Introduction: DGFraud is a Graph Neural Network (GNN) based toolbox for fraud detection. It integrates the implementation & comparison of state-of-the-art GNN-based fraud detection models. It also includes several utility functions such as graph preprocessing, graph sampling, and performance evaluation. The introduction of implemented models can be found here . Useful Resources Graph-based Fraud Detection Paper List Awesome Fraud Detection Papers Attack and Defense Papers on Graph Data PyOD: A Python Toolbox for Scalable Outlier Detection (Anomaly Detection) PyODD: An End-to-end Outlier Detection System DGL: Deep Graph Library Outlier Detection DataSets (ODDS) Table of Contents Installation User Guide Implemented Models Model Comparison TODO List How to Contribute github地址： https://github.com/safe-graph/DGFraud