Detect Rug Pulls Before They Drain Your Wallet
SentinelX analyzes Ethereum smart contracts using XGBoost machine learning, rule-based security detection, and SHAP explainability to identify potential rug-pull indicators, honeypots, and hidden backdoors. Our model extracts 53 smart-contract features and produces risk scores from 0-100 with transparent explanations.
Analyze any Ethereum contract by address or paste raw Solidity source code. SentinelX provides automated security analysis for informational and research purposes only.
Key Features
- AI-powered smart contract risk analysis with 96.15% accuracy
- XGBoost machine learning classification trained on 2,400+ contracts
- SHAP feature attribution for explainable risk scoring
- Honeypot detection, hidden mint identification, and access control analysis
- Real-time analysis with sub-3-second response times
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Technical Stack
- Backend: FastAPI + XGBoost ML model + SHAP explainability
- Frontend: React + TypeScript + Tailwind CSS
- Database: Supabase (PostgreSQL) with Row Level Security
- Model: XGBoost classifier trained on 2,400+ labeled contracts with 53 features
- Deployment: Vercel (frontend) + Render (backend)
SentinelX provides automated security analysis for informational purposes only. Results are not financial advice or guarantees of safety.