#1 Leading

    Agentic Smart
    Contract Auditing

    One exploit can erase everything you built. Cecuro keeps finding the criticals that top auditors miss.

    #1 on EVMBench — OpenAI's exploit benchmark

    What top auditors miss, Cecuro finds.

    HackenHigh ×2
    CecuroJan 2026
    Zellic V12Critical
    CecuroJan 2026
    NethermindHigh ×6
    CecuroJan 2026
    BlockSecCritical
    CecuroSept 2025
    QuantstampHigh
    CecuroAug 2025
    OtterSecHigh
    CecuroMay 2025

    Your protocol could be the next row.

    More cases below
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    Top-tier audits for every builder

    Every project deserves the same protection as billion-dollar protocols.
    The same rigor that protects major DeFi, now within reach.

    Depth You Can Trust

    Our AI agents typically run for 8+ hours per audit, systematically exploring attack vectors and edge cases that human auditors, constrained by time and cost, routinely miss.

    No Tradeoff Between Depth and Speed

    Traditional audits take weeks because thorough human analysis is slow. Our agents achieve the same depth in hours, with no queues and no compromises.

    Security for Every Builder

    Top-tier audit quality that was previously reserved for protocols with six-figure security budgets, now accessible to every Web3 project.

    Traditional vs Cecuro

    Traditional
    Cecuro
    Speed
    Weeks
    Hours
    Cost
    $15K-$300K+
    up to 95% less
    Quality
    High
    High+
    10x Faster90% CheaperTop-tier Quality

    What the world's best auditors miss, Cecuro finds.

    These codebases passed top-tier human audits.Cecuro still found critical bugs. Don't let the next one be you.

    Missed finding
    • Medium

      Medium finding pending public disclosure

      Cecuro identified a Medium-severity vulnerability in a Solidity merkle-tree verification path that was reviewed and missed by SRLabs's May 2026 audit. Full technical writeup and the named project will be published once the issue is fixed and disclosure is appropriate.

    Missed finding
    • Low

      Low-severity finding missed across the V3 competition and review

      Cecuro identified a Low-severity vulnerability in Alchemix V3 that was reviewed and missed by both the Immunefi competition (298 researchers, 952 reports, $100k pool) and a subsequent Y-Audit review (commit 45e4b08).

    How Y-Audit touched this code

    Confirmed at commit 45e4b08.

    2 missed findings
    • High

      First High finding pending public disclosure

      Cecuro identified a High-severity vulnerability reviewed and missed by Hacken's January 2026 audit. Full technical writeup and the named project will be published once the issue is fixed and disclosure is appropriate.

    • High

      Second High finding pending public disclosure

      Cecuro identified a second High-severity vulnerability reviewed and missed by Hacken's January 2026 audit. Full technical writeup and the named project will be published once the issue is fixed and disclosure is appropriate.

    Missed finding
    • Critical

      Cross-function reentrancy in ServiceManager.create() drains pooled ERC20 deposits via _safeMint callback

      ServiceManager.create() registers a new service and mints its ownership NFT via ERC721 _safeMint, which hands control to the recipient's onERC721Received hook before the service's accounting is finalised. From inside that callback an attacker can re-enter the registry's deposit path and act against pooled ERC20 deposits while the contract's state is still mid-update — a classic cross-function reentrancy across the create/deposit boundary. Reviewed and missed by the Zellic V12 AI auditor, which inspected ServiceManager.create() and StakingBase but did not flag the _safeMint reentrancy window.

    How Zellic V12 touched this code

    Reviewed ServiceManager.create() and StakingBase, but did not flag the _safeMint reentrancy window.

    6 missed findings
    • High

      Cross-contract reentrancy in liquidation drains the collateral vault via live phantom shares

      During liquidation the account is temporarily inflated with "phantom" shares used only for solvency math, and the two collateral tokens are settled one after the other. An external callback fires mid-sequence while the phantom shares are still live, letting a malicious liquidator transfer them out and redeem them for real assets — draining the CollateralTracker and socializing the loss to all depositors. Reviewed and missed by Nethermind's NM-0701 audit; independently confirmed as High (H-02) by the parallel Code4rena "Panoptic: Next Core" competition and since mitigated.

    • Medium

      Oracle rebase mask clears 8 bits of spot EMA, corrupting the solvency oracle after large moves

      The bitmask used when "rebasing" the packed price-oracle word is sized wrong and erases more bits than intended, wiping part of the stored EMA price values it was supposed to preserve. This corrupts the price feed the solvency checks depend on after large market moves. Missed by Nethermind's NM-0701; confirmed as Medium (M-04) by Code4rena and since mitigated.

    • Medium

      Liquidation bonus underflow leaves insolvent accounts unliquidatable or overpays liquidators

      The liquidation-bonus formula subtracts collateral balance from the requirement without guarding against the balance being the larger of the two. The V2 solvency rewrite made that state reachable (an account insolvent in one token but flush in the other), so the unsigned subtraction misbehaves — blocking liquidations entirely, or producing a wildly inflated bonus. Missed by Nethermind's NM-0701; confirmed as Medium (M-01) by Code4rena and since mitigated.

    • Medium

      Per-leg zero-width credits overwritten instead of accumulated, mis-valuing multi-leg positions

      When computing a position's required collateral, the credit for zero-width legs is overwritten on each loop iteration instead of summed. Positions with multiple such legs are mis-valued, which can trigger erroneous liquidations. Missed by Nethermind's NM-0701; confirmed as Medium (M-02) by Code4rena and since mitigated.

    • Medium

      Liquidation / force-exercise DoS via manipulable spot-vs-TWAP stale-oracle check

      A short-lived spot-price manipulation can trip the StaleOracle guard inside dispatchFrom, blocking time-critical liquidations, force exercises, and premium settlements for as long as the attacker holds the price off-band. Missed by Nethermind's NM-0701; confirmed as Medium (M-06) by Code4rena and since mitigated.

    • Medium

      Internal oracle is cheaply manipulable via slot0 tick across 64-second epochs

      The internal oracle ingests an easily-influenced spot tick, and once updated in a 64-second epoch it can't be corrected until the next one. An attacker can front-run legitimate updates and nudge the oracle across epochs (e.g. with flash loans) to skew the price used in risk calculations. Missed by Nethermind's NM-0701; confirmed as Medium (M-11) by Code4rena and since mitigated.

    How Nethermind touched this code

    Nethermind's NM-0701 reviewed the panoptic-v2-core liquidation, oracle, and collateral-settlement paths — the same shared core logic — but did not flag any of these six issues. Each was independently confirmed by the parallel Code4rena "Panoptic: Next Core" competition (later commit 29980a74) and has since been mitigated by Panoptic.

    Missed finding
    • High

      High finding pending public disclosure

      Cecuro identified a High-severity vulnerability that was reviewed and missed by four independent audits — Cantina Code, GetRecon, 0xMacro, and Octane Security. Full technical writeup and the named project will be published once the issue is fixed and disclosure is appropriate.

    Missed finding
    • High

      High finding pending public disclosure

      Cecuro identified a High-severity vulnerability that was reviewed and missed by four independent audits — Cantina Code, GetRecon, 0xMacro, and Octane Security. Full technical writeup and the named project will be published once the issue is fixed and disclosure is appropriate.

    INSIDE THE ENGINE

    Rigorous by design. Not another scanner.

    Most tools surface-scan your code in seconds. A Cecuro audit coordinates ~180 specialized agents for an average of 8 hours, investigates every contract from adversarial angles, and reproduces each finding with a runnable proof-of-concept before it reaches your report.

    How It Works

    Getting started is simple. Connect your code and receive a comprehensive smart contract audit in just a few hours.

    Step 1

    Connect GitHub

    Select your repository, branch, and commit, then submit for auditing.

    60 seconds to start
    Step 2

    Deep Agent Analysis

    Our AI agents spend ~8 hours systematically probing attack vectors, tracing execution paths, and testing exploit scenarios across your entire codebase.

    ~8 hours of deep analysis
    Step 3

    Issue Detection

    Identifies vulnerabilities with detailed explanations and suggested fixes. Resubmit your fixes to verify remediation.

    Actionable insights
    Step 4

    Final Audit Report

    Receive your comprehensive audit report with professional documentation ready for stakeholders.

    Professional-grade

    #1 On Exploit Benchmarks.
    Catching What Human Auditors Miss.

    Proven across two independent benchmarks. Not just better than AI models. Better than protocols with up to 11 audits from top firms.

    2x

    the detection rate of the best frontier AI model

    13x

    more value protected vs the same model without our architecture

    11

    audits from top firms missed exploits that Cecuro detected

    EVMBench Leaderboard

    CecuroCecuro
    87.17%
    Azimuth(TestMachine)Agent
    75.2%
    AuditAgent(Nethermind)Agent
    67.0%
    KaiAgent
    64.2%
    GuardixAgent
    59.8%
    Anthropic
    Claude Opus 4.6
    45.6%
    OpenAI
    GPT-5.3-Codex
    39.2%
    OpenAI
    GPT-5.2
    39.2%
    Anthropic
    Claude Opus 4.5
    36.1%
    Google
    Gemini 3 Pro
    20.8%
    OpenAI
    o3
    10.6%

    Detection rate (%) on the EVMBench dataset (117 vulnerabilities from Code4rena competitions). Best variant shown per model family.

    Real-World Exploit Detection

    Cecuro Security Agent

    Purpose-built AI security system

    Value Protected$96.8M

    Frontier Model (Baseline)

    Same model, no security specialization

    Value Protected$7.5M

    Tested on 90 real exploits that caused $228M in losses. Both systems ran the same frontier model. The difference is entirely Cecuro's purpose-built security architecture.

    About These Benchmarks

    EVMBench results from the industry benchmark by OpenAI, Paradigm, and OtterSec. Real-world exploit data sourced from Anthropic's SCONE-bench and DeFiHackLabs. Both confirm that specialized architecture, not model size, is the key differentiator in AI smart contract security.

    Featured inCoinDesk

    Who needs an AI audit?

    Audited doesn't mean safe.

    Cecuro consistently finds what top firms miss.

    $0M+

    drained from DeFi protocols in 2026 alone

    Hack Radar →
    Pre-launch

    Audited, about to ship?

    Top auditors miss things. Cecuro catches them.

    Make Cecuro your final set of eyes before deployment.

    Post-launch

    Already live, still uncertain?

    You should be. Bugs lurk for months.

    Re-audit shipped code before adversaries find them.

    Pre-audit

    First audit? Tight budget? Start with the leading AI auditor, at a fraction of the cost of a traditional human audit.

    Can AI really outperform human auditors?

    We tested on 90 contracts that were exploited in the real world.Cecuro detected 92% of the vulnerabilities humans had already missed.

    90 contracts exploited in the real world for $228M — despite existing security reviews.

    Cecuro detected
    92%

    of the vulnerabilities that human auditors had already reviewed and missed

    Sources: Anthropic SCONE-bench · DeFiHackLabs · Security Boulevard

    AI Exploit Capabilities
    Doubling Every 1.3 Months

    The only viable defense is AI-powered security that evolves at the same pace.

    1.3 months

    AI exploit capability doubling time

    Source: Anthropic
    $1.22

    Cost to attack a single contract

    Source: Anthropic
    72%

    Exploits executed end-to-end by AI agents

    Source: OpenAI / Paradigm

    Protect your protocol with the leading agentic auditor.

    "Cecuro caught real issues that were independently confirmed by our human senior auditors. The findings were well-reasoned, clearly explained, and actionable. For an AI-powered audit, the signal-to-noise ratio was impressive. We came away with genuine improvements to our codebase and will definitely be using Cecuro on future codebases."

    Utkir

    CTO at Zyfai

    "We ran Cecuro alongside our existing audit process and it flagged a critical finding that separate manual reviews had missed. Saved us from what could have been a serious incident."

    Founder

    DeFi

    Ready to Secure Your Protocol?

    Token.sol
    pragma solidity ^0.8.0;
    contract SafeToken {
    mapping(address => uint...
    function transfer(addre...
    require(balances[msg....
    balances[msg.sender] ...
    Staking.sol
    contract StakingPool {
    uint256 public totalSta...
    mapping(address => uint...
    function stake(uint256 ...
    stakes[msg.sender] +=...
    totalStaked += amount...
    DEX.sol
    contract DEXPool {
    uint256 reserveA, reser...
    function swap(uint256 a...
    uint256 amountOut = g...
    tokenA.transferFrom(m...
    tokenB.transfer(msg.s...
    Governance.sol
    contract Governance {
    struct Proposal {
    uint256 votes;
    bool executed;
    }
    function vote(uint256 p...
    Vault.sol
    contract Vault {
    address owner;
    uint256 balance;
    function withdraw(uint2...
    require(msg.sender ==...
    payable(owner).transf...
    Bridge.sol
    contract CrossChainBridge...
    mapping(bytes32 => bool...
    function bridgeTokens(b...
    require(!processedHas...
    processedHashes[hash]...
    mintTokens(msg.sender...
    Smart Contract Analyzed
    Vulnerability Detected
    Audit Report Generated
    Analyzing Token.sol...

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