Application owners quickly learn the intended state of their distributed application environment and exposure risk. Edgewise automatically identifies trusted entities communicating in the environment, including the software, users, and hosts. The machine learning systems build immutable cryptographic identities by collecting and analyzing data from many sources including its agents and DevSecOps toolchains. Edgewise then maps the application topology based on communication pathways between application workloads. Using this topology, Edgewise measures exposure risk and analyzes attack paths to present a clear picture to application owners of overly exposed application pathways that are not needed by the business.
The Edgewise PolicyGraph Engine uses the principle of least privilege and automatically builds the optimal policy set based on the application topology model. Policies are based on application workload communication patterns, making them more accurate, portable, and efficient in contrast to traditional address-based policies. Operations teams gain the broadest protection coverage with the fewest number of policies. The application-centric policies described in plain English enable application owners and DevOps to more effectively collaborate and protect business applications. One click is all it take to apply the policies and receive proof of correctness.
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.