Even though XDR systems made their debut several years ago, they continue to provoke questions from clients and cybersecurity experts. Is this truly a novel approach, or is it merely a marketing tactic designed to repackage familiar cybersecurity tools and sell them to customers?
What Is XDR?
XDR is a single-vendor SaaS solution that integrates sensor-based information security subsystems, event correlation and advanced response capabilities, as well as the expertise required to weave all these elements into a cohesive system. XDR represents a fresh perspective on centralized control within the realm of information security.
This article will delve into the nature of extended detection and response, commonly known as XDR, investigate how XDR solutions interact with security tools and explore specific considerations when using XDR.
XDR: Basic Concepts
Two decades ago, XDR was all about gathering events and managing updates within a specific system. A few years back, XDR the strategy expanded to include the integration of indicators of compromise (IoC). Today that is not enough. It is crucial to gather and process all security-related information centrally. This holistic approach is key to identifying incidents that might not be evident on a singular endpoint.
The term XDR is closely related to endpoint detection and response (EDR), and many vendors have adopted this methodology in developing their solutions. Nowadays, customers are looking for XDR to embody features of SIEM systems, SOAR and NDR as well as the inclusion of behavioral analysis and machine learning. The XDR concept has gained widespread appeal, and it is starting to encompass other facets of information security, extending even to the zero trust paradigm.
XDR refers to an automated solution pre-equipped with detection capabilities and predefined detection rules. This operational logic is both designed and updated by the vendor. SIEM or SOAR components primarily function as building blocks, which the customer uses to create a customized solution.
The XDR concept can be broadly split into two primary components. The front end consists of sensors, modules and products situated around the perimeter, tasked with data collection. The back end comprises user behavior analytics (UBA), machine learning and deep analytics, as well as static and dynamic rule sets.
XDR Advantages
XDR eases the burden on cybersecurity professionals and lessens the impact of human error. The extended detection and response system can swiftly identify a cyberattack, thereby reducing the damage. It can potentially reduce system maintenance costs, as operating a single solution tends to be more cost-effective than managing an array of individual products from multiple vendors.
All the features that SOAR and SIEM manufacturers promise their clients, XDR provides right out of the box. XDR systems are inherently designed to operate via APIs; thus, unlike SIEM, are not based on data correlation, but rather on data enrichment with the help of various sources like threat hunting, indicators of compromise, OSINT data, etc.
Primarily, XDR eases the burden on cybersecurity professionals and lessens the impact of human error.
When it comes to SOAR, these systems evolved from incident response platform (IRP) solutions with added automation features. SOAR systems rely on detection-centric systems, processing the data they receive. When purchasing a standalone SOAR solution, customers have to independently craft usage scenarios and customize the system’s response to externally received data.
In contrast, XDR autonomously identifies incidents and determines the appropriate response, all within a single system.
Rather than gathering security events, XDR collects telemetry from endpoints, pinpointing incidents within a large array of data that would not be detectable on a single host. This method significantly reduces the number of false positives, as the XDR core can analyze data from various system nodes.
XDR Implementations
XDR systems can be delivered in various forms. A vendor restricting itself to only cloud-based or solely on-premises solutions might miss out on potential customers. It is important to note that XDR processes vast quantities of data, necessitating substantial computational resources that are challenging to provide within a single company’s infrastructure. From this perspective, cloud-based systems are advancing more quickly and appear to be a more favorable option.
Detection and Response Mechanisms Used in XDR
The bulk of detection in XDR occurs through analyzing the telemetry from endpoint devices. Here are a few examples of such detection techniques:
- Searching for indicators of compromise
- Identifying attack patterns
- Information derived from sandbox environments
- Incident data from third-party systems
- A neural network that emulates the actions of a security operations center (SOC) employee
The arsenal of response scenarios and tools in contemporary XDR solutions can encompass actions like terminating a process on the endpoint, isolating it, reverting the changes it made to the system. On the firewall front, the attacked host is typically added to a block list. In response to dubious user activities, the user’s account may be blocked, or additional authentication measures may be applied to the account.
Moreover, customized scenarios developed through specially created scripts are also possible. Another possibility includes evidence gathering and incident investigation, yet another form of response.
How to Test an XDR System
Given that XDR is a concept, the customer may already possess some of its components. In this instance, testing would only be required for the missing modules. An initial product evaluation can be made by applying a past security event to the new product. The customer can then determine what the outcome might have been if they had already been using XDR at the time of the previous case. Basic response scenarios can also be tested to demonstrate how much quicker this process will be with XDR.
The Future of the XDR Market
The global market is anticipated to move toward a clearer understanding of the XDR concept. Developers of information security solutions will be forced to adapt to this defined interpretation in order to remain competitive.
The volume of analyzed data will increase, while the number of false positives from XDR systems will decline. Products and ecosystems will become more practically oriented, aiming to minimize the probability of unacceptable business risks. Vendors will amplify the integration of new products into XDR and increase the number of third-party data sources compatible with the system. Simultaneously, the collected data can be utilized for purposes beyond detecting cyber threats, such as implementing the zero trust concept.
The broadening scope of XDR interaction with sensor systems and other data sources, including those from other vendors, could gradually edge standalone SIEM and SOAR products out of the market.
Some experts envision XDR as the foundational technology platform for security operations centers, an autonomous tool capable of decision-making, thereby reducing a company’s reliance on human intervention.
In summary, XDR tools can seriously enhance a company’s level of information security. Automated, autonomous, and comprehensive incident response enables security specialists to focus solely on serious issues, reducing response time and preventing attacks.
On the flip side, neither vendors nor customers currently possess a clear understanding of the scope and content of this concept or what specific tools should constitute an XDR solution. The answers to these and other questions will shape the future of this market sector.
