Hiago Kin Levi · Zenodo (CERN European Organization for Nuclear Research) 2026 · 2026
DOI: 10.5281/zenodo.23089652
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DAI (Decripte Artificial Intelligence) is a proprietary domain-specific LLM within a governed autonomous defensive architecture. It is an instance of the proposed ADAI (Autonomous Defensive Artificial Intelligence) category defined in the companion framework paper. This paper describes incident-response sessions spanning signal curation, structured target extraction, reviewed playbook selection, declared action contracts, deterministic admissibility, bounded network-edge execution, capability-disjoint verification, hash-linked evidence sealing, scheduled review, reconciliation and undo. The learned model is trained on the system’s own outcome-verified transcripts and narrates the result; admissibility and execution authority remain structurally outside the model. The paper addresses per-principal containment within shared enforcement domains, rule-budget aggregation, element-identified reconciliation, independent receipt recomputation and exact localization of controlled tampering. It reports a containment executed, independently observed and sealed 887 ms after the session’s first turn, a twelve-turn externally recomputed receipt, isolation observations and a review-to-undo cycle. These measurements refer to the version and period described in the manuscript and are not a claim of universal performance. Post-filing edition prepared on 1 October 2026. U.S. provisional application 64/166,855; patent pending, not granted. English manuscript and Portuguese translation. This is a preprint and is not represented as peer-reviewed.
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Zenodo (CERN European Organization for Nuclear Research) 2026 · 0 citations
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