Token Due Diligence

ChainAware Token Audit Launched – We Tested 10,000 CoinGecko Tokens. Here Are the Results.

ChainAware Token Audit is live – 127 automated security checks across 9 modules, tested against the top 10,000 CoinGecko tokens by market cap. The results: 55.2% high risk, 131 confirmed honeypots, 13.2% upgradeable proxy contracts – including 139 controlled by a single private key. ChainAware catches threats invisible to GoPlus, CertiK Skynet, and TokenSniffer: transitive approve() analysis, phantom balanceOf, EIP-2612 permit correctness, reentrancy detection, and asymmetric pause – powered by behavioral intelligence across 20M+ wallet personas on 8 blockchains. Free at chainaware.ai/token-audit.

How to Identify Fake Crypto Tokens in 2026: Rug Pulls, Long Rug Pulls, and DYOR

95% of PancakeSwap pools end as rug pulls. 99% of Pump.fun tokens extract money from buyers. This 2026 guide explains how to identify fake crypto tokens before investing – covering instant rug pulls, slow pump-and-dump schemes, the red flags to check manually, and which AI tools automate the detection for you.

Web3 AdTech and Fraud Detection – X Space with Magic Square

ChainAware co-founder Martin joins Magic Square to discuss Web3 AdTech and fraud detection for the real economy. Covers ChainAware’s origin from SmartCredit credit scoring through to fraud detection, rug pull prediction, wallet auditing, and Web3 AdTech – and why custom AI models, not LLM wrappers, are the only defensible IP moat in Web3.

AI-Based Predictive Rug Pull Detection: Why Static Analysis Fails and Behavioral AI Wins

Static smart contract analysis fails against professional rug pull operators who deliberately write clean code. Behavioral AI catches what code scanners miss – by reading the on-chain history of the people behind the contract. This guide explains why behavioral prediction beats static analysis for rug pull detection and how ChainAware’s V3 model achieves 90.1% accuracy.