We started ExtraHop with a bold vision: help enterprises rise above the noise of alerts, organizational silos, and runaway technology by giving security and IT teams the clarity, confidence, and agility they need to eradicate threats and seize opportunities.
An advantage to interpreting observed network traffic is that SOC analysts can respond to alerts as soon as threats give themselves away instead of struggling to piece together insights from reported log data. Reveal(x) goes a step further in characterizing affected assets by application type and value to the business to help prioritize remediation efforts. It detects threats and delivers correlated, concise investigation guidance built on cloud-based machine learning.
Eric Ogren, Senior Analyst, 451 Research
[Reveal(x)] analyzes all network interactions, applying machine learning to detect abnormal behavior, and then automates basic functions to streamline threat investigations. The launch of Reveal(x) takes ExtraHop into the network detection and response (NDR) market.
Rik Turner, Principal Analyst, Ovum
A complete data source is the starting point for successful security analytics programs. Prioritizing critical assets with insights from smart, machine learning-based network traffic analytics is a way to deliver comprehensive visibility that ultimately enables security teams to sort through the noise of threat alerts in order to detect and investigate what matters most, before critical damage is done.
Rob Bamforth, Independent Analyst