I just generated 1,000,000 transaction graph visualizations from real Ethereum/Arbitrum/Polygon data — now training a Vision-Language model to detect DeFi attacks

The author generated 1,000,000 transaction graph visualizations from real Ethereum, Arbitrum, and Polygon data and is training a Vision-Language model to detect DeFi attacks. The dataset is open and available under an MIT license. The goal is to create a model that can identify attack patterns in transaction graphs.