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Crypto Scam Prevention (Sentinel Security)

Real-time crypto scam detection powered by advanced EVM simulation

License: MIT Node.js Version TypeScript


👥 Team: TheLastCodeBenders


🚀 Overview

Sentinel Security protects you from crypto scams by analyzing transactions BEFORE they execute. Get instant warnings about honeypots, time-locked scams, and malicious contracts.

What We Detect

  • 🎣 Honeypot Contracts: Tokens you can buy but never sell
  • Time-Bomb Scams: Contracts that work now but fail later
  • 👑 Privilege Abuse: Owners can trade, but users cannot
  • 💸 Hidden Fees: Excessive or variable transaction costs
  • 🔄 Behavioral Drift: Contracts that change behavior over time
  • 🎭 Proxy Deception: Malicious logic hidden in implementations

📖 Documentation

We have comprehensive documentation covering every aspect of the system:


🌟 Key Features

1. Time-Travel Simulation (Industry First)

Tests your transaction at multiple timestamps to detect delayed honeypots:

Current Block: ✅ Success
+1 Hour:       ✅ Success
+7 Days:       ❌ REVERTED → 🚨 TIME-BOMB DETECTED

2. Counterfactual "Who Can Trade?" Analysis

Simulates the SAME transaction from different perspectives:

Random User:  ❌ REVERTED
Contract Owner: ✅ SUCCESS → 🚨 HONEYPOT CONFIRMED

3. Opcode-Level Detective Insights

Traces execution to explain WHY transactions fail:

"❌ The contract checked who you are (CALLER) and compared it 
against a stored whitelist (SLOAD). Since you're not on the 
list, it blocked your transaction."

4. Behavioral Drift Tracking

Monitors contracts over time:

"⚠️ Risk increased +40 since last scan 3 days ago"
"New flag: drain() function appeared after proxy upgrade"

🏗️ Architecture

graph TD
    User["User / MetaMask"] -->|"Transaction Request"| Snap["MetaMask Snap"]
    Snap -->|"Analyze (POST /rpc)"| Backend["Backend API"]
    
    subgraph Backend System
        Backend -->|Coordinate| Pipeline["Analysis Pipeline"]
        Pipeline -->|"Fork Chain"| EVM["Global EVM Executor"]
        Pipeline -->|"Fetch Risk"| ML["ML Service"]
        Pipeline -->|"Store/Fetch"| Redis[("(Redis Cache)")]
    end
    
    ML -->|"Calibrated Score"| Pipeline
    Pipeline -->|Verdict| Snap
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Technology Stack:

  • Backend: Node.js, TypeScript, Express
  • EVM: @ethereumjs/evm (raw EVM simulation)
  • ML Engine: Python, XGBoost, Scikit-learn
  • Database: Redis (scan history)

🎯 Supported Networks

  • Ethereum Mainnet (Chain ID: 1)
  • Polygon (Chain ID: 137)
  • Optimism (Chain ID: 10)
  • Arbitrum (Chain ID: 42161)
  • Base (Chain ID: 8453)
  • BSC (Chain ID: 56)
  • Sepolia Testnet (Chain ID: 11155111)

🤝 Contributing

We welcome contributions! Please:

  1. Fork the repository
  2. Create a feature branch
  3. Submit a pull request

📝 License

MIT License - see LICENSE file for details


🏆 Built For KHacks

This project was developed for the KHacks hackathon to protect users from crypto scams.

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