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XDR vs SIEM: A Technical Comparison

Mark Stone
XDR vs SIEM: A Technical Comparison

For decades, organizational risk due to emerging threats has been significant. But as the threat landscape escalates and hackers ramp up their game with new attack methods, security teams must mitigate the threat with new solutions for detection and response.

Today, the complexity surrounding detection and response can be overwhelming. Solutions marketed to overcome these burgeoning threats are countless: SIEMs, endpoint detection and response (EDR), network detection and response (NDR), managed detection and response (MDR) and more. While each solution can address the challenges, combining them presents its own challenge.

Enter extended detection and response (XDR). What is it, why is it becoming more popular, and how does it compare with SIEM? 

Defining extended detection and response 

Extended detection and response (XDR) refers to a cybersecurity strategy that brings detection, investigation and response with end-to-end visibility across multiple security layers.

XDR is an emerging methodology that focuses on strengthening cyber defenders’ fundamental skills to protect against this type of sophisticated attack by detecting, containing, and responding to unknown cyber attacks. It is a strategy that offers broad protection against today’s sophisticated cyber attacks, including malware infections, system breaches, ransomware encryption, data theft or modification, and more. 

Some of the primary benefits of XDR are reducing product sprawl, curtailing alert fatigue, and addressing integration challenges that increase operational expense. For security operations teams that are handicapped by maintaining a handful of best-of-breed solutions or aren’t gaining enough insight from a traditional SIEM or SOAR solution, XDR can be very practical. 

Comparing XDR with SIEM 

There are several key differences to be aware of between XDR and SIEM solutions.

First, XDR is a reactive system while SIEM is proactive. Second, XDR’s primary functionality is event logging, while SIEM is for alerting, correlation, and post-event analysis. Next, SIEMs collect data from all devices within an environment, whereas XDR only collects data from devices within an organization’s network. 

Digging a little deeper, the goal of XDR is to identify, investigate and take proper action to resolve incidents efficiently and quickly. Today’s modern SIEM essentially serves the same purpose but can also be leveraged for compliance monitoring, retention and reporting.  

Also, the function of XDR is not intended for satisfying compliance mandates in the same way as today’s modern SIEM. While both XDR and SIEM rely on logs, XDR platforms are not as reliant on them as evolved SIEM platforms.  

For compliance purposes, modern SIEM solutions typically incur more throughput costs than XDR platforms. 

However, the use cases for XDRs rarely go beyond threat detection and incident response. Organizations that need to integrate more log types or meet regulatory log retention requirements will still need a SIEM. 

Ultimately, XDR vendors are touting their solutions as the next-gen SIEM — boasting a better, faster and cheaper product. But both XDR and the modern SIEM are relatively new in the marketplace, and organizations can succeed with either product.

The right tool for your organization depends on your organizational requirements.

Why XDR is next big thing in threat detection 

Traditional approaches are not as practical for detecting malware and exploits because they detect threats at a single point of view, such as the file level or the network level. However, XDR detects threats at all levels simultaneously. XDR leverages data from across the entire system, including every module and process running on that system. Typically, it provides the highest detection rates of all known malware and antivirus products.

But where XDR really shines is its ability to improve security operations capability and operational security staff productivity. 

Benefits for security operations include: 

  • Threat intelligence sharing between various security solutions so threats can be efficiently blocked across all components
  • Leveraging reliable external threat intelligence for detection methods surrounding cloud, network, endpoint, web, and email
  • Reducing missed alerts by correlating and confirming alerts automatically
  • Combining weak signals from multiple components into stronger malicious threat signals
  • Speeding up alert triage and improving alert accuracy with more relevant data
  • Providing centralized configuration with weighted guidance to help prioritize actions 

When it comes to operational security staff productivity, XDR can reduce training time to get up to speed on completing operational tasks with a unified management and workflow experience across multiple security components. Out of the box, a robust XDR solution provides usable and effective detection with little fine-tuning required. Typically, it will leverage the MITRE ATT&CK framework for threat classifications/visualizations and should be able to respond automatically to known events.

How the data lake factors into the XDR concept

With the rise of big data, organizations can now leverage their data for strategic decision-making. The availability of not only structured data but also unstructured data has driven the need for a solution that can accept, store, and process it all. A data lake is an organization’s storage repository for its raw data. The primary goal of a data lake is to make data easier to manage, share, and use. 

Data lakes are great for analytics applications because the data is stored in different structures and formats to make it easier to mine for patterns or insights that arise from shrewd attackers who exploit gaps in security siloes. Because if an attacker can slip between an organization’s siloed products, they can move laterally, dwell on your network, collect payloads, and prepare for future attacks as they learn about the network’s defenses.

The XDR-data lake process goes like this: it collects data from all the layers, feeds the results into a data lake, sterilizes it, then correlates the data to the penetrated attack surface. The data is centralized, normalized and is typically made accessible and manageable through a single pane of glass.

How Panther fits into the XDR space

XDR is a vague and evolving space. Despite their differences, next-gen SIEM is often included in the marketplace where XDR is trying to innovate. But Panther’s next-gen SIEM technology is already doing a lot of what the market expects XDR to do. Still, security teams should consider leveraging a combination of a next-gen SIEM like Panther and an XDR, with XDR acting as the “reaction” arm and Panther as the source of truth. 

The market demand is simple: companies want a faster, more scalable, cloud-native solution that can bring all of their disparate security data together. Panther delivers on that need with a single pane of glass security solution built for the cloud.

With Panther, you can build your security data lake, maintaining strong security as your data volumes grow exponentially. Panther is a petabyte-scale security analytics platform that operationalizes massive volumes of data for teams to identify suspicious activity and prevent breaches.

With Panther, you can collect and scale your security logs, analyze them with Python, generate alerts in real-time, and build a scalable security data lake in AWS or Snowflake. Its modular and open approach offers easy integration and flexible detections to help you build a modern security operations pipeline.

Learn more about how Panther’s platform works or request a demo today to explore how Panther can help your organization overcome the challenges of threat detection and response.