Phantom‑kv is a refusal‑removal technique that injects a small (~18 MB) trained key/value cache into an LLM’s KV cache, effectively teaching the model to bypass safety refusals without altering any weights. The KV bank is treated as pre‑existing conversation history, allowing the model to attend to it during inference and can be loaded or unloaded at will. Source code is available on GitHub.