In recent decades, cybercrime has become more and more frequent in people’s lives, causing serious consequences. Cybercrime groups usually hold a range of large and complex cyber assets to support the operation of their industries. Analyzing information about the cyber assets and the relationships among them can help people better understand the mechanism of cybercrime gangs. In this paper, based on an open-source cybercrime gang asset dataset, we propose a visual analysis system: CAGviz. The system helps to achieve tasks such as mining subgraphs of gang assets and extracting important assets. In addition, it also allows users to interactively view and analyze cyber asset information through a visual interface. Finally, two case studies illustrate the effectiveness of the system.