Are the Kids Okay? Securing Healthcare’s LLMs as They Mature

Ghosts are just hacks waiting to happen

Large language models (LLMs) are the toddlers of healthcare innovation, curious, fast-learning, occasionally unpredictable, and increasingly integrated into the family (i.e., your EHR, patient portals, and diagnostic tools). But just like actual kids, they’re vulnerable. And while most of us are still figuring out how to harness their potential, bad actors are already planning how to exploit them.

Let’s talk plainly. LLMs aren’t ready to be left home alone, especially not in healthcare.

Why LLMs in Healthcare Are a Hacker’s Dream

Healthcare data is the holy grail of cybercrime: full names, birth dates, social security numbers, and complete medical histories. Now, add a model trained on that information that makes decisions or assists with diagnostics, and what do you get? A target worth every malicious byte.

Adding a decision-making or diagnostic model to that information creates a highly valuable target for malicious cyber activity. This makes the system extremely vulnerable to attack, as it holds sensitive data that could be used for harmful purposes.

Because it contains confidential information easily exploited for malicious activities, this system is particularly susceptible to breaches.