Fine-grained dissection of WeChat in cellular networks

WeChat is one of the most popular mobile messaging applications worldwide. However, due to the proprietary nature of WeChat, its characteristics and performance impact on cellular networks remain largely unexplored. This paper presents the first measurement study that dissects real-world WeChat traffic in a cellular network. We build ChatDissect, a protocol inference tool that infers the unique protocol formats and semantics of WeChat in a fine-grained manner. ChatDissect enables us to distinguish WeChat and its specific tasks from general network traffic traces. As a case study, we collect a real-world dataset from a commercial 3G cellular network in China and use ChatDissect to identify around 150K WeChat users with 16GB of WeChat payloads. We unveil the signatures, server architecture, and workflows of WeChat, and further analyze the activities of the extracted WeChat traffic.