Token price is the per-unit cost of using a language model, usually billed by input and output tokens. It is a basic way to estimate AI spend, compare vendors, and forecast the cost of chatbots, copilots, and agentic workflows. In practice, a low token price can make experimentation cheap, but the full bill also includes orchestration, storage, monitoring, and security controls.
In cyber security, token price matters because attackers and defenders both use models at scale. Attackers may optimize costs to run phishing generation, prompt testing, or automated reconnaissance more cheaply. Defenders track token price when budgeting for detection pipelines, red-team simulations, or secure AI features. But cost alone is not the main risk: if cheaper usage encourages wider deployment without least privilege, logging, and approval checks, an AI system can become an easier target for prompt injection or tool abuse.