Specialized malware-detection engine secures file transfers and protocols used in EHR and PACS systems
REYKJAVIK, Iceland–(BUSINESS WIRE)–Varist today introduced its DICOM Detection Engine™, a specialized system designed to safeguard healthcare communications networks, electronic health records (EHR) and picture archiving and communication systems (PACS) used in medical imaging from malware, including AI-powered malware that employs artificial intelligence to automate, scale and customize cyberattacks. The Varist malware detection engine combines large-scale file scanning with real-time simulation of suspicious files to quickly detect and analyze emerging threats within milliseconds.
Medical imaging is vulnerable
Medical imaging environments process millions of files daily, creating a vast, often under-protected attack surface for emerging threats and AI-generated malware. Varist’s DICOM (Digital Imaging and Communications in Medicine) Detection Engine provides real-time scanning and analysis for imaging file streams, specialized protocols and ultra-large files. Along with PACS and EHR, AI-scale detection helps prevent radiology information systems (RIS) and other critical communications systems used in healthcare from becoming vectors for malware.
“A picture is worth a thousand words, especially when lives depend on it, and threat actors may be looking to use that to their advantage,” says Varist CTO Siggi Petursson. “Varist’s specialized detection for healthcare environments finds new self-evolving threats designed to evade detection by conventional systems, without adding delays or compromising patients’ care and privacy.”
Picture-perfect detection for medical imaging
As the universal standard for medical imaging files, PACS relies on specialized protocols and formats to enable interoperability across imaging modalities such as X-rays, CT and PET scans, MRIs, and ultrasounds. Varist’s DICOM Detection Engine fills security gaps left by conventional scanning and sandboxing, detecting known and unknown threats, including malware that attempts to leverage life-critical images.
Highlights of the Varist DICOM Engine include:
- Dedicated detection engines for DICOM, HL7 and FHIR, three formats used in PACS and EHR platforms.
- Hyperscale DICOM header analysis to find headers modified to turn imaging files into executables that deliver malicious payloads.
- Full-file scanning, including large medical images (such as MRIs) up to 3GB. Varist finds threats anywhere within the file, including image data regions that conventional scanners ignore.
- Predictive payload detection simulates the behaviors of suspicious files to enable zero-day detection of novel DICOM exploits that have not yet been cataloged in malware signature databases.
- Privacy that aligns with compliance and cyber insurance requirements: Organizations that integrate Varist technology can scan and analyze files locally without uploading them to public cloud infrastructures
Highlights of the Varist Hybrid Detection Engine
Varist’s hybrid approach raises the bar for modern malware detection:
- Each HDE instance processes ~500 files per second
- Suspicious files are analyzed in under 9ms (1000x faster than sandboxes) with a false positive rate of less than 0.001%
- The Varist architecture scales horizontally to match the demands of large, multi-site networks and multi-cloud deployments
About Varist
Varist (varist.com) is a cybersecurity innovator delivering AI‑scale malware detection through its advanced Hybrid Detection Engine™, which identifies both known and zero‑day threats in real time and at hyperscale. Leveraging technology proven to perform over 500 billion file scans per day, Varist combines predictive detection, real‑time simulation and ultra-low false positive rates to help enterprises and OEM partners counter increasingly complex, AI‑powered threats. Its hybrid approach — scanning every file, simulating suspicious behavior, and assigning automated risk scores — enables organizations to stop threats earlier, reduce operational burden and secure environments at global scale.
Contacts
Media Contact
Sara Delacruz
[email protected]
