Managed Detection and Response for IT
Monitoring across the IT environment within the health system. We train our AI specifically within healthcare environments to limit false positives and increase detection sensitivity across your technology environment.
Integration across all common security technologies
AI models across network activity (Netflow, DNS, etc)
Detection of common attacks against authentication and attack patterns
Monitoring for indications of APT activity and zero day exploits.
Managed Detection and Response for Clinical/IoT
Managed Detection and Response for Clinical
Monitoring of the entire Clinical Technology environment. This includes monitoring for known threats and attacks against known vulnerabilities as well as detection of unknown threat activity.
Network threat detection
Attacks against Medical Devices and other IoT technologies found in healthcare
Attacks against medical devices and intermediary patient care sources (eg PACS)
Agentless monitoring of medical device endpoints for anomalies or compromise
Managed Detection and Response for EHR/EMR
Monitoring of EMR/EHR for behavior that creates security risk. Early detection of potential breach events as well as events that raise security risk, including:
Alert correlation with common privacy analytics technologies (e.g. Fair Warning)
Detection of common/known attack patterns
Comprehensive activity monitoring to identify anomalous use
Correlations with security telemetry to detect access from risky or compromised devices
Healthcare Security is Different.
Modern healthcare delivery organizations are faced with an increasingly connected array of digital tools - everything from medical IoT to EMR to remote worker endpoints span this interconnected environment.
Yet the security lens on the data flowing across these systems has been limited and siloed. Attackers know this, which is why more and more breaches are happening in one part of the healthcare environment and then spreading rapidly to others before they are discovered-which is often too late, particularly in ransomware attacks.