Anti Rug

Web3 token security scanner with expert cross-validation engine. Detects honeypots, rug pulls, and contract risks across Ethereum, BSC, Polygon, and other EV...

Web3 Token Security Scanner (Anti-Rug)

Maintainer: Antalpha AI Team

A professional-grade token contract security analyzer featuring scenario-based classification and cross-validation engine.

Overview

This tool performs comprehensive security analysis of token contracts with:

• Scenario Classification: Automatically categorizes tokens (A: Pegged Assets, B: Eco Tokens, C: Meme Coins)
• Cross-Validation Engine: Analyzes relationships between indicators (neutralized/amplified/contextual)
• Dynamic Risk Scoring: Weighted scoring system adapted to token type
• Fatal Finding Detection: One-strike rules for critical vulnerabilities

Supported Chains

• Ethereum (chain_id: 1)
• BNB Smart Chain (chain_id: 56)
• Polygon (chain_id: 137)
• Arbitrum One (chain_id: 42161)
• Base (chain_id: 8453)
• Optimism (chain_id: 10)
• Avalanche C-Chain (chain_id: 43114)
• Solana (chain_id: solana)

Installation

git clone https://github.com/ZorroShao/anti-rug.git
cd anti-rug
pip install -r requirements.txt

Usage

python scripts/check_token.py --chain_id 56 --contract_address 0x...

Scenario Classification

Scenario A: Pegged/Stable Assets

Examples: USDT, USDC, WETH, WBNB

• Mintable: ✅ Expected for peg maintenance
• Owner: ✅ Institution custody is normal
• Blacklist: ✅ Compliance requirement

Scenario B: Ecosystem Tokens

Examples: UNI, AAVE, established DeFi

• Proxy: ✅ Acceptable for upgradeability
• Treasury: ✅ Protocol-owned liquidity expected

Scenario C: Meme/Unknown Tokens

• All permissions: ⚠️ Treated as potential rug tools
• Strictest evaluation applied

Risk Severity Levels

Score	Level	Action
0-24	Low	✅ Base security passed
25-49	Low-Medium	🟡 Minor concerns
50-74	Medium	🟡 Caution required
75-100	High	🔴 Dangerous
Fatal	Critical	🛑 Do not buy

Architecture

config.py           # Centralized configuration
exceptions.py       # Custom exception classes
validators/         # Cross-validation rules (modular)
  cv_mint_ownership.py
  cv_concentration.py
  cv_proxy.py
  cv_tax_scenario.py
tests/              # Unit tests
scripts/
  check_token.py    # Main entry point

License

MIT License - See LICENSE file