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Cloud detection and response: CDR vs. EDR vs. NDR vs. XDR
Cloud detection and response is the latest detection and response tool. Explore how it differs from endpoint, network and extended detection and response tools.
The cybersecurity field has more abbreviations than ever, further highlighting the complexity and growth of the IT landscape as it expands between on-premises and cloud environments.
The threat detection and response (TDR) category of tools has seen significant growth with the emergence of endpoint detection and response (EDR), which focuses on workloads; network detection and response (NDR), which assists with network activity; and extended detection and response (XDR), which evolves both EDR and NDR and includes SIEM capabilities.
Now up to bat is cloud detection and response (CDR), which shifts TDR tools into the cloud to combat suspicious and malicious activities, including malware, credential theft, insider threats and more.
How CDR differs from EDR, NDR and XDR
CDR includes some elements of EDR, NDR and XDR but with a focus on cloud threats. The most significant difference between CDR and the other three is reliance on the cloud fabric itself, which provides a guardrail of automated, software-based security control applications.
One of the hallmarks of CDR is automation through cloud provider services and APIs. CDR also focuses on large-scale event processing and automated risk analysis through machine learning and analytics.
The following are other key differences between CDR and other TDR options:
- Comprehensive focus. CDR encompasses all aspects of cloud security visibility to facilitate detection and response across an interconnected cloud fabric. To this end, CDR is most similar to XDR, which incorporates EDR and NDR with SIEM to provide a more thorough range of detection and response capabilities and controls. CDR includes cloud workloads of all types -- VMs, containers and serverless -- as well as cloud networking, storage nodes and more.
- Automated detection and response. The cloud, as a software-defined infrastructure, has many APIs available and opportunities to automate detection and response capabilities. CDR continuously evaluates network traffic and workload events in real time, sending alerts to a central console. CDR can trigger automated response actions to quarantine workloads, adapt network access controls, isolate assets and network zones, and even tear down and rebuild workloads from approved images.
- Cloud-centric risk monitoring and reporting. The cloud offers innumerable configuration options and controls, which are often easily misconfigured and attacked. CDR continuously evaluates the configuration of the cloud itself -- beyond just assets deployed there -- to provide up-to-date reporting on risks that stem from poorly configured services and assets.
- Cloud-specific workload protection. In traditional data centers, EDR primarily focuses on physical and virtual endpoints and servers. In the cloud, workloads can be VMs, containers or serverless, meaning attack surfaces and patterns differ from traditional on-premises infrastructure models. CDR tools accommodate these workload models to detect cloud-specific attack patterns, such as identity and access management privilege escalation, abuse of cloud APIs and more.
- Cloud big data processing. One common challenge with cloud event management is the sheer quantity of data produced and how to manage and sift through it. Using machine learning models, CDR platforms and services cull less relevant data and correlate the most important information to provide insights into cloud attacks. Given the velocity of cloud changes and deployments, CDR services should be capable of rapid analysis and alerting, too.
In many ways, CDR reflects a combination of other TDR services, but cloud is a different environment that demands a different level of focus on visibility and API-driven automation. Accordingly, those are the key differences in CDR vs. EDR, NDR and XDR.
Dave Shackleford is founder and principal consultant with Voodoo Security; SANS analyst, instructor and course author; and GIAC technical director.
