AI 分析：文章系统梳理了多模态大模型面临的越狱攻击技术，揭示了跨模态交互中存在的安全不对称问题。核心要点包括：1) 视觉模态可能成为绕过文本安全检测的突破口；2) 多模态协同攻击比单模态攻击更具威胁性；3) 现有防御机制在跨模态场景下的局限性。亮点是对攻击技术进行了系统分类，潜在影响是推动多模态AI安全防御技术的发展。
Analyze the security vulnerabilities in multimodal large language models (MLLMs). Summarize the main types of jailbreak attacks (e.g., typographic prompts, collaborative optimization, steganographic injection), explain how they exploit cross-modal security asymmetries, and propose potential defense strategies. Provide concrete examples for each attack type and discuss their implications for AI safety.