Ransomware is one of the most significant cybersecurity threats to modern networks, leveraging advanced techniques to communicate with Command and Control (C&C) servers to coordinate attacks, exfiltrate data, and issue encryption commands. The novel approach presented in this study provides a comprehensive method for tracing ransomware network traffic to C&C servers, focusing on detecting the specific communication patterns, encryption protocols, and geolocation data that can enhance existing detection systems. The methodology integrates both signature-based and anomaly-based techniques, allowing for the identification of ransomware traffic even when advanced obfuscation methods, such as domain-flux and fastflux techniques, are employed. Through the use of controlled sandbox environments, custom-built C&C server emulators, and sophisticated network traffic analysis, the research outlines key indicators of ransomware communications and provides practical tools for improving network defenses. The results demonstrate how a hybrid approach to detection can significantly increase accuracy while maintaining operational efficiency, offering a tangible framework for mitigating ransomware threats through early identification of C&C traffic. The study also highlights the importance of understanding the geographical distribution of C&C infrastructure and its implications for network security, particularly in regions with lenient cybersecurity regulations. Overall, the findings contribute to a deeper understanding of the ransomware ecosystem and its critical dependence on covert C&C communications, providing a foundation for developing more effective cybersecurity defenses.