Building an Automated Red‑Team Framework for LLM Security Testing
This article presents a systematic approach to evaluating large language model security by defining threat models, categorizing attack surfaces such as jailbreak and privacy leakage, and describing an automated red‑team platform that generates, mutates, scores, and evolves adversarial prompts to continuously assess model robustness.
