Don’t Just Guard the Door: Jailbreak Safety Needs Checkpoints A single prompt classifier is an attractive idea because it is simple, cheap, and easy to draw in a system diagram. The user sends a prompt. The guard says safe or unsafe. The model either answers or refuses. Very tidy. Also, increasingly incomplete. ...
Guardrails usually fail quietly. A user sends a malicious prompt. The model begins answering. The safety policy that looked firm in the demo environment starts behaving like office wallpaper: present, decorative, and not especially involved. By the time a post-hoc filter reads the final answer, the model has already produced the thing it should not have produced. The system may block the response from the user, but the real lesson is less flattering: the model crossed the line before the defense noticed. ...
The dangerous part is often clearer after the model starts answering Moderation usually begins with the user’s prompt. That sounds sensible. Read the request, classify the risk, block the bad thing, let the good thing through. A tidy little border checkpoint, complete with imaginary clipboard. The problem is that jailbreaks are not polite enough to declare themselves at the border. ...
TL;DR for operators Most LLM safety systems still assume that, when a model sees a harmful request, the correct behaviour is refusal. That works until the attacker stops arguing with the prompt and starts interfering with generation itself. The paper behind this article, Strategic Deflection: Defending LLMs from Logit Manipulation, proposes SDeflection: a fine-tuning method that teaches a model to answer in a safe, topic-adjacent way rather than relying only on explicit refusal language.1 The model does not provide harmful instructions. It redirects the subject toward harmless information that is close enough to the original topic to survive attacks that try to force compliance-style openings. ...
TL;DR for operators CAVGAN is not another “clever jailbreak prompt” paper. Its real claim is more uncomfortable: jailbreaks and defenses may both be expressions of the same internal boundary inside an LLM. If malicious and benign requests occupy separable regions in hidden-state space, then an attacker can try to push a harmful request into the “safe-looking” region. A defender can also monitor that same space and intervene before the model answers. Convenient. Also slightly rude. ...