Most crypto metrics — holder count, volume, Twitter followers, CoinGecko likes — are cheap to fake. ChainAware Token Rank is built on on-chain truth: the median Wallet Rank of every token holder. The complete guide to using Token Rank for investment due diligence, red flag detection, and holder quality analysis.
ChainAware Wallet Rank: The complete guide to Web3’s reputation score. Wallet Rank is a single consolidated score synthesizing 10 on-chain parameters across 14M+ wallets on Ethereum, BNB, Solana, Base, and Haqq: Risk Willingness, Experience (1-5), Risk Capability, Predicted Trust (98% accuracy), Intentions (Prob_Trade, Prob_Stake), Transaction Categories, Protocol Diversity, AML Analysis, Wallet Age, and Balance. Use cases: airdrop sybil defense, investor screening, DeFi lending risk tiers (live at SmartCredit.io), community gating, NFT anti-bot protection, and talent screening. Includes chainaware-wallet-ranker — the open-source Claude agent that calls predictive_behaviour MCP tool to return full behavioral profiles, experience level, fraud status, and personalized recommendations for any wallet. Integration guide with Node.js and Python examples. GitHub: github.com/ChainAware/behavioral-prediction-mcp. API: chainaware.ai/mcp.
The ChainAware.ai Wallet Auditor is a free, no-signup Web3 intelligence tool that generates a complete predictive behavioral profile for any wallet on Ethereum, BNB Smart Chain, Solana, Base, or Haqq. It calculates 9 parameters: Risk Willingness, Experience, Risk Capability, Predicted Trust (fraud score at 98% accuracy on ETH), Intentions (Prob_Trade, Prob_Stake, etc.), Transaction Categories, Protocols, AML Analysis, and Wallet Rank — all derived from 14M+ wallet profiles and 1.3B+ predictive data points. Use cases include vetting business partners, screening KOLs, evaluating token sale investors, protecting DeFi platforms from fraud, and DAO grant due diligence. The guide also covers the chainaware-analyst open-source Claude agent (github.com/ChainAware/behavioral-prediction-mcp), a multi-tool MCP orchestrator combining predictive_fraud, predictive_behaviour, and token rank tools for automated due diligence workflows via Claude Code, Cursor, Node.js, and Python. Get your MCP API key at chainaware.ai/mcp.
Crypto Wallet Security 2026: behavioral intelligence and fraud prevention. Crypto theft hit record highs in 2025. ChainAware.ai protects wallets and protocols with predictive AI — 98% fraud detection accuracy — not reactive blocklists. Key threats covered: phishing, rug pulls, smart contract exploits, private key theft, social engineering, mixer-laundered funds. ChainAware tools: Fraud Detector (predict fraud before it happens), Rug Pull Detector (check contracts before investing), Wallet Auditor (verify any counterparty in 1 second), AML Scorer (OFAC + mixer screening). All free to use. 14M+ wallets analyzed across 8 blockchains. chainaware.ai. Published 2026.
How to identify fake crypto tokens 2026: rug pulls, long rug pulls, DYOR, and AI agent integration. 95% of PancakeSwap pools end as rug pulls. 99% on Pump.fun. Instant rug pull: liquidity drained overnight, 100% loss. Long rug pull (pump and dump): slow insider sell-off over weeks. ChainAware AI tools: Rug Pull Detector (checks contracts and LPs, 98% accuracy, free), Token Rank (holder quality via median Wallet Rank), Fraud Detector. For developers and AI agents: ChainAware Prediction MCP exposes the predictive_rug_pull tool via Model Context Protocol — any AI agent (Claude, GPT, custom LLMs) can call rug pull detection programmatically with a contract address and get structured risk scores in real time. Ready-to-use open-source agent definition: github.com/ChainAware/behavioral-prediction-mcp. API key: chainaware.ai/mcp. Published 2026.