The first step in speeding up microsegmentation projects is to understand how applications communicate and quantify their network attack surface. Edgewise automatically maps application topologies to reveal how applications communicate and then highlights potential pathways of attack within the network. This application-centric view helps defenders gain a clear picture of the applications they need to protect and prioritize based on exposure risk.
Edgewise uses machine learning to build the smallest number of policies that provide the broadest protection coverage (up to 99.99% of observed communications). The machine learning system quantifies the reduction in network attack surface and exposure risk realized by applying Edgewise policies. Edgewise produces plain-English policies, making it easy for application owners, security operations, and networking teams to collaborate more easily—no need to translate “application speak” to “network speak.”
Stop lateral movement of malicious software that bypasses firewalls. Lock down your cloud and allow only verified applications to communicate over approved pathways. Receive alerts for any anomalous communication.
As much as 95% of network pathways are not required for normal business use. Eliminate unneeded application communication paths and protect the rest by mutually validating connections before a single packet is sent.
Apply workload protection policies in minutes, not days or months. Quickly approve machine-learned and automatically-built policy recommendations.