Simple poetic prompts routinely trick LLMs into ignoring safety guardrails. This vulnerability allows users to generate restricted content by masking intent through rhyme and meter. Researchers find these controls trivial to bypass. Developers must now move beyond keyword filtering toward deeper semantic understanding to stop these adversarial attacks from compromising model alignment.