent benchmarks for AI vulnerability detection rather than our own scoreboard. Every model on the panel is a current frontier model; the consensus layer is what lifts coverage above what any single one scores alone. AI Consensus Audit is built to complement human auditors, not replace them — it clears the ground so expert review lands where judgment is actually needed.
Pricing & payment · crypto only
No subscriptions, no seats, no cards. You pay only for the code you actually audit — priced per line scanned and settled in crypto. Buy credits from your own wallet on the chain of your choice; heavy users get volume rates.
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For developers
Call the same engine from your CI, your launchpad, your DEX, or your bot — on any chain. Send a contract, get back ranked findings and a Consensus Score as structured data. Pay per call in credits, no monthly minimum. Ship code that's been through the panel before it ever hits mainnet.
FAQ
No — it's the step before one. It catches the obvious and much of the subtle so human auditors spend their time on the hard, contextual logic, and so you don't pay audit rates to find a missing access-control check.
Any of them. Because the panel is made of general AI models — not a tool wired to one virtual machine — it reads Solidity, Rust, Move, Cairo, Vyper and more, across any chain.
Several independent AI models review your code separately; we surface the findings they agree on and rank everything by how strongly the panel converges.
One model has one set of blind spots. A panel cross-checks each other, which raises coverage and cuts false positives.
Run your contract past the panel before it goes live.
Audit your contract