Hybrid Detection Engine™ detects previously unseen threats in real time and cuts costs compared to traditional sandboxing
Varist launched its Hybrid Detection Engine™, creating the first AI-scale malware detection solution that finds both known and zero-day threats instantly at scale. Built on proven technology used to perform more than 500 billion file scans per day for global customers, the Varist solution surpasses conventional detection by scanning every file and simulating suspicious components in real time. By combining unknown threat detection, lower costs and hyperscale scanning, the Varist Hybrid Detection Engine meets the exponentially growing data demands of hyperscalers and cybersecurity providers.
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Varist’s hybrid approach delivers the essential components of an AI-scale solution:
- Scan every file at hyperscale, with each instance processing approximately 500 files per second
- Simulate threats 1,000 times faster than conventional sandboxes while keeping costs low
- Deliver detection efficacy with less than 0.001% false positives
- Analyze suspicious files in under nine milliseconds
- Protect at scale: safeguarding five billion mailboxes worldwide through OEM partners
“Traditional methods for detecting unknown malware assume no solution can scale to scan every file and that conventional sandboxing is too slow and too costly to execute against every potential threat,” says Varist founder Hallgrímur Th. Björnsson. “Agentic AI creates complex, self-evolving threats, so providers need a more scalable and cost-effective way to find known and zero-day threats, without bombarding response teams with false positives.”
Leveraging a malware dataset of over 3 petabytes, Varist delivers fast, accurate detection of known and zero-day threats at the edge to reduce the overall volume of malware threats entering an organization’s environment. The Hybrid Detection Engine simulates behavior in real-world environments and assigns risk ratings to help responders prioritize investigations.
The Need for a Hyperscale Approach
File-centric workflows hide malware throughout legitimate traffic. Traditional signature-based tools and sandboxes cannot manage the volume of threats or their sophistication. The Hybrid Detection Engine performs inspection and simulation on every file while it is in motion and without interrupting business processes. It provides automated risk scoring so teams can stop threats, reduce false positives and keep systems safe against AI-assisted malware.
“The increased use of and potential for AI to create and execute malware campaigns could completely overwhelm conventional detection systems sooner rather than later,” says Mike Fleck, a 20-year cybersecurity industry veteran. “Security stacks will not only need to detect known threats at greater scale, but also detect novel threats in near real-time.”
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