In the ever-evolving realm of cybersecurity, the rise of generative AI models like ChatGPT, FraudGPT, and WormGPT has introduced both innovative solutions and unprecedented challenges. This research delves into the multifaceted applications of generative AI in social engineering attacks, offering insights into the evolving threat landscape using the blog mining technique. Generative AI models have revolutionized the field of cyberattacks, empowering malicious actors to craft convincing and personalized phishing lures, manipulate public opinion through deepfakes, and exploit human cognitive biases. These models, ChatGPT, FraudGPT, and WormGPT, have augmented existing threats and ushered in new dimensions of risk. From phishing campaigns that mimic trusted organizations to deepfake technology impersonating authoritative figures, we explore how generative AI amplifies the arsenal of cybercriminals. Furthermore, we shed light on the vulnerabilities that AI-driven social engineering exploits, including psychological manipulation, targeted phishing, and the crisis of authenticity. To counter these threats, we outline a range of strategies, including traditional security measures, AI-powered security solutions, and collaborative approaches in cybersecurity. We emphasize the importance of staying vigilant, fostering awareness, and strengthening regulations in the battle against AI-enhanced social engineering attacks. In an environment characterized by the rapid evolution of AI models and a lack of training data, defending against generative AI threats requires constant adaptation and the collective efforts of individuals, organizations, and governments. This research seeks to provide a comprehensive understanding of the dynamic interplay between generative AI and social engineering attacks, equipping stakeholders with the knowledge to navigate this intricate cybersecurity landscape.

翻译：在快速演变的网络安全领域，ChatGPT、FraudGPT与WormGPT等生成式AI模型的兴起，既带来了创新解决方案，也引发了前所未有的挑战。本研究运用博客挖掘技术，深入探讨生成式AI在社会工程攻击中的多维度应用，揭示不断演化的威胁态势。生成式AI模型革新了网络攻击领域，使恶意行为者能够构建更具说服力的个性化钓鱼诱饵、通过深度伪造技术操纵公众舆论、并利用人类认知偏差。这些模型——ChatGPT、FraudGPT与WormGPT——不仅放大了既有威胁，还催生了新的风险维度。从模仿可信机构的钓鱼活动，到冒充权威人物的深度伪造技术，我们系统剖析了生成式AI如何增强网络犯罪分子的攻击能力。此外，本文揭示了人工智能驱动的社会工程攻击所利用的脆弱性，包括心理操纵、定向钓鱼以及真实性危机。为应对这些威胁，我们提出了一系列策略，涵盖传统安全措施、基于AI的安全解决方案以及网络安全领域的协作方法。我们强调，在对抗AI增强型社会工程攻击的斗争中，保持警惕、提升意识并加强监管至关重要。在AI模型快速演进且训练数据匮乏的环境下，抵御生成式AI威胁需要持续适应，并依赖个人、组织及政府的协同努力。本研究旨在全面阐释生成式AI与社会工程攻击之间的动态交互关系，为相关利益方提供应对这一复杂网络安全格局的知识武装。