CB Insights named ChainAware.ai in its AI Fraud Prevention Market Map – placing it in the On-Chain Intelligence subcategory alongside Chainalysis, Elliptic, and TRM Labs. 200+ companies selected. One mission: building the trust and intelligence infrastructure the worldwide AI revolution demands.
CORRECTED: Week 22, 2026: $19,154,855 extracted across PancakeSwap V2/V3 and Uniswap V2/V3 – -3.6% vs prior week. 7,864 rug pull events. Running total (corrected for a USD double-counting bug) reaches $389,696,109.
CORRECTED: Week 21, 2026: $19,870,500 extracted across PancakeSwap V2/V3 and Uniswap V2/V3 – +16.5% vs prior week. 8,670 rug pull events. Running total (corrected for a USD double-counting bug) reaches $370,541,254.
CORRECTED: Week 20, 2026: $17,051,590 extracted across PancakeSwap V2/V3 and Uniswap V2/V3 – +5.1% vs prior week. 6,718 rug pull events. Running total (corrected for a USD double-counting bug) reaches $350,670,754.
$284,694,192. That is not a headline from a dramatic DeFi hack. No Twitter threads trended. No security firms issued emergency advisories. No mainstream crypto media ran front-page coverage. That is the total value extracted from retail investors on PancakeSwap V2 alone – across just 20 weeks in 2026 – through a mechanism so normalized it barely registers as news: the rug pull. 103,695 separate rug pull events. $973,588,405 removed. $688,894,213 added before removal. ChainAware simultaneously launches Rug Pull Detector V3, combining behavioral analysis of contract creators with full smart contract inspection to reach 90.1% prediction accuracy, up from 68% in V2.
Web3 lost $4 billion to fraud in 2025. Most fraud detection tools were built for wallet providers and CEXs – not DApps. ChainAware is the only platform purpose-built for DApps: behavioral wallet screening at connection, zero-code GTM deploy, 98% fraud accuracy, MiCA-aligned at 1% of Chainalysis cost.
Web3 lost over $3.6 billion to fraud in the first three quarters of 2025 – and 57.8% of those losses came not from smart contract bugs but from access-control failures. Trust in Web3 is not one problem. It is five distinct problems requiring five distinct solutions, and most protocols are only covering one.
Sybil attacks cost Web3 protocols billions annually in fake airdrop claims, manipulated governance votes, and inflated engagement metrics. This guide ranks and compares every major on-chain behavioral Sybil protection provider in 2026 – from GNN/RNN graph detection to behavioral scoring – and explains where each approach works and where it falls short.
Every wallet address that connects to your DApp carries a complete behavioral history. In 2026, three distinct layers of wallet auditing infrastructure have emerged – raw data, descriptive profiles, and actionable predictions – and confusing them leads to selecting the wrong tools for the job.
AI agents need on-chain wallet data to make intelligent decisions – but most blockchain data providers were built for human analysts, not autonomous systems. This guide maps every major provider enabling AI agent access to wallet data in 2026, from raw indexers to pre-computed behavioral intelligence layers.