The field of cloud security and natural language processing is rapidly evolving, with a focus on innovative solutions to protect against cyber threats and enhance the robustness of large language models. Researchers are exploring the application of natural language processing methodologies, such as topic modelling, to analyze cloud security data and predict future attacks. This approach has the potential to provide a new form of vulnerability detection, improving overall security throughout the CI/CD pipeline. Additionally, the development of novel attacks against large language models, such as lingual-backdoor attacks, highlights the importance of promoting research on potential defenses to enhance the models' robustness. Furthermore, the creation of culturally adapted models for reliable content moderation in underrepresented languages is gaining attention. Noteworthy papers include: BadLingual, which presents a novel task-agnostic lingual-backdoor attack against large language models, and A Comparative Benchmark of a Moroccan Darija Toxicity Detection Model, which highlights the importance of culturally adapted models for reliable content moderation.