RFC-ATF-4: Agent Trust Fabric — Proactive Governance Layer: Anticipatory Veto Protocol, Dynamic Semantic Portability, and Structural Shift Detection

RFC-ATF-4 specifies the Proactive Governance Layer (PGL) — the fourth RFC in the OMNIX Agent Trust Fabric Open Standard series, extending RFC-ATF-1, RFC-ATF-2, and RFC-ATF-3 without superseding any prior specification. The Problem Space RFC-ATF-1 answered the identity and delegation question: who authorized this agent, with what authority, and can that be proved offline without contacting the issuing platform? RFC-ATF-2 answered the runtime continuity question: did authority remain valid throughout execution, and was every health degradation event cryptographically attested? RFC-ATF-3 answered the evidence question: where does the resulting artifact go, who can interpret it across organizational boundaries, and can a regulator reconstruct the full chain of custody years later without platform access? RFC-ATF-4 answers a fourth, structurally harder class of questions that no existing governance framework — LangChain, AutoGPT, CrewAI, Microsoft AutoGen, or VeriSigil VGS — has formally addressed: Three Open Problems Closed (1) The Detection Latency Problem — Anticipatory Governance Veto Protocol (AGVP) A system satisfying only reactive governance (RFC-ATF-1/2/3) has a forensic gap between the onset of adverse conditions and the next governance request. During this interval, receipts may be issued under conditions the system would have rejected had it evaluated them. The AGVP closes this gap to ≤ 60 seconds by emitting ML-DSA-65 signed ProactiveVetoReceipts (PVRs) before any governance request arrives — anchoring the forensic record to the moment of detection rather than the moment of the next request. No prior AI governance specification emits an anticipatory governance receipt. This is a new artifact class. (2) The Recalibration Topology Problem — Structural Shift Detector (SSD) When the Assumption Validity Monitor detects sustained drift, two fundamentally different conditions are indistinguishable without additional analysis: a sustained excursion from a stable signal composition (recalibration safe) versus a structural change in which signals drive governance instability (recalibration unsafe). Recalibrating to a topology change would embed unvalidated assumptions as the governance baseline — a category error with compounding downstream effects. The SSD distinguishes them using the Component Rank Stability Index (CRSI) — a continuous 0, 1 metric proved correct across all real-number inputs by Z3 SMT (CRSI-BOUND-LO, CRSI-BOUND-HI, CRSI-CLASS-TOT). No prior specification defines CRSI or makes recalibration safety formally tractable. (3) The Semantic Portability Problem — Dynamic Semantic Portability Protocol (DSPP) A governance receipt preserves cryptographic integrity but not semantic portability: the meaning of its governance fields may shift as regulatory contexts evolve, sovereign policies are updated, or operational definitions drift. A receipt issued under EU AI Act Art. 9 today may carry different semantic weight in the same domain eighteen months from now — without any cryptographic change. The DSPP provides a unilateral, offline-computable Retroactive Semantic Assessment (RSA) that any receiving domain can perform without contacting the originating runtime — O (1) per receipt per domain, no bilateral negotiation required. The Semantic Drift Update (SDU) score aggregates three weighted components (Regulatory Alignment 0. 40, Operational Scope 0. 35, Technical Compatibility 0. 25) proved to sum to 1. 0 across all inputs (SDU-WSUM invariant). Formal Verification — Dual Methodology (First in AI Governance) 19 formal properties proved by OMNIX Formal Verification Suite (OMNIX-FVS-1. 0) using Z3 SMT solver — all 19 return UNSAT. Machine-reproducible in < 200ms per proof. Three properties additionally verified by TLA+ model checking (ATF-INV-001, ATF-INV-004, RGC-INV-004) — the first AI governance RFC with dual-methodology formal verification: arithmetic proofs across the continuous input domain (Z3) and state-machine safety proofs across all discrete execution traces (TLA+). Proof inventory by module: RFC-ATF-1/2 foundational (Z3+TLA+): ATF-INV-001, ATF-INV-004, RGC-INV-004 AGVP (Z3): AGV-INV-001, AGV-INV-002, AGV-INV-003, AGV-INV-004, AGV-INV-005, AGV-INV-006 CRSI/SSD (Z3): CRSI-BOUND-LO, CRSI-BOUND-HI, CRSI-CLASS-TOT, SSD-INV-001, SSD-INV-003 DSPP/SDU (Z3): SDU-BOUND-LO, SDU-BOUND-HI, SDU-WSUM, DSPP-INV-005, DSPP-INV-007a Total: 19/19 UNSAT · 0 SAT · 0 UNKNOWN · Runtime < 200ms per proof Compared to Closest Published Specification (VeriSigil VGS, May 2026) 19 Z3 proofs vs. 4 (4. 75× more) Dual Z3 + TLA+ methodology vs. separate methodologies on different protocols Proactive veto receipt (PVR) — not present in any published specification CRSI recalibration topology metric — not present in any published specification O (1) offline semantic portability — partial in VeriSigil (requires runtime contact for full assessment) Post-quantum signing ML-DSA-65 (FIPS 204) on all governance artifacts — not present in VeriSigil Compliance Designation ATF-PGL-Compliant (Proactive Governance Layer Compliant) — the fourth tier in the ATF compliance hierarchy: ATF-Compliant → ATF-RGC-Compliant → ATF-FEI-Compliant → ATF-PGL-Compliant → ATF-CGL-Compliant (RFC-ATF-5). Regulatory Alignment EU AI Act Art. 9 (risk management), Art. 13 (transparency), Art. 61 (post-market monitoring) · DORA Art. 6 (ICT risk), Art. 9 (protection) · NIST AI RMF GOVERN 1. 6 / MANAGE 4. 1 · China AI Law Arts. 20–22 · GCC/DIFC AI Regulation Art. 10 · SOC 2 Type II CC7. 2 · FATF Recommendation 16 Package Contents RFC-ATF-4. pdf — full specification with professional diagrams (ATF stack, AGVP flow, SSD decision tree, DSPP portability flow, 19-proof inventory) — 2, 477 lines proofᵣeport. json — 19 Z3 SMT proofs, all UNSAT, machine-reproducible via OMNIX-FVS-1. 0 conformanceᵥectors. json — 108 deterministic test vectors (AGVP: 31, SSD: 28, DSPP: 30, Cross-module: 19) Priority Records OMNIX-PAR-2026-AGVP-001 · OMNIX-PAR-2026-SSD-001 · OMNIX-PAR-2026-DSPP-001 · OMNIX-PAR-2026-FVS-001 Machine Verification Proof runner: python -m omnixcore. formalᵥerification. runₐll --json Test suite: pytest tests/testformalᵥerification. py (19 assertions, all pass) Implementation: omnixcore/ (Python 3. 11, open source) Acknowledgements Detection latency and recalibration topology problems (§2. 1, §2. 3) crystallized through technical dialogue with Reza Zarei (3S Silent Authority System). Semantic portability problem (§2. 2) formally articulated by Antonio Socorro in cross-system review of RFC-ATF-3. Dual-methodology formal verification approach inspired by VeriSigil's Z3 proof publication (Babatunde, 2026).