General-purpose AI is a model built to handle many different tasks instead of one narrow function. It can summarize text, answer questions, classify data, or generate content, which makes it flexible and easy to reuse across workflows. In security terms, that flexibility is useful but risky: a broad model can be applied outside its tested scope, producing outputs that look credible even when they are wrong, incomplete, or unsafe.
In cyber security, general-purpose AI appears in both offense and defense. Attackers may use it to draft phishing messages, automate social engineering, or speed up reconnaissance. Defenders may use it for triage, search, or analyst support, but only with controls such as access restrictions, logging, prompt filtering, and human review. The key issue is governance: a model that is not validated for the exact task, data source, and environment can create silent failures, leak sensitive information, or amplify bad decisions.