Journal of Cybersecurity and Information Management JCIM 2690-6775 2769-7851 10.54216/JCIM https://www.americaspg.com/journals/show/3154 2019 2019 Associate Professor, Department of CSE, Koneru Lakshmaiah Education Foundation Vaddeswaram, AP, India M. M. Professor, Dept. of EEE, Mailam Engineering College, Villupuram, TN, India A. Jeraldine Viji Associate Professor, Department of Computer Science and Engineering, Guru Ghasidas Vishwavidyalaya (A Central University), Bilaspur, (C G), India Amit Kumar Chandanan Senior Assistant Professor, School of Computer Science Engineering and Artificial intelligence (SCAI), VIT-Bhopal University, India Vijay Birchha Assistant Professor (Computer Science), College of Community Science, Central Agricultural University, Tura, Meghalaya, India Tushar Kumar Pandey Assistant professor, Department of Computer Science and Engineering, Bhilai Institute of Technology Durg, Chhattisgarh, 491001, India Sumit Kumar Sar As AI is deployed increasingly in defensive systems, hostile assaults have increased. AI-driven defensive systems are vulnerable to attacks that exploit flaws. This article examines the approaches used to resist AI-based cybersecurity systems and their effects on security. This paper examines existing literature and case studies to demonstrate how attackers modify AI models. These include avoidance, poisoning, and data-driven assaults. It also considers data breaches, system failures, and unauthorized access if a hostile effort succeeds. The report recommends adversarial training, model testing, and input sanitization to address these issues. It also stresses the need for monitoring and updating AI algorithms to adapt to changing opponent tactics. This paper emphasizes the need to limit hostile strike threats using real-life examples and statistics. To defend AI-driven cybersecurity systems from complex threats, cybersecurity specialists, AI researchers, and policymakers must collaborate across domains. This article provides full guidance for cybersecurity and AI professionals. It describes the complex issues adversarial assaults create and proposes a flexible and robust architecture to safeguard AI-driven cybersecurity systems from emerging threats. 2025 2025 288 297 10.54216/JCIM.150123 https://www.americaspg.com/articleinfo/2/show/3154