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• The proposed security architecture employs a six-domain threat model for agentic AI in healthcare, covering credential exposure, execution capability abuse, network egress exfiltration, prompt integrity failures, database access risks, and fleet configuration drift.method 70%
• The security architecture implements a four-layer defense in depth strategy including kernel-level workload isolation using gVisor on Kubernetes, credential proxy sidecars, network egress policies, and a prompt integrity framework.method 70%
• The architecture was deployed for nine autonomous AI agents in production at a healthcare technology company.technical 70%
• During a 90-day deployment period, four HIGH severity security findings were discovered and remediated by an automated security audit agent.result 70%
• The deployment demonstrated progressive fleet hardening across three VM image generations.result 70%
• The defense coverage of the architecture maps to all eleven attack patterns identified in recent literature.result 70%
• The effectiveness of the architecture might be limited by its configuration complexity and the necessity for constant updates to address emerging threats.limitation 70%
• The proposed security framework has the potential to replace existing, less specialized security solutions in the healthcare sector for AI agent deployment.market 70%

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