XDR collects telemetry from what would otherwise be multiple silos of data, using a local agent that effectively serves as a security information and event management (SIEM) solution, among other functions. XDR identifies malware and advanced threats, and then takes various steps to prioritize, contain, and eliminate them using the power of machine learning (ML) and automation.
To accomplish this, XDR continuously performs three core functions:
The solution collects data across servers, endpoints, clouds, and other parts of the ecosystem, correlates that data, and sends only relevant, important alerts to the organization’s security team, helping to minimize alert fatigue.
Taking advantage of its wide and deep visibility, XDR uses ML to establish a baseline of normal user and entity behavior. Layered with other detection mechanisms, this allows the XDR solution to investigate anomalies that could indicate security threats.
XDR isolates and eliminates a threat, and then updates security policies to stop that threat in the future. Where it goes beyond EDR is in consolidating security operations center (SOC) resources across network, endpoint, and cloud environments in one console.
XDR unifies detection and response capabilities across an entire data environment, enabling it to go beyond traditional security products and point solutions to offer greater coverage and a more complete picture of security incidents. An effective XDR platform provides:
XDR supports three primary use cases:
With the sheer volume of threats targeting today’s enterprise networks, even the most skilled security professionals can’t keep up with the alerts, let alone quickly and accurately sort out the false positives, prioritize the most critical threats, and respond. XDR uses ML and advanced analytics to refine threat data from the entire ecosystem into a manageable number of high-quality alerts.
Today’s sophisticated threats are extremely good at hiding, making threat hunting both more important and more difficult than ever. Because XDR offers visibility into your entire ecosystem alongside ML-powered detection and correlation, it can pinpoint threats that traditional SIEM solutions alone will miss.
XDR solutions provide rich context to support root cause analysis, including real-time and historical data, helping your security team understand what happened in an attack and what it will take to stop similar attacks in the future.
With detection and automated response technologies, businesses can continually monitor systems to detect, investigate, and contain threats in network and application traffic as they arise. Using machine learning and automation technologies, XDR can prioritize, contain, and remove those threats in real time.
Other detection and response technologies include:
Endpoint detection and response (EDR), which can identify, prioritize, and respond to malware and advanced threats on endpoints and in workloads, but lacks visibility across the rest of the ecosystem.
Network detection and response (NDR), which focuses its response capabilities on attacks that hide in network traffic and attempt to evade network firewalls.
Managed detection and response (MDR), which relies on services provided by a team of third-party security analysts, rather than your own personnel.
NDR and EDR were revolutions in the realms of network and endpoint security at one time, but today’s complex, multilayered data ecosystems call for more coordinated visibility and analytics, alongside greater accuracy and speed, to keep up with the volume and sophisticated techniques of modern cyberattacks.
Like any relatively new technology, there are a lot of different perspectives out there on what defines extended detection and response. What exactly makes XDR? At its core, XDR is:
If your organization is looking to implement zero trust—or hone your existing zero trust architecture—you’d do well to add XDR to your cloud-delivered security stack to take full advantage of:
Zscaler integrates with industry-leading partners to combine the cloud native Zscaler Zero Trust Exchange™ platform with the power of XDR. Using advanced AI/ML, our XDR alliances provide high-fidelity threat intelligence and context for faster, more effective detection and response across platforms, enabling end-to-end visibility.
The Zscaler Zero Trust Exchange™ is a cloud native platform built on zero trust. Based on the principle of least privilege, it establishes trust through context, such as a user’s location, their device’s security posture, the content being exchanged, and the application being requested. Once trust is established, your employees get fast, reliable connections—wherever they are—without ever being placed directly on your network. The Zero Trust Exchange operates across 150 data centers worldwide, ensuring that the service is close to your users, colocated with the cloud providers and applications they are accessing. It guarantees the shortest path between your users and their destinations, providing comprehensive security and an amazing user experience.
Endpoint detection and response provides continuous monitoring and detection of endpoint data and uses an automated response to prioritize and contain threats.
While EDR focuses only on endpoint detection and protection, XDR provides monitoring, detection, and resolution across all security control points, including email, clouds, networks, and servers.
Both XDR and security information and event management (SIEM) solutions pull threat data from multiple sources. However, XDR makes use of advanced security measures, whereas SIEMs are limited to pushing security alerts to SOCs. XDR can proactively adjust network and endpoint defenses to neutralize threats while also notifying SOCs.
XDR is a highly sophisticated way to monitor and detect threats in real time, using automation to filter out the most important issues and lighten the load on security teams.