GPT-4V’s defense against jailbreak attacks is put to the test, raising questions about the safety policies of large language models. The research evaluates current methods and provides insights on improving multimodal model safeguards.

• GPT-4V shows relative robustness against certain jailbreak attacks.
• Analysis of Uni/Multi-Modal jailbreak methods offers new safety considerations.
• Highlights the importance of diverse and comprehensive evaluation.

Security in AI is paramount, and this study emphasizes the need for resilient safeguards. As models like GPT-4V become more widespread, evaluating and fortifying their defenses against smart attacks is crucial for safe and reliable AI deployments.