Orca’s agentless Cloud Security Platform helps organizations quickly identify and respond to cloud attacks by continuously collecting and analyzing intelligence from cloud feeds, workloads, and configurations in a single, unified platform.
EDR, TDR, and XDR solutions only detect risks at the cloud workload level, not the control plane. For example, a stolen identity used by an outside attacker won’t be detected by workload-focused tools.
Many existing CDR tools are adapted from on-premises TDR, EDR or XDR solutions that don't offer any cloud telemetry or present blindspots due to lack of contextual insight.
Detection & Response tools require security agents to be installed for each asset.
Receive alerts when changes and anomalies occur that indicate possible malicious intent versus normal behavior, automatically prioritizing events that endanger the company’s most critical assets.
Research malicious activity to quickly gain insight into whether the events are malicious and if any of the organization’s critical assets are in danger.
Intercept cloud attacks by leveraging remediation steps and automatically assigning issues using Orca’s 20+ third-party technical integrations (including SOAR, notifications, and ticketing systems).
Orca’s SideScanning™ technology collects workload-deep intelligence and cloud configuration metadata without the blind spots, organizational friction, high TCO and performance hits of agent-based solutions.
With CDR in place, teams can closely monitor ongoing events, changes and behaviors in their public cloud environments and receive an alert if any suspicious activity is detected.
Orca offers a number of third-party integrations so you can add auto-remediation or auto assignment of issues.
Supply Chain Platform
“If you work for a company that’s in the cloud, Orca Security provides you with a robust security visibilitythat is second to none.”
Charles PoffVP of Information Security
“With Orca Security, we saw a return on investment straight away, which is unheard of with most security tooling.”