A working UVLM research release for split-knowledge evaluation, provenance, red teaming, correction, and coordinated disclosure, without publishing dangerous content.

A UVLM research manuscript examines whether real high-consequence information could be conveyed through public media that only a prepared audience can interpret, and how to detect such channels without turning art, spirituality, or coincidence into accusation.

This manuscript formalizes an architecture, mathematical vocabulary, software boundary, and empirical evaluation program. It does not report a completed validation study; certify truth; establish a literal quantum mechanism for cognition; authorize memory, canonization, publication, deployment, or release; or grant autonomous authority to generated hypotheses.

UVLM introduces MORALware, a non-lethal, evidence-grounded AI governance layer using triadic review, deterministic veto, provenance, and auditable refusal. Most AI safety asks how to make machines obey. UVLM asks what must remain impossible—even when an order is authenticated, urgent, and powerful.