Toward Standardized Cross-Vendor Agent Tool Trust Management in Autonomous Networks

Abstract:Autonomous Network Levels 4-5 require AI agents to invoke tools across vendor boundaries without human oversight, yet existing management standards lack a standardized mechanism for cross-vendor trust visibility. When a tool from Vendor B is compromised, agents from Vendor A continue invoking it -- unaware of the trust degradation -- causing cascading service impact. We present AgentToolMO, a proposed 3GPP NRM information model for agent tool trust management. The model comprises: a formally defined trust state machine with provable graduated enforcement, damped cascade propagation with bounded convergence, cross-vendor trust notifications via existing Management Services (MnS) interfaces, and retroactive impact assessment through NRM dependency graph traversal. Simulation-based evaluation across multi-vendor topologies shows that standardized cross-vendor notifications reduce blast radius from hours-scale undetected propagation to near-real-time containment bounded by MnS notification delivery, with cascade convergence guaranteed in bounded iterations and sub-linear notification scaling across vendor domains. The framework operates within existing 3GPP management infrastructure, leverages existing protocols, and provides a standardization pathway for trustworthy multi-vendor autonomous network management.

Artificial Intelligence (cs.AI); Cryptography and Security (cs.CR); Networking and Internet Architecture (cs.NI)

arXiv:2607.25914 [cs.AI]

(or arXiv:2607.25914v1 [cs.AI] for this version)

https://doi.org/10.48550/arXiv.2607.25914 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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