Healthcare
Securing AI in Healthcare. HIPAA-Compliant, Audit-Ready.
Healthcare organizations deploying AI face unique security and compliance requirements. We help you ship AI that meets HIPAA standards and withstands adversarial testing.
The Challenge
AI in Healthcare Creates New Attack Surfaces
Traditional security controls were not designed for AI pipelines that process patient data. The gap between standard HIPAA controls and AI-specific risks is where breaches happen.
HIPAA Compliance for AI Systems
AI systems that process PHI must meet HIPAA's technical safeguards. Most AI architectures were not designed with these constraints in mind, and retrofitting compliance is harder than building it in from the start.
Patient Data in LLM Pipelines
When patient records flow through LLM inference pipelines, de-identification gaps, prompt logging, and embedding storage create exposure points that traditional HIPAA controls do not cover.
Clinical AI Agent Security
AI agents used in clinical workflows, from triage bots to diagnostic assistants, carry unique risks. Prompt injection could alter clinical recommendations. Data leakage could expose patient histories.
Medical Device AI Validation
AI embedded in medical devices faces FDA scrutiny alongside HIPAA requirements. Security assessments must cover both the AI model behavior and the device communication layer.
How We Help
AI Security Built for Healthcare
AI Security Audits for Health Tech
Comprehensive security assessments of your healthcare AI systems. We test LLM pipelines for PHI leakage, evaluate prompt injection risks in clinical AI, and review your architecture against HIPAA technical safeguards.
HIPAA Compliance for AI Systems
Gap analysis mapping your AI architecture to HIPAA requirements. We identify where PHI enters AI pipelines, assess de-identification controls, evaluate BAA coverage for third-party AI APIs, and prepare audit-ready documentation.
Clinical AI Agent Protection
Specialized security testing for AI agents in clinical workflows. We test for prompt injection vectors that could alter medical recommendations, validate data isolation between patient sessions, and assess agent autonomy boundaries.
Healthcare AI Security FAQ
Yes. If your AI system processes, stores, or transmits protected health information (PHI), it falls under HIPAA. This includes LLMs used for clinical documentation, AI chatbots that interact with patients, and any ML model trained on patient data. The Security Rule's technical safeguards apply to the AI pipeline just as they would to any other system handling PHI.
The top risks are PHI leakage through model outputs (where an LLM inadvertently includes patient data in responses), prompt injection attacks on clinical AI agents (where malicious inputs alter medical recommendations), inadequate de-identification in training data, and uncontrolled data flows to third-party AI providers without proper BAAs in place.
Yes, but it requires specific controls. You need a Business Associate Agreement (BAA) with the API provider (both OpenAI and Anthropic offer BAA-eligible tiers), encryption for all data in transit and at rest, access controls on who can send PHI to the model, audit logging of all prompts and completions containing PHI, and a data retention policy aligned with HIPAA requirements.
A typical engagement runs 4 to 6 weeks depending on the number of AI systems in scope. This includes threat modeling, active security testing of AI endpoints, HIPAA gap analysis, and remediation guidance. We can scope a faster assessment focused on specific high-risk areas if you have an urgent compliance deadline.
We assess against HIPAA (Security Rule, Privacy Rule, and Breach Notification Rule), NIST AI RMF, OWASP LLM Top 10, and HITRUST CSF where applicable. For organizations with international operations, we also map findings to GDPR and ISO 42001. Each assessment includes a compliance mapping showing which controls satisfy which framework requirements.
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