Why LLM-Generated Passwords Are Dangerously Insecure (www.irregular.com)

Recent research has highlighted the inherent insecurity of passwords generated by large language models (LLMs). While LLM-generated passwords may appear strong at first glance, they are, in fact, predictable as LLMs rely on token prediction rather than true randomness. This study tested several state-of-the-art models, including GPT and Claude, revealing troubling patterns such as repeated passwords and uneven character distribution. Despite these weaknesses, many users and coding agents inadvertently use LLM-generated passwords, often overlooking traditional secure password generation methods. The implications for the AI/ML community are significant, particularly as the accessibility of AI tools increases. As less tech-savvy users turn to LLMs for password generation, they may unknowingly compromise their security. This study urges both users and developers to favor established secure password generation practices and encourages AI developers to prioritize such techniques in their models. The findings serve as a cautionary reminder about the need for robust password management measures, especially in an era of growing reliance on AI-assisted coding and automation.