Extended detection and response (XDR) is a term coined by Nir Zuk at Palo Alto Networks in 2018. The purpose of XDR is to address the challenges posed by siloed approaches to data analysis for security. In the past, security measures focused on a single type of device or area, such as endpoint, network, or user behavior. However, this approach often missed crucial context and indicators from other areas that could have identified potential risks.
XDR aims to analyze all these focus areas and bring them together in a holistic platform. By doing so, it can provide a comprehensive understanding of all the data involved in a security event. This allows the security operations center (SOC) to respond effectively to malicious or risky events by providing tracking and remediation steps.
The concept of XDR was developed in response to the challenges faced by enterprises regarding visibility and understanding of significant security events in their environments. Palo Alto Networks realized that there was a gap between the focused, siloed products vendors offered and the broader coverage required by enterprises. XDR was designed as a solution to bridge this gap by connecting information from all sides of an enterprise IT infrastructure.
To handle the massive increase in raw data, XDR incorporates a machine learning engine. This engine analyzes the data and ensures that only significant events are brought to the attention of an analyst. This prevents analysts from being overwhelmed by unactionable or irrelevant alerts.
The “X” in XDR signifies the extension of detection and response capabilities to all aspects of IT operations. Palo Alto Networks has created a vision map to outline how XDR came into existence and where it is expected to evolve in the future.
XDR plays a crucial role in cybersecurity by moving away from segregated datasets for different aspects of security and unifying them into a single platform. This shift allows enterprises to have a comprehensive view of their security operations and IT landscape. It reduces the likelihood of missed significant events, false positives, false negatives, skill barriers, and manual aggregation and reporting. By analyzing combined data sets with machine learning, XDR has transformed how businesses handle cybercrime, which has evolved from individual hackers to cybercrime businesses and even nation-state level operators.
The market response to XDR has been varied. Many vendors have adopted the term reluctantly while attempting to pass off their existing products, such as endpoint detection and response (EDR) or network detection and response (NDR), as XDR. These vendors have redesigned their user interface to present all the information as a “unified single source” without actually incorporating data from all sources. This approach still maintains the siloed nature of their products.
There has also been an increase in new players who focus on gaining in-depth visibility but do not cover all the different types of equipment in an IT infrastructure. This results in incomplete information being presented to users.
Some vendors have released products without automation through machine learning, leading to a flood of alerts that cannot be adequately addressed. This lack of automation prevents analysts from understanding the full chain of events that led to a security incident.
When adopting XDR, it is crucial to prioritize two main topics. Firstly, all data streams need to be brought together and correlated to provide a comprehensive understanding of an event. Secondly, there must be a system that automatically determines the severity of an event and whether further investigation by an analyst is necessary. To achieve success in today’s cybersecurity defense programs, both of these aspects must be present and work together seamlessly.
In conclusion, XDR is an essential development in the field of cybersecurity. It enables organizations to overcome the limitations of siloed approaches and obtain a holistic view of their security operations. With the incorporation of machine learning, XDR is poised to play a critical role in combating increasingly complex cyberattacks.