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The healthcare industry continues to face mounting pressure to protect sensitive data-driven by a rapidly expanding digital ecosystem and strict compliance mandates. But beneath the surface of daily operations, what really puts patient data at risk? And more importantly, what actually works to reduce that risk?
Cyera Research Labs-the data and cybersecurity research arm of Cyera-analyzed real-world environments across the healthcare sector, looking into peta bytes of healthcare related, anonymized, aggregated telemetry collected through the Cyera platform. This research provides a rare, ground-truth view into the most common data exposures and the most effective tactics organizations are using to fix them.
🔍 Note: All insights are drawn from anonymized metadata and behavioral patterns. No customer-specific, sensitive, or identifiable data was accessed in the analysis.
The findings show that while risks are real and widespread, leading organizations are actively addressing them-proving that prevention at scale is possible.
Even today, massive volumes of sensitive data-credit card numbers, PHI, identity details-remain stored in plain text across cloud and on-prem systems. Some of the most affected repositories involved:
In many cases, the presence of sensitive data wasn't due to negligence-but a lack of automated classification and enforcement.
Production datasets are often copied into non-production systems for testing, analytics, or performance tuning. But in these environments, encryption, access control, and visibility are often weaker-and risk skyrockets.
This practice remains one of the most common (and solvable) exposure patterns.
A frequent high-severity risk was observed in files containing sensitive data shared externally via collaboration platforms-like Microsoft 365 or Google Drive. In many cases:
Organizations that applied automated remediation policies and integrated risk signals into their operations showed consistent success in reducing exposure. These teams weren’t just seeing the risk-they were closing it.
That’s what separates detection from defense.
These aren’t guesses. These are the top patterns that worked in real environments:
Organizations that led in risk reduction had one thing in common: encryption was the default, not an afterthought. They:
📌 This eliminated entire categories of preventable exposure, especially in cloud-hosted environments.
Unmanaged file sharing was one of the most recurring and preventable risks. Leading orgs automated:
📌 Rather than block productivity, these policies ensured secure collaboration-without manual policing.
Data classification systems flagged dozens of cases where production-grade data had leaked into dev/test environments. Where remediation was successful, orgs had:
📌 This approach protected developer workflows-while closing one of the most invisible backdoors to patient and financial data.
While the data revealed strong examples of effective governance, several issues remain consistently unaddressed:
Cloud buckets remain misconfigured-granting open or excessive access to sensitive storage
In short: the problems haven’t changed-but the solutions have become much more accessible.
Organizations that successfully reduce risk do not rely on periodic audits or hope. They:
This is where Cyera delivers real operational impact-by not just showing security teams what’s wrong, but helping them fix it.
Healthcare security isn’t about stopping every incident-it’s about eliminating the most systemic, scalable risks before they spread. The data shows that while exposure is common, so is progress.
Cyera Research Labs will continue publishing anonymized, pattern-based insights to help healthcare CISOs and security leaders benchmark their posture and drive change-quietly, constructively, and effectively.
Because when data is protected properly, care can be delivered with confidence.
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