My experience with Orca Security is recent, as I used it about two months back while still in the previous organization, and I have recently switched jobs. In my opinion, the best features of Orca Security are that it is very easy to deploy, primarily because it does not have agents, which are used in many other SIEM solutions or security solutions such as SentinelOne, Sentinel, Wazuh, or AlienVault. Those benefits include faster onboarding and reduced alert noise via intelligent prioritization. It also has better DevSecOps integrations with code scanning and SDLC visibility. The main advantages are that it is easy to set up with user-friendly dashboards, and the agentless design reduces operational friction. It also offers excellent visibility and exhaustive scanning of the cloud accounts, and Orca Security can be used on any cloud platform, whether it is AWS, Azure, GCP, or Oracle. Using Orca Sensors has been beneficial since by default, Orca Security's cloud platform employs a side-scanning technology that connects cloud accounts via APIs. It offers workload block storage without needing to deploy a traditional agent on each workload. Orca Sensor is a lightweight sensor designed to supplement the agentless platform with runtime visibility. It uses EBPF for deep system-level observability, making it easy to deploy. The reason we use Orca Sensor is that it provides broad cloud-wide visibility and prioritized risk. Orca Sensor adds real-time monitoring and detects malicious behavior similar to other SIEM products. By using Orca Sensor, we can confirm if potential vulnerable code is executed in runtime. There are many features for Orca Sensors, as it fits into an agentless model, is easy to deploy via cloud APIs, and offers deep, real-time processing and network visibility. Providing runtime visibility with Orca Sensor has been effective, as it complements Orca Security's core platform, which uses agentless side-scanning. This allows us to see what processes are running and detect real-time threats such as malware execution or privilege escalation. The hybrid approach lets organizations maintain agentless coverage for the entire cloud estate while applying deep runtime protection to critical workloads. Prioritizing risks using Orca Security is generally easy and effective, especially compared to other tools I have used such as SentinelOne and Sentinel. Orca Security provides a risk score for everything, including attack path visualization and business impact context. This helps us propose risks while correlating multiple signals such as common CVEs and cloud misconfigurations. For example, a public EC2 instance with an admin IAM role running malicious scripts could be a critical risk. Compared to other cybersecurity tools, Orca Security's agentless architecture enhances its risk prioritization capabilities. I have not seen many alerts in Orca Security during my tenure since the architecture was well-structured by our cybersecurity architect, leading to very few alerts. Some alerts were related to possibly malicious activity installed by our team or older versions of Java. However, I believe that Orca Security reduces alert volume because it combines vulnerability data into a unified view, speeding up cloud security workflow. It significantly reduces alert noise and accelerates alert handling by correlating risks with workloads, showing prioritized issues so the team can focus on remediation.
