The Internet of Everything (IoE) extends traditional IoT by integrating people, processes, data, and things into a highly dynamic and context-sensitive ecosystem. This convergence introduces complex security, privacy, and trust challenges that cannot be effectively addressed using static or device-centric models. In this paper, we propose CAT-M, a novel Context-Aware Trust Management framework that integrates dynamic trust evaluation, semantic policy enforcement, and context-sensitive privacy controls to secure heterogeneous IoE environments. CAT-M leverages fuzzy logic, semantic translation, and lightweight cryptography to ensure scalable, interoperable, and human-centric security. Through simulation in a smart healthcare scenario, we demonstrate the framework’s effectiveness in reducing privacy leakage, improving trust accuracy, and enabling real-time access control. The results highlight CAT-M’s potential as a unified approach to building secure and trustworthy IoE systems, while paving the way for future enhancements through intelligent trust prediction and cross-domain interoperability.