How-AI-Detects-Rugpulls AmirhosseinHonardoust · COMPLETED
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.
github.com/AmirhosseinHonardoust/How-AI-Detects-Rugpulls · ★ 21 · Forks 0 · Size 120 KB
SUMMARY
Technologies 1
Scored 1
Observed 1
Practices 6
Evidence 1
Skips 0
COVERAGE
Analyzed 2 files · 27 commits · 0 API calls
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ACTIVITY & OWNERSHIP
First commit 2025-11-17
Last commit 2025-11-19
Active months 1
Commits 27