Internal monologues in reasoning models create a critical security flaw. Attackers can trigger excessively long streams of thought, slowing systems to a crawl. This vulnerability targets the step-by-step processing used by LLMs for complex coding and math. Developers must now balance deep reasoning capabilities with strict output constraints to prevent these resource-exhaustion attacks.