Your pacemaker is now an endpoint. Attackers read release notes too.
Why Devices + AI Are Tricky
- Firmware–model coupling, edge inference, constrained compute, long lifetimes.
- Risks mapped in Biasin et al.’s study on AI medical device cybersecurity (arXiv).
Case in Point
The 2017 firmware recall for ~465k Abbott (St. Jude) pacemakers shows the stakes, a patch was issued to mitigate RF cybersecurity vulnerabilities (Read more).
Regulatory Overlap
- AI used for medical purposes typically lands in high-risk under the AI Act, layering obligations on top of MDR/IVDR (European Commission).
- This includes logging, robustness, and human oversight.
Secure Design Patterns
- Isolation/sandboxing
- Secure boot + model integrity checks
- Fail-safe fallback modes
- Lightweight cryptography
- Device logging & anomaly detection
- OTA updates with rollback
- Adversarial robustness testing
Ship devices with a patch plan, audit trail, and model provenance. Or don’t ship at all.
