A complete Web3 security toolkit combining AI-powered token auditing, ML-based deployer reputation scoring, and live Etherscan V2 data. Includes static analysis for rugpull detection, RandomForest reputation modeling, contract-fetching automation, and Solidity on-chain registries for transparent, reproducible security insights.

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.

A hybrid Solidity + Python security toolkit that analyzes ERC-20 token contracts using static pattern extraction and ML-inspired scoring. Detects mint backdoors, blacklist controls, fee manipulation, trading locks, and rugpull mechanics. Outputs interpretable risk scores, labels, and structured features for deeper analysis.

AI-powered real-time smart contract scanner that connects Machine Learning with Etherscan V2 to analyze newly deployed contracts instantly. Fetches verified Solidity code, performs static risk analysis, computes ML-driven deployer trust scores, and generates full security intelligence pipelines for Web3 threat detection.

A deep technical exploration of how malicious smart-contract developers weaponize fee logic in ERC-20 tokens. Covers dynamic tax flipping, hidden sell traps, fee obfuscation, whitelist-based bypasses, liquidity-drain funnels, attack timelines, forensic analysis, mathematical modeling, and ML-powered detection strategies for tax abuse.

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.

🔍 Analyze ERC-20 token smart contracts with ML-driven risk scores and labels to enhance security and identify potential threats.

🔍 Token Safety Analyzer for Ethereum — Detect honeypots, rug pulls & scam tokens using GoPlus Security API + Etherscan V2. Safety scoring system with Telegram bot alerts. Built with Python & Web3.py.

A proactive security dashboard for the Base and Solana ecosystems, powered by the Webacy Risk Engine to detect rug-pulls and malicious contracts in real-time.

🔍 Explore how developers misuse fee logic in smart contracts, uncovering methods of detection and modeling with machine learning to combat token tax abuse.

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