KILL SWITCH GOVERNANCE OF ARTIFICIAL INTELLIGENCE (AI) SESSION MEMORY THROUGH USER INVOKED AND POLICY TRIGGERED KV CACHE SANITIZATION

Kill switch governance of artificial intelligence session memory is disclosed. A transformer based inference system maintains a session specific KV cache comprising cached key tensors and value tensors derived from prompt-associated inputs. A software control, hardware actuator, or both initiate a kill switch responsive to user actuation, detection of a privacy condition, or detection of a policy condition. The system identifies session derived inference state artifacts, including at least the session specific KV cache, and sanitizes the identified artifacts by deleting, overwriting, invalidating, quarantining, encrypting, cryptographically erasing, access revoking, or otherwise rendering them unavailable for subsequent inference while preserving unrelated model weights. The sanitization may apply to remote data-center KV cache partitions, local edge inference KV cache entries, or both. In some embodiments, a purge receipt is generated without retaining plaintext prompt content.