Extended Detection and Response (XDR) is a modern security technology designed primarily as a Security Operations Centre (SOC) enabler tool. It addresses the complexities and challenges faced by security teams in today’s evolving threat landscape. The core idea behind XDR is to take challenging incident response processes and make security analysts more effective, even at more junior levels.
The term XDR itself has emerged over the last few years and can be seen as somewhat nebulous, with different definitions existing. However, a fundamental definition involves the collection of telemetry from multiple security tools, the application of analytics to that telemetry to arrive at a detection, and then a response based on that detection.
Why XDR is Needed
Security threats have evolved, and attackers are using more advanced tactics, techniques, and procedures (TTPs) to evade traditional security tools. Catching threats with a single solution or point product is no longer reliable. The industry felt let down by previous investments, such as Security Information and Event Management (SIEM) tools, which often required significant effort from the user to extract value.
Security teams are often overwhelmed by the sheer volume of data and alerts, leading to “alert fatigue”. It’s like looking for a needle in multiple stacks of needles. There is also a skills gap in the security industry, making it difficult to staff and train analysts to handle complex investigations.
XDR attempts to solve these problems by simplifying security operations, making security analysts more effective, and bringing the necessary information to the surface.
Key Elements and Capabilities of XDR
XDR platforms integrate data from various sources and provide a unified approach to security incident detection and response. Key capabilities often include:
- Data Collection and Integration: XDR collects and correlates data across multiple security products and control points. This includes data from endpoint security, network detection and response (NDR), email security, identity systems, firewalls, and cloud environments. A critical aspect is the ability to integrate with third-party vendors to avoid vendor lock-in and leverage existing security investments. However, the ease and depth of integration can vary between vendors.
- Analytics and Detection: XDR applies analytics, often powered by machine learning (ML) and artificial intelligence (AI), to the collected telemetry. This process involves correlating events from different sources to roll up multiple alerts into a single, prioritized incident. XDR aims to provide a prioritized list or queue of incidents. Detections are often mapped to frameworks like the MITRE ATT&CK framework to provide context on attacker TTPs.
- Investigation: The platform provides tools to investigate security incidents and understand the chain of events. This can involve visualizations, such as attack graphs, that change over time to show the attack path. The goal is to provide detailed examination results and contextual evidence to help analysts understand the nature, priority, and potential impact of an incident.
- Response and Remediation: XDR provides capabilities to respond to detected threats. This often includes guided response actions, recommending steps to contain, mitigate, remediate, or eradicate a threat based on the specific detection and TTPs. XDR also facilitates automation of repetitive tasks and enables automated response actions across integrated tools. The ability to respond is seen as a key part of the value proposition.
- Threat Intelligence: XDR platforms often incorporate threat intelligence from various sources to enrich investigations and aid in threat identification.
- Prioritization: Prioritizing incidents allows security teams to focus on threats posing the greatest risk. XDR aims to provide risk-based prioritization.
- Visualization: Centralized dashboards and visualization tools help organize data and provide a unified view of the security posture.
XDR Compared to Other Security Tools
XDR builds upon and extends the capabilities of previous security solutions.
- XDR vs. SIEM: XDR is not simply a SIEM. While SIEMs primarily focus on collecting and storing raw logs from a wide range of sources, requiring the user to parse and query the data to find value, XDR focuses on curating specific data sources that add value to investigations. XDR is intended to cover the space where traditional SIEMs may have fallen short in making operations easier. However, the lines between these tools are blurring as SIEM vendors also integrate automation and analytics.
- XDR vs. EDR: Endpoint Detection and Response (EDR) solutions focus on the endpoint. XDR extends EDR capabilities by integrating data and detections from other domains like the network.
- XDR vs. SOAR: Security Orchestration, Automation, and Response (SOAR) solutions focus heavily on automating and orchestrating security workflows. XDR platforms also include orchestration and automation tools, which is a significant overlap with SOAR’s core function.
Benefits of Implementing XDR
By unifying security data and workflows, XDR promises significant benefits for security operations:
- Faster Detection and Response: Correlating alerts and providing context helps confirm attacks sooner and accelerates the time to respond.
- Improved Efficiency and Productivity: Automating repetitive tasks and streamlining investigations reduces the workload on security staff. This can lead to reduced analyst effort per incident and increased SecOps efficiency.
- Better Prioritization: Prioritizing incidents based on impact allows teams to focus on the most critical threats.
- Reduced Alert Fatigue: Consolidating multiple alerts into fewer, higher-fidelity incidents helps reduce the overwhelming volume of notifications.
- Enhanced Security Posture: By enabling quicker, more informed responses and potentially reducing attack dwell times, XDR helps improve an organization’s overall security resilience.
Managed XDR (MXDR) Services
For organizations that may not have the staff or resources to fully manage an XDR platform, Managed XDR (MXDR) services are available. These services can include 24×7 monitoring, analysis, investigation, and guided response recommendations provided by the vendor or a third party.
The Role of AI in XDR
Artificial intelligence (AI) plays a significant role in XDR, even if the term is now more mainstream. AI capabilities have been present in security products for a long time.
In XDR, AI is used for:
- Alert Correlation and Chaining: Automatically linking events from different sources and systems to form a correlated incident. This is crucial for handling the volume of incoming events in a timely fashion.
- Dynamic Responses: Moving beyond static guidebooks to potentially offer more dynamic response recommendations based on the specific context of an incident and the environment.
- Threat Intelligence Processing: Helping to process and combine threat intelligence, including leveraging teams like Cisco Talos. This enriches investigations and threat hunting.
- Analysis: Applying analytics to telemetry to identify detections.
Generative AI, while a hot topic due to things like chatbot interfaces, is an evolution of AI techniques. Concepts like Large Language Models (LLMs) are models learning from data, and these are being used in various security contexts.
Challenges
Despite the benefits, implementing XDR can present challenges, including the potential cost and the complexity of integrating disparate security tools. Choosing an open platform that facilitates integration is crucial to avoid vendor lock-in.
Conclusion
In summary, XDR represents an evolution in security operations, moving towards a more unified, automated, and intelligent approach to detecting and responding to sophisticated threats across an extended environment. It aims to simplify complex processes and empower security teams to be more effective.
Further Reading
https://www.cisco.com/site/us/en/products/security/xdr/index.html
https://medium.com/@sdntechdemo
Disclaimer: The author is completely responsible for the content of this article. The opinions expressed are their own and do not represent IEEE’s position nor that of the Computer Society nor its Leadership.
