When RAG Chatbots Expose Their Backend: An Anonymized Case Study of Privacy and Security Risks in Patient-Facing Medical AI
Background: Patient-facing medical chatbots based on retrieval-augmented generation (RAG) are increasingly promoted to deliver accessible, grounded health information. AI-assisted development lowers the barrier to building them, but they still demand rigorous security, privacy, and governance controls. Objective: To report an anonymized, non-destructive security assessment of a publicly accessible patient-facing medical RAG chatbot and identify governance lessons for safe deployment of generativ
Record details
Published: 1 May 2026
Source: arXiv
Category: Research
Topics: Regulation · Privacy · Healthcare
Retrieved: 14 July 2026
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ethics.ai (1 May 2026), “When RAG Chatbots Expose Their Backend: An Anonymized Case Study of Privacy and Security Risks in Patient-Facing Medical AI,” evidence record 5107, https://ethics.ai/record/5107 (originally published by arXiv).
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