Recent advances in information and communication technology have increased the complexity and connectivity of modern software systems. As Artificial Intelligence (AI) becomes more widely adopted, more sophisticated AI-based attacks (i.e., offensive AI) on systems are emerging. These attacks can be adaptive, harder to detect, and highly destructive, and existing defence mechanisms are often inadequate against their evolving nature and decision logic. Systems that rely on interconnected components, external services, and third-party technologies further expand the attack surface, making it critical for organisations to prepare and strengthen resilience against offensive AI. This scientific research project contributes to resilience against AI-based cyberattacks. The overall goal is to understand which types of AI-based cyberattacks may affect software systems, their potential impact, and the strategies that can protect systems from such attacks. The proposed approach employs an AI attacker and an AI defender that engage in a game-theoretic setting: both agents act on a target system, receive rewards through reinforcement learning, and adapt their strategies over time. The AI attacker aims to uncover vulnerabilities and improve attack strategies, while the AI defender learns to adapt responses and strengthen system resilience against offensive AI. This project also aims to produce scientific publications in highly ranked conferences or journals. Two senior and one junior researchers at RISE will be involved in the project.