The paper introduces a novel Call Detail Record generator designed to produce massive synthetic datasets for telecommunications research and operational testing. The generator employs a multi-distribution approach and Markov chains to simulate realistic telecommunications data, encompassing both standard user behaviors and complex scenarios such as SIM box fraud or telecommunication probes. The generator serves multiple practical applications, including network planning and optimization, fraud detection and the training and testing of AI and machine learning models for predictive analytics. Moreover, the generator is characterized by very high speed of operation, allowing the generation of millions of events in seconds.