{"type": "project", "title": "Contract Guardian: Empowering Smart Contracts with AI Auditing", "logoImg": "bafkreicjrflt45khdeqi64dfnrsmbbpyauaayvir4hps37of44lia6g6ge", "website": "https://contractguard.ecofuse.ai", "bannerImg": "bafkreigh4e463zuamx5fpnce747mghwlmaabhagghq2ej4wlkzf6x6sa6a", "createdAt": 1699428029048, "userGithub": "ecofuseai", "credentials": {"twitter": {"type": ["VerifiableCredential"], "proof": {"jws": "eyJhbGciOiJFZERTQSIsImNyaXQiOlsiYjY0Il0sImI2NCI6ZmFsc2V9..bSvQwst_uBJ5bZpW-O37S0WvPoMzKNXxkjW-ul7q8_47-LUUm1n8zWvDFycSXkN5csPJlxt-ii2JW-ZsobUrCw", "type": "Ed25519Signature2018", "created": "2023-11-08T07:10:14.787Z", "proofPurpose": "assertionMethod", "verificationMethod": "did:key:z6MkghvGHLobLEdj1bgRLhS4LPGJAvbMA1tn2zcRyqmYU5LC#z6MkghvGHLobLEdj1bgRLhS4LPGJAvbMA1tn2zcRyqmYU5LC"}, "issuer": "did:key:z6MkghvGHLobLEdj1bgRLhS4LPGJAvbMA1tn2zcRyqmYU5LC", "@context": ["https://www.w3.org/2018/credentials/v1"], "issuanceDate": "2023-11-08T07:10:14.787Z", "expirationDate": "2024-02-06T07:10:14.787Z", "credentialSubject": {"id": "did:pkh:eip155:1:0xB1b1dEbB6C65258d05842a1CFc9CCb5D8B868286", "hash": "v0.0.0:olqq+ZsIttS/LsW2j0mCIJ1R4TTtwOofsI7Qat9ZYMQ=", "@context": [{"hash": "https://schema.org/Text", "provider": "https://schema.org/Text"}], "provider": "ClearTextTwitter#EcoFuseAI"}}}, "description": "Contract Guardian, developed by the EcofuseAI team, is an AI-powered web application designed to provide supplementary audit analysis for EVM-based Solidity smart contracts. This tool is meticulously crafted for accessibility and simplicity, aimed at assisting a wide range of users in their contract analysis needs.\n\nContract Guardian empowers users and organizations by offering a valuable contract analysis tool for smart contract code destined for deployment on the Optimism/EVM chain. It facilitates audit analysis, allowing users to proactively identify basic compilation errors, potential exploits, and vulnerabilities. These insights can complement the work of third-party auditing services, enhancing the overall security of smart contracts.\n\nThe tool operates through a straightforward process. Users input their smart contract code into a text input window, and Contract Guardian generates a preliminary audit analysis as output. You can explore this process in detail through an informative video explanation: [Watch the Video](https://youtu.be/3uowBcjqDw4).\n\nHere are the relevant links for the Contract Guardian project:\n\n- **Try Demo**: [Contract Guardian Demo](https://contractguard.ecofuse.ai/)\n- **Website**: [EcofuseAI](https://www.ecofuse.ai/)\n- **Twitter**: [EcofuseAI Twitter](https://twitter.com/ecofuseai)\n- **Live Demo Test Video**: [Live Demo Test Video](https://youtu.be/hscuMvDK2cM)\n- **In-depth Video Explanation**: [Watch the Video](https://youtu.be/3uowBcjqDw4)\n\nThe success of our project in meeting the requirements lies in the innovative approach we have taken to address common issues associated with AI-based auditing, namely accuracy and context.\n\n1. **Multi-Model Unit (MMU)**: Contract Guardian employs multiple LLM models in a communication bridge. These models verify, critique, and complement each other's findings, exposing inaccuracies and offering a broader perspective on vulnerabilities and fixes. This approach significantly enhances accuracy and context.\n\n2. **Incorporation of Third-Party Static Analyzers**: To combine the strengths of AI and non-AI tools, we integrate third-party static analyzers. These open-source tools check for compilation errors and basic vulnerabilities, providing valuable insights to the MMU. This dual approach ensures higher accuracy and greater context for the AI models.\n\n3. **Additional Training Data**: Recognizing that LLM models were not initially designed for auditing code, we enrich their knowledge base with specialized training data. Langchain Vectorstores, built on extensive sources including audit reports, books, articles on vulnerabilities, and news about recent exploits, provide essential context, enabling the models to stay updated with the latest trends in vulnerabilities and exploits.\n\nWe acknowledge that our current demonstration has limitations, primarily due to its basic hosting environment. However, we are actively working to refine the solution, addressing these dependencies. We encourage you to explore our test demo, though it is in its alpha stage and falls short of our ultimate vision. We appreciate your understanding as we continue to develop and enhance our offering. For a more detailed explanation of our approach, please watch this video: [Watch the Video](https://youtu.be/3uowBcjqDw4).", "logoImgData": {}, "bannerImgData": {}, "projectGithub": "ecofuseai", "projectTwitter": "ecofuseai"}
Contract Guardian: Empowering Smart Contracts with AI Auditing
Contract Guardian, developed by the EcofuseAI team, is an AI-powered web application designed to provide supplementary audit analysis for EVM-based Solidity smart contracts. This tool is meticulously crafted for accessibility and simplicity, aimed at assisting a wide range of users in their contract analysis needs.

Contract Guardian empowers users and organizations by offering a valuable contract analysis tool for smart contract code destined for deployment on the Optimism/EVM chain. It facilitates audit analysis, allowing users to proactively identify basic compilation errors, potential exploits, and vulnerabilities. These insights can complement the work of third-party auditing services, enhancing the overall security of smart contracts.

The tool operates through a straightforward process. Users input their smart contract code into a text input window, and Contract Guardian generates a preliminary audit analysis as output. You can explore this process in detail through an informative video explanation: [Watch the Video](https://youtu.be/3uowBcjqDw4).

Here are the relevant links for the Contract Guardian project:

- **Try Demo**: [Contract Guardian Demo](https://contractguard.ecofuse.ai/)
- **Website**: [EcofuseAI](https://www.ecofuse.ai/)
- **Twitter**: [EcofuseAI Twitter](https://twitter.com/ecofuseai)
- **Live Demo Test Video**: [Live Demo Test Video](https://youtu.be/hscuMvDK2cM)
- **In-depth Video Explanation**: [Watch the Video](https://youtu.be/3uowBcjqDw4)

The success of our project in meeting the requirements lies in the innovative approach we have taken to address common issues associated with AI-based auditing, namely accuracy and context.

1. **Multi-Model Unit (MMU)**: Contract Guardian employs multiple LLM models in a communication bridge. These models verify, critique, and complement each other's findings, exposing inaccuracies and offering a broader perspective on vulnerabilities and fixes. This approach significantly enhances accuracy and context.

2. **Incorporation of Third-Party Static Analyzers**: To combine the strengths of AI and non-AI tools, we integrate third-party static analyzers. These open-source tools check for compilation errors and basic vulnerabilities, providing valuable insights to the MMU. This dual approach ensures higher accuracy and greater context for the AI models.

3. **Additional Training Data**: Recognizing that LLM models were not initially designed for auditing code, we enrich their knowledge base with specialized training data. Langchain Vectorstores, built on extensive sources including audit reports, books, articles on vulnerabilities, and news about recent exploits, provide essential context, enabling the models to stay updated with the latest trends in vulnerabilities and exploits.

We acknowledge that our current demonstration has limitations, primarily due to its basic hosting environment. However, we are actively working to refine the solution, addressing these dependencies. We encourage you to explore our test demo, though it is in its alpha stage and falls short of our ultimate vision. We appreciate your understanding as we continue to develop and enhance our offering. For a more detailed explanation of our approach, please watch this video: [Watch the Video](https://youtu.be/3uowBcjqDw4).
Contract Guardian: Empowering Smart Contracts with AI Auditing