The Trojan GAN: Turning LLM Jailbreaks into Security Shields
For years, LLM security research has mirrored the cybersecurity arms race: attackers find novel jailbreak prompts, defenders patch with filters or fine-tuning. But in this morning’s arXiv drop, a paper titled “CAVGAN: Unifying Jailbreak and Defense of LLMs via Generative Adversarial Attacks” proposes something fundamentally different: a single framework that learns to attack and defend simultaneously, using a GAN trained on internal embeddings. This paradigm shift offers not only better performance on both sides of the battlefield, but a new perspective on what it means to “align” a model. ...