This blog post by Bruce Schneier discusses the vulnerabilities of large language models (LLMs) to prompt injection attacks, revealing that LLMs recognize text styles in role/instruction blocks, making them prone to security issues. The article emphasizes that unless LLMs can genuinely perceive roles, defenses against injections will continue to be challenging, likening the issue to a 'whack-a-mole' game. It highlights the continuous threat posed by subtle injections that can manipulate LLM states through seemingly harmless text.