Abstract: Computer security improvements relating to detection of social engineering attacks using a deep learning pipeline for account and communication correlations are disclosed. A service provider may utilize a framework having computing operations for detecting social engineering attacks, fraud, and other malicious or suspicious activities by malicious bots and other fraudsters. In this regard, the service provider may extract pattern data from communications using one or more AI models, which may include semantic information. Account assets for different accounts may be correlated using a relationship graph that links the assets based on the communication patterns shared between the assets. The relationship graph may then be used by additional AI models that classify if the communications are associated with social engineering attacks by classifying the communications using an attack classifier. The classification may be based on inferencing by the AI models from training on past social engineering attacks.