Cyberbullying has evolved into a significant digital threat, impacting various age groups across social media platforms, online gaming, educational portals, and communication networks.Traditionallystudiedthroughpsycholo gical and sociological lenses, cyberbullying is now increasingly recognized as a cybersecurity issue due to its association with privacy violations, identity theft, data manipulation, doxxing, deepfake harassment, and social-engineering attacks. This systematic review synthesizes global research published between2015and2024,analyzing cyberbullying through a cybersecurity framework. Based on 91 peer-reviewed studies selected from Scopus, Web of Science, IEEE Xplore, SpringerLink, and Google Scholar, the review evaluates the forms, mechanisms, and risks associated with cyberbullying, along with detection technologies, legal frameworks, and preventive strategies. Key findings reveal growing complexity in cyberbullying, including the use of anonymity tools, AIgenerated deepfakes, multimodal harassment, and cross-platform abuse. Although AI-based detection and machine learning models show promise, significant gaps persist, such as dataset limitations, inadequate cross-platform detection, and weak legal enforcement. The review underscores the need for comprehensive cybersecurity integration in cyberbullying mitigation, emphasizing the importance of AI-enhanced moderation, stronger legal frameworks, and improved digital literacy. The paper concludes by recommending further research on multimodal detection, virtual environments, and the development of standardized global policies for combating cyberbullying