ATLANTA--(BUSINESS WIRE)--Damballa, the experts in network security monitoring, today announced the release of Failsafe 6.2 advanced threat detection platform that features new capabilities to help customers accelerate and automate threat response. Leveraging the distributed computing architecture of version 6.0 released in April 2015, the new version of Failsafe is designed to provide customers with broader visibility into threat-related network activity, enabling their security teams with new options for automating and prioritizing their response to the latest threats. Among its new capabilities, Damballa Failsafe 6.2 allows teams to more efficiently identify rogue devices connected to their network, correlate policy breaches related to network activity, label and prioritize the risk of device malware types (i.e., relatively benign to actively compromised), and transform data into actionable insights that allow an organization to reduce its risk by identifying and addressing gaps in its network policies.
“Security teams must deal with threats at a greater velocity than ever before. Consequently, it is imperative that they automate as many aspects of their response as possible in order to separate the signal from the noise,” said Stephen Newman, CTO of Damballa. “The new Failsafe uniquely combines advanced machine learning, deeper automation, and greater throughput to empower security teams to proactively respond to the most salient threats at the earliest stage in the threat lifecycle. Damballa Failsafe represents the most sophisticated threat detection platform on the market and we will continue to listen to our customers in order to deliver best-in-class innovations to this fast changing market.”
Damballa Failsafe version 6.2 includes a number of critical new features and capabilities to help detect and analyze network threats, including:
- Retroactive Analysis – Historical patterns are instrumental in helping security teams accelerate the identification of future threats. Version 6.2 provides customers with the ability to capture and analyze historical network activity from a suspected device to improve their threat response. Retroactive analysis also captures and stores full network metadata for up to seven days, providing teams with enhanced discovery as well as an option to manually query metadata to aid in their forensic investigations;
- 10 Gbps Throughput – As networks are bombarded with a higher volume of threats, the ability to ingest and process data at is a critical requirement for modern threat detection;
- Carbon Black Integration - Speed remediation by automating Carbon Black Enterprise Protection policy implementation based on Failsafe findings, including a kill process, the ability to ban and quarantine suspect binary files and machines, as well as the ability to prevent the lateral spread of infections once they have breached the network.
More information about Damballa Failsafe version 6.2 can be found at https://www.damballa.com/products-solutions/damballa-failsafe/.
About Damballa
Damballa is a network security monitoring system that provides evidence of threat-related activity needed to prevent data theft. We discover criminal operators that have already bypassed perimeter defenses and pose a business risk. Our automated system works in real-time and over time regardless of the attack vector, device type or OS. Attackers may take time to reveal themselves and when they do, Damballa will expose them and initiate mitigation. Our patented solutions leverage Big Data from one-third of the worlds Internet traffic, combined with machine learning, to automatically discover and terminate criminal activity, stop data theft, minimize business disruption, and reduce the time to response and remediation. Damballa protects any device or OS including PCs, Macs, Unix, iOS, Android, and embedded systems. Damballa protects more than 400 million endpoints globally at enterprises in every major market and for the world's largest ISP and telecommunications providers. For more information, visit www.damballa.com, or follow us on Twitter @DamballaInc.