CATO Networks

Cyber Security, Enterprise, Network
Artificial Intelligence Machine Learning

Business Overview

Cato is the world’s first SASE platform, converging SD-WAN and network security into a global, cloud-native service. Cato optimizes and secures application access for all users and locations. Using Cato, customers easily migrate from MPLS to SD-WAN, optimize connectivity to on-premises and cloud applications, enable secure branch Internet access everywhere, seamlessly integrate cloud datacenters into the network, and connect mobile users with Cato SDP all with a zero-trust architecture.

Operating Status
January 2015
Business model
Offering type
Funding stage
Series E
Business stage
Revenue status
Revenue Generating
Total funding
$332 Million
Cyber Security, Enterprise, Network, Software Defined (SD), Threat Intelligence, Wide Area Network (WAN)


CATO Networks
Gur Shatz
COO and President
CATO Networks
Shlomo Kramer
Serial Entrepreneur

Board Members and Advisors

CATO Networks
Yoni Cheifetz
Board Member
CATO Networks
Jerry Chen
Board Member
CATO Networks
Theresia Gouw
Board Member
CATO Networks
Steven Krausz
Board Member
CATO Networks
Gur Shatz
Board Member
CATO Networks
Shlomo Kramer
Board Member

Funding Rounds

New wpDataTable

Date Announced

Funding Round

Amount Raised


AI Technology Stack

AI Description

Cato’s reputation assessment system eliminates false positives in threat intelligence feeds by leveraging the convergence of security and networking information in its SASE platform. Cato ingests more than 5 million IoCs from nearly 200 open source and commercial threat intelligence sources. IoCs are then scored, and false positives are identified and eliminated using real-time network intelligence gathered by machine-learning models mining Cato’s comprehensive data warehouse of SASE flow metadata.

Cato’s proprietary machine-learning models crowdsource IoC verification by:

  • Building a comprehensive reputation profile for each IoC. Cato builds a profile of each IoC from the record’s metadata, such as when the IoC was last reported, the number of user flows destined for this IoC, and the number of threat intelligence feeds reporting the same IoC.
  • Predicting false positives. With a profile built for each IoC, Cato’s reputation assessment system simulates hits on the IoCs with the worst reputation, utilizing network traffic from its cloud-based network.
  • Automatically removing false positives: Once identified, Cato automatically removes false positives from the security feeds and updates Cato’s global IPS, keeping the customer’s security posture current and free from false positives.
AI types
Artificial Intelligence, Machine Learning

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