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token-security

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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.

  • Updated Nov 19, 2025

A research-grade framework for extracting, classifying, and analyzing the “genetic” behavior of smart contract tokens. Identifies economic traits, supply mutations, fee patterns, permission risks, upgradeability vectors, and scam species using a structured gene taxonomy with risk scoring, HTML reports, and token comparison tools.

  • Updated Nov 29, 2025
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🛡️ Leverage AI to uncover hidden risks in ERC-20 tokens, detecting rugpulls before they harm investors. Analyze Solidity code for real-time threat assessment.

  • Updated Dec 24, 2025

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