A deep technical article exploring how AI, feature engineering, and static smart-contract analysis uncover rugpull risks before humans detect them. Covers Solidity pattern mining, mint abuse detection, blacklist/fee manipulation signals, ML-inspired scoring models, and how to quantify ERC-20 token scam probability.
data-science machine-learning static-analysis smart-contracts cybersecurity solidity web3 feature-engineering erc20 security-research ai-security blockchain-security tokenomics decentralized-finance risk-scoring defi-security smart-contract-auditing token-security rugpull-detection ml-in-blockchain
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Updated
Nov 19, 2025