< + > AI Deception is Reshaping Healthcare Security

The following is a guest article by Sandy Kronenberg, Founder and CEO at Netarx

From Falsified Diagnostics to Cloned Physicians, Deepfakes are Exposing Gaps in Traditional Defenses and Demanding Urgent Executive Action

Healthcare is facing a new category of cyber risk. Deepfakes, AI-generated audio, video, and images, are moving from social media into clinical systems, telehealth visits, and patient communications. Unlike malware, they do not rely on code that can be scanned or quarantined. Their power comes from exploiting human trust.

For CISOs and IT leaders, this threat reaches beyond infrastructure. A falsified medical image can misguide a diagnosis. A cloned physician’s voice can unlock access to sensitive systems. A fabricated video of a public health official can circulate misinformation at scale. These are not speculative scenarios. The tools exist, the barriers to entry are low, and the healthcare sector is already a target.

Training Alone Won’t Stop the Threat

At UC San Diego Health, nearly 20,000 employees completed cybersecurity awareness training. Yet a recent study revealed that many still fell victim to phishing simulations, underscoring how training alone often fails when real-world deception arrives at scale. This is more than a lesson about phishing; it is a warning about the limits of human vigilance. As healthcare moves online, the next wave of deception will not come through suspicious emails, but through convincing synthetic voices, manipulated scans, and fabricated video consults.

Why Healthcare Is Especially Vulnerable

Deepfakes pose a growing risk to hospitals, insurers, and patients alike. In healthcare, the stakes are life-and-death. A falsified CT scan could lead to unnecessary surgery. A cloned physician’s voice might trick staff into disclosing credentials. A synthetic video of a public health official could spread misinformation to millions. Trust, the bedrock of care, is suddenly fragile.

Recent research illustrates how close this danger is. In one study, attackers used generative adversarial networks to alter CT scans, inserting or removing signs of disease. Radiologists and machine-learning diagnostic tools alike were fooled. Another analysis in Frontiers in Public Health noted that while deepfakes can enrich training datasets for AI, they simultaneously open dangerous doors for fraud and ethical misuse. What makes the threat especially insidious is accessibility: just a few seconds of a doctor’s voice from a webinar or press briefing can generate a convincing clone capable of issuing fraudulent orders in a clinical setting.

Gaps in Traditional Defenses

Healthcare’s existing defenses are ill-prepared for this new reality. Identity Threat Detection and Response (ITDR), endpoint protection, and multi-factor authentication remain essential for combating malware and credential misuse, but they are not designed to spot a synthetic face on a telemedicine call or an altered MRI file in an imaging system. These tools operate at the system or network level, while deepfakes exploit something more human: our instinct to believe what looks and sounds real.

Advances in Detection Research

Detection research is advancing, but the challenge is formidable. New frameworks such as DProm use visual prompt tuning with pre-trained models to adapt to evolving manipulations, offering more robust detection across diverse datasets. 

Other approaches rely on ensembles of detection models, where multiple algorithms analyze the same input and combine results to improve accuracy. Cryptographic provenance, digital watermarking, or blockchain-based signing of medical records and images is also gaining traction to ensure that what clinicians see has not been tampered with. Whatever the technique, the consensus is clear: detection must happen in real time, in the flow of care, not after an incident is reported.

What CISOs and IT Leaders Must Do

For healthcare CISOs, this creates both a technical and a governance challenge. Security architectures must expand beyond traditional boundaries to include deepfake detection inside electronic health records, imaging systems, and telemedicine platforms. Incident response plans should consist of scenarios where a doctor’s voice or a patient’s scan is fraudulent. 

Staff training should move beyond phishing awareness to structured verification protocols for unexpected requests, even those appearing to come from trusted voices. Awareness alone is not enough, but awareness paired with clear processes can reduce blind trust.

The regulatory environment also lags behind. HIPAA and FDA frameworks focus on privacy and device integrity, but have not yet been adapted to synthetic media threats. Healthcare organizations that move early by implementing provenance checks and real-time media validation will not only reduce risk but also help shape emerging standards. Waiting for policy to catch up risks leaving guidance to be written after a crisis rather than before.

The Urgency of Trust 

What makes the deepfake problem uniquely urgent in healthcare is the centrality of trust. In banking, fraud is measured in dollars. In healthcare, it can be measured in misdiagnoses, mistreatment, or public loss of confidence in providers. Once patients begin to question whether their records, scans, or even their clinicians are genuine, the system risks a collapse of credibility.

That is why leadership action cannot wait. Executives should treat deepfake detection as a core part of identity and access strategy, not a peripheral concern. They should ensure that synthetic media risks appear on risk registers and board reports alongside ransomware and insider threats. And they should push for collaboration across hospitals, insurers, and regulators, recognizing that no single organization can solve this alone.

Attackers already possess the tools. They are using voice clones and synthetic videos to defraud organizations across industries. Healthcare, with its reliance on trust and its wealth of sensitive data, is among the most attractive targets. The question facing healthcare leaders is not whether deepfakes will arrive in their systems, but whether their defenses will be ready when they do. The time for action is now. Protect your patients. Protect your data. Above all, protect the trust on which healthcare depends.

About Sandy Kronenberg

Sandy Kronenberg is the CEO at Netarx and has more than two decades of experience helping organizations strengthen their cybersecurity posture. He writes frequently about the intersection of artificial intelligence, digital identity, and organizational resilience, with a focus on how technology leaders can adapt to emerging threats.