metadata: {"type": "project", "title": "Malicious Contract Detector", "logoImg": "bafybeidn4aldo5j5xozmnteoysgzyv7ia4jfnc2iwwbedjhwe262d2c7qy", "website": "https://github.com/venglov/Malicious-Contract-Detector", "bannerImg": "bafybeigu4slwqzynbetk6bt5fistsbodv2ijdcsfhw76valmvdxl72wi4e", "createdAt": 1673702733262, "userGithub": "venglov", "credentials": {"twitter": {"type": ["VerifiableCredential"], "proof": {"jws": "eyJhbGciOiJFZERTQSIsImNyaXQiOlsiYjY0Il0sImI2NCI6ZmFsc2V9..Yl2A0lVBHqMOlaBdItbyoAV3I-GBe_2ZHE7EECIo5bNOoUVJm5EgmToh_lBAO7mQg6e5Gfm4ryZksohqQTipAw", "type": "Ed25519Signature2018", "created": "2023-01-14T13:24:48.655Z", "proofPurpose": "assertionMethod", "verificationMethod": "did:key:z6MkghvGHLobLEdj1bgRLhS4LPGJAvbMA1tn2zcRyqmYU5LC#z6MkghvGHLobLEdj1bgRLhS4LPGJAvbMA1tn2zcRyqmYU5LC"}, "issuer": "did:key:z6MkghvGHLobLEdj1bgRLhS4LPGJAvbMA1tn2zcRyqmYU5LC", "@context": ["https://www.w3.org/2018/credentials/v1"], "issuanceDate": "2023-01-14T13:24:48.655Z", "expirationDate": "2023-04-14T13:24:48.655Z", "credentialSubject": {"id": "did:pkh:eip155:1:0xA3c2e3d65206deE0456416F8189de7CF4fccbB22", "hash": "v0.0.0:59x9wqkj2j+lxp2gvTqtR81hQOkM1ZN8o5iC4uxshGY=", "@context": [{"hash": "https://schema.org/Text", "provider": "https://schema.org/Text"}], "provider": "ClearTextTwitter#vvlovsky"}}}, "description": "The Malicious Contract Detector project aims to use advanced machine learning techniques to analyze the code of new contracts and identify potential issues or vulnerabilities. The project is divided into two main parts: research and development.\n\nIn the research phase, a variety of algorithms and feature sets will be analyzed, including function signature hashes, abstract syntax trees, opcodes, and even approximate source code, to determine the optimal approach for identifying malicious contracts. The goal is to create a finished machine learning model that can accurately classify contracts as safe or potentially harmful.\n\nIn the development phase, the bot will be created and the process of transforming contract code into a feature set for analysis will be optimized. The focus will be on ensuring that the bot can handle high volumes of incoming contracts in real-time, while maintaining a high level of accuracy and precision.\n\nThe project is currently in the alpha testing stage, with initial results indicating that the BERT transformer model has shown promising results in classifying malicious contracts. A set of bots using different models will be created in order to further improve the accuracy and reliability of the Forta bot.", "logoImgData": {}, "bannerImgData": {}, "projectTwitter": "vvlovsky"}
name: Malicious Contract Detector