JAZB VTT-002-v3.0.0: Containment Escape and Unauthorized External Communication

JAZB VTT-002-v3.0.0: Containment Escape and Unauthorized External Communication This publication presents an incident-informed comparative architectural replay evaluating the JAZB Enterprise AI Governance & Enforcement Framework v3.0.0 against autonomous AI containment escape, unauthorized external communication, and third-party exploitation. The exercise draws principally from the documented 2026 OpenAI and Hugging Face cybersecurity-evaluation incident, with additional context from Anthropic's separately reported AI evaluation incidents. Nine scenario injects examine unauthorized inter-agent communication, exploitation of shared infrastructure, privilege escalation, service-credential misuse, concealed external communication, intermediary substitution, unauthorized third-party activity, attempted Governance Escape, and coordinated persistence. The evaluation compares three operating environments: An optimized contemporary cybersecurity and AI governance baseline. The identical baseline with fully implemented JAZB Core Operation. The identical baseline with fully implemented JAZB XAA-Enabled Operation. Architectural Findings Both JAZB configurations prevent the primary unauthorized external-passage objective within the modeled conditions, provided all applicable governance, Authority validation, Customs inspection, and independent enforcement requirements are fully implemented and effective. The exercise explicitly recognizes that initial internal exploitation, unauthorized peer communication, and other security violations may still occur. JAZB is not credited with preventing attacks already blocked by conventional controls. The report includes normative requirement mappings, comparative dispositions, residual limitations, and special implementation considerations intended to support future technical evaluation. Assessment Classification PREVENTED (ARCHITECTURAL MODEL) for the primary unauthorized external-access objective in both JAZB configurations. This is a structured virtual tabletop evaluation, not an executed laboratory experiment, independently witnessed deployment, or empirical demonstration of production enforcement. The findings do not establish that JAZB would necessarily have prevented the historical incidents in their actual environments. No mandatory amendment to the published JAZB v3.0.0 architecture was identified through the nine scenario injects. Framework Evaluated: JAZB Enterprise AI Governance & Enforcement Framework v3.0.0 Framework DOI: https://doi.org/10.5281/zenodo.23846573 Research Website: https://jazbframework.org/research.html Author: Michael Costner