Reasoning is the internal problem-solving work a model performs to turn a request into an answer. In AI systems, it often means extra computation spent on step-by-step analysis, planning, or tool use, which can increase token consumption and latency. Stronger reasoning can improve accuracy on complex tasks, but it also makes each request more expensive and less predictable.
In cyber security, reasoning matters because it affects both defense and abuse. Security teams use it for alert triage, phishing analysis, malware summarization, and incident-response assistants. Attackers can try to force unnecessary reasoning through long prompts, chained questions, or agent workflows, driving up cost, slowing response, and increasing the chance of mistakes. Good defenses limit when reasoning is triggered, keep prompts narrow, and apply policy checks before expensive model paths are used.