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Stoa: A Monad-based AI Smart Contract Audit and Dispute Precheck System

A smart contract audit platform integrating six LLM families, achieving a 95% recall rate for invalid disputes on Polymarket, supporting the ERC-8004 standard, and operating with zero daily inference costs.

智能合约审计AI安全Monad区块链PolymarketERC-8004预测市场DeFi安全多模型集成
Published 2026-05-16 09:41Recent activity 2026-05-16 09:49Estimated read 7 min
Stoa: A Monad-based AI Smart Contract Audit and Dispute Precheck System
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Section 01

Stoa Project Overview: AI-Powered Smart Contract Audit and Dispute Precheck Platform

Stoa is an AI smart contract audit and dispute precheck system built on the Monad blockchain. It integrates six LLM families for multi-model integration, supports the ERC-8004 standard to ensure on-chain verifiability, and operates with zero daily inference costs. Key highlights include a 95% recall rate for invalid disputes on Polymarket. Positioned as a dual-function platform: an AI smart contract audit firm and a dispute precheck classifier, it aims to solve the problems of high cost and long cycle in traditional manual audits, meeting the needs of the DeFi ecosystem and prediction markets.

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Section 02

Project Background and Positioning

Smart contract audit is the core of blockchain security, but traditional manual audits are costly and time-consuming, making it difficult to adapt to the rapidly developing DeFi ecosystem; dispute resolution in prediction markets (such as Polymarket) requires an efficient and accurate mechanism. Stoa was born in this context, positioned as a dual-function platform: both an AI smart contract audit firm and a dispute precheck classifier. It runs on the Monad blockchain and provides verifiable audit services using multi-model integration.

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Section 03

Analysis of Core Technical Architecture

Stoa's core technical architecture includes:

  1. Integration of Six LLM Families: Reduces single-model bias, improves vulnerability coverage, and enhances conclusion interpretability;
  2. Native ERC-8004 Support: Follows the Ethereum Improvement Proposal for AI verifiability, ensuring audit reports are on-chain verifiable and can be referenced by other contracts;
  3. Zero Daily Inference Cost Architecture: Achieves zero daily inference fees through local deployment of open-source models, model distillation/quantization, and accessing resources from decentralized computing power markets, ensuring sustainable operation.
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Section 04

Introduction to Core Function Modules

Smart Contract Audit

  • Static code analysis to identify common Solidity vulnerabilities (reentrancy, integer overflow, etc.);
  • Semantic understanding of contract business logic and potential risks;
  • Generate multi-dimensional reports with risk levels and repair suggestions;
  • Audit conclusions comply with the ERC-8004 standard and are on-chain verifiable.

Dispute Precheck Classifier

  • Evaluate the validity of disputes in prediction markets like Polymarket;
  • 95% recall rate for invalid disputes, helping users avoid unnecessary submissions;
  • Optimize the resource burden of prediction market resolution systems.
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Section 05

Performance Metrics and Verification Results

Stoa's public performance metrics:

  • 95% INVALID-recall: Accurately identifies 95% of invalid disputes in Polymarket's historical dispute data;
  • ERC-8004 Compliance: Audit outputs meet AI verifiability standards;
  • Zero Daily Inference Cost: Operates without ongoing API call fees. These metrics balance practicality and economy, supporting efficient security analysis and low-cost operation.
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Section 06

Application Scenarios and Value Proposition

Smart Contract Developers

  • Pre-deployment security scanning, continuous monitoring of deployed contracts, generation of verifiable audit reports;

Prediction Market Participants

  • Dispute pre-evaluation, saving costs on invalid disputes, AI-assisted decision-making;

Audit Industry

  • Human-machine collaboration to improve efficiency, shorten cycles and reduce costs, promote the development of ERC-8004 standardization.
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Section 07

Technical Challenges and Industry Outlook

Technical Challenges

  • Model Interpretability: Multi-model integration increases complexity, requiring clear explanation of conclusion derivation;
  • Zero-Day Vulnerability Coverage: AI relies on historical data, so it needs to combine traditional security research to address new attack vectors;
  • On-Chain Verification Overhead: ERC-8004 compliance may incur Gas costs, requiring a balance between verifiability and economy.

Industry Outlook

Stoa represents the trend of AI automated audits supplementing manual audits. Its multi-model architecture and ERC-8004 practice provide references for the industry. In the future, more projects may adopt verifiable AI architectures to promote smart contract security upgrades, which is worthy of attention from blockchain security, AI application, and Monad ecosystem developers.