Technology has continued to advance over the years giving rise to the era of Large Language Models (LLMs) and Large Multimodal Models (LMMs) which have demonstrated abilities to process vast amounts of data in various formats. As much as LLMs and LMMs are transforming the way key sectors operate through beneficial integrations; they have also introduced a new barrage of security and privacy concerns. This paper presents a multi-domain analysis of these challenges. We focus on three key sectors: education, health, and finance. Through this detailed study, we highlight various threats such as data breaches, biased output, and unauthorized access. To address these and other threats, mitigation strategies are proposed including validation techniques and differential privacy. We aim to provide valuable security and privacy insights to developers, policymakers, and users on LLMs and LMMs integration in various domains.