What is extended detection and response (XDR)?
Learn how extended detection and response (XDR) solutions provide threat protection and reduce response time across workloads.
XDR definition
Extended detection and response, often abbreviated as XDR, is a unified security incident platform that uses AI and automation. It provides organizations with a holistic, efficient way to protect against and respond to advanced cyberattacks.
Enterprises increasingly operate in multicloud and hybrid environments, where they encounter an evolving cyberthreat landscape and complex security challenges. In contrast to targeted systems like endpoint detection and response (EDR), XDR platforms expand coverage to protect against more sophisticated types of cyberattacks. They integrate detection, investigation, and response capabilities across a wider range of domains, including an organization’s endpoints, hybrid identities, cloud applications and workloads, email, and data stores. They also drive efficiency across security operations (SecOps) with advanced cyberattack chain visibility, AI-powered automation and analytics, and broad threat intelligence.
Read this article for an overview of XDR security, including how XDR works, its key capabilities and benefits, and emerging XDR trends.
Key XDR capabilities
XDR platforms coordinate cyberthreat detection and response across an organization’s entire digital estate. They help quickly stop cyberattacks by seamlessly consolidating various security tools in a single platform, breaking down traditional security silos to enhance cyberthreat protection. Here are five key XDR capabilities:
Incident-based investigation
XDR collects low-level alerts and correlates them into incidents, more quickly giving security analysts a comprehensive picture of each potential cyberattack. Analysts no longer need to sift through random pieces of information to uncover and understand cyberthreat activity, increasing productivity and enabling faster responses.
Automatic disruption of advanced cyberattacks
Using high-fidelity security signals and built-in automation, XDR detects in-progress cyberattacks. It then initiates effective incident response actions, including isolating compromised devices and user accounts, to disrupt attackers. Using these capabilities, organizations can significantly lower risk, limit the incident blast radius, and reduce and simplify analysts’ post-incident investigation and cleanup.
Cyberattack chain visibility
Because XDR ingests alerts from a wider set of sources, analysts can view the full cyberattack chain of a sophisticated attack that might otherwise go undetected by point security solutions. Greater visibility reduces investigation time and increases the likelihood that full cyberattacks can be successfully remediated.
Auto-healing of affected assets
Using built-in automation capabilities, XDR returns assets compromised by ransomware, phishing, and business email campaigns to a safe state. It performs healing actions such as terminating malicious processes, removing malicious forwarding rules, and containing affected devices and user accounts. Freed from repetitive, manual tasks, security teams can focus on addressing more complex, high-risk cyberthreats.
AI and machine learning
XDR’s application of AI and machine learning makes AI for cybersecurity scalable and efficient. From monitoring threatening behavior and sending alerts to investigation and remediation, XDR uses AI to automatically detect, respond to, and mitigate possible cyberattacks. With machine learning, XDR can create profiles of suspicious behavior, flagging them for analyst review.
How XDR works
XDR uses AI and advanced analytics to monitor numerous domains across an organization’s technology environment, identify alerts and correlate them into incidents, and prioritize the incidents that present the highest risk. Able to view each cyberattack in greater context, security teams can more clearly and quickly understand the danger at hand and determine how to best respond.
Here's how an XDR system works step by step:
Collects and normalizes data.
The system automatically ingests telemetry data from multiple sources. It cleans, organizes, and standardizes the data to help ensure the availability of consistent, high-quality data for analysis.
Parses and correlates data.
The system uses machine learning and other AI capabilities to automatically analyze the data and correlate alerts into incidents. It can analyze extensive data points and locate cyberattacks and malicious behavior in real time, significantly faster than security teams attempting to manually correlate alerts and remediate threats.
Facilitates incident management.
The system prioritizes the severity of new incidents and provides more context, helping security personnel more quickly triage then acknowledge and respond to the most important cyberthreats. Based on present conditions, personnel can respond manually or let the system respond automatically, such as by quarantining devices or blocking IP addresses and mail server domains. Security analysts can also review incident reports and recommended solutions and act accordingly.
Helps prevent future incidents.
Through analysis of broad threat intelligence, some XDR systems provide detailed cyberthreat information that is relevant to an organization’s specific environment, including cyberattacker techniques and recommended actions for addressing them. Security teams can use these insights to proactively protect against those cyberthreats that present the greatest risk to their operations.
Key XDR benefits
Increased visibility
XDR expands an enterprise’s view, offering a clearer understanding of its security landscape. Also, by integrating telemetry data from multiple domains, including endpoints, identities, email, cloud applications and workloads, data, and other sources, XDR uncovers threats that might otherwise go undetected.
Accelerated threat detection and response
XDR identifies cross-domain threats in real time and deploys automated response actions. These capabilities eliminate or reduce the amount of time that cyberattackers have access to enterprise data and systems.
Streamlined SecOps workflows
By automatically correlating alerts, an XDR streamlines notifications, reducing noise in analysts’ inboxes and the amount of time they spend manually investigating threats.
Reduced operational complexity and costs
XDR simplifies investigation and response across security operations by consolidating tools from multiple vendors into a single cost-effective XDR platform.
Enhanced incident prioritization
XDR evaluates and highlights high-risk, in-progress incidents that analysts need to promptly investigate. It also recommends actions that are aligned with key industry and regulatory standards as well as with an enterprise’s custom requirements.
Faster SOC insights
XDR provides the security operations center (SOC) with AI and automation capabilities required to stay ahead of sophisticated threats. In addition, with a cloud-based XDR platform, the SOC can rapidly pivot and scale its operations as cyberthreats evolve.
Improved productivity and efficiency
XDR offers capabilities that automate repetitive tasks and enable asset self-healing, reducing labor and freeing analysts for higher-value activities. Also, centralized management tools increase alert accuracy and simplify the number of solutions analysts must access to investigate and remediate threats.
How to implement XDR
A successful XDR implementation can drive security and efficiency across enterprise operations. However, getting the most value from an XDR platform requires careful planning, from creating a broad XDR strategy to measuring system performance. Follow these steps to help ensure a successful XDR implementation:
Assess security needs.
Begin by evaluating and documenting your organization’s specific security requirements. Identify areas of greatest risk, factoring in network size, data types, device types, and access locations. Also consider data protection and other regulations and requirements with which you must comply.
Set strategic goals.
Establish an XDR strategy and roadmap that support your organization’s larger security strategy. Set realistic objectives based on your existing cybersecurity maturity and skill sets, architecture and tools, and budgetary constraints.
Research and select an XDR system.
Look for a robust XDR platform with advanced AI and automation capabilities and a user-friendly interface providing real-time visibility. Find a solution that is compatible with existing systems and can be quickly deployed and scale to accommodate growing data volumes. Not least, work with an experienced vendor offering expert services and support.
Plan the implementation.
Develop a comprehensive plan for deploying, configuring, and managing the XDR system, including defining associated roles and responsibilities. Outline how to connect the system to existing infrastructure, tools, and workflows. Also, establish storage requirements for logging and telemetry data and create risk-assessment mechanisms for automated alert and incident prioritization.
Carry out a phased rollout.
Implement and test the system in stages to minimize operational disruptions. Begin by testing the XDR system with a selection of endpoints before deploying it across the entire technological environment. Once the system is up and running, run through automated scenarios in your incident response playbook and adjust rules as needed.
Provide training and support.
Train your security team to effectively use and manage the XDR platform’s main components and functions. Also, assess and address any knowledge and skills gaps in the team’s ability to interpret alerts and respond to threats. Provide ongoing support to assist the team with any post-implementation challenges.
Continually monitor and refine performance.
Regularly build in time to fully assess the XDR system and its baseline data to help ensure accuracy. Also, adjust playbooks and rules as the system takes in more historical data and new cybersecurity risks emerge.
Components of an XDR system
Endpoint detection and response tools
Endpoint detection and response (EDR) tools monitor a variety of endpoints, including mobile phones, laptops, and Internet-of-Things (IoT) devices. EDR helps enterprises detect, analyze, investigate, and respond to suspicious activities that elude antivirus software.
AI and machine learning
XDR platforms use the latest AI and machine learning capabilities to automatically detect anomalies, prioritize active threats, and send alerts. They also offer user and entity behavior analytics for filtering out false alarms.
Other threat detection and response tools
Email security and identity protection capabilities safeguard user accounts and communications from unauthorized access, loss, or compromise. Cloud security and data security tools help protect cloud-based systems and data from internal and external vulnerabilities, such as data breach incidents. Mobile threat detection provides visibility into and protection for all devices—including personal devices—connected to the enterprise network.
A security analytics engine
An analytics engine uses AI and automation to sift through myriad individual alerts and correlate them into incidents. The engine enriches detections with cyber threat intelligence—detailed, contextual knowledge about in-progress and other threatening attacks. Threat intelligence is both built into XDR platforms and pulled from external global feeds.
Data collection and storage
A secure, scalable data infrastructure enables enterprises to gather, store, and process large volumes of raw data. The solution should connect to multiple data sources—including third-party applications and tools across cloud, on-premises, and hybrid environments—and support different data types and formats.
Automated response playbooks
Playbooks are a collection of remediation actions that security teams can use to automate and orchestrate their threat responses. Playbooks can be run manually in response to specific types of incidents or alerts or run automatically when triggered by an automation rule.
Common XDR use cases
Cyberthreats vary in relevance and type, requiring different methods of detection, investigation, and resolution. With XDR, enterprises have greater flexibility to address a wide range of cybersecurity challenges across IT environments. Here are some common XDR use cases:
Cyber threat hunting
With XDR, organizations can automate cyber threat hunting, the proactive search for unknown or undetected threats across an organization’s security environment. Tools for cyber threat hunting also help security teams disrupt pending threats and in-progress attacks before significant harm occurs.
Security incident investigation
XDR automatically collects data across attack surfaces, correlates abnormal alerts, and performs root-cause analysis. A central management console provides visualizations of complex attacks, helping security teams determine which incidents are potentially malicious and require further investigation.
Threat intelligence and analytics
XDR gives organizations the ability to access and analyze huge volumes of raw data about emerging or existing threats. Robust threat intelligence capabilities monitor and map global signals every day, analyzing them to help organizations proactively detect and respond to ever-changing internal and external threats.
Email phishing and malware
When employees and customers receive emails that they suspect are part of a phishing attack, they often forward the emails to an assigned mailbox for security analysts for manual review. With XDR, enterprises can automatically analyze the emails, identify those with malicious attachments, and delete all infected emails across the organization. This boosts protection and reduces repetitive tasks. Similarly, XDR’s automation and AI capabilities can help teams proactively detect and contain malware.
Insider threats
Insider threats, whether intentional or unintentional, can result in compromised accounts, data exfiltration, and damaged company reputations. XDR uses behavior and other analytics to identify suspicious online activities, such as credential abuse and large data uploads, that could signal insider threats.
Endpoint device monitoring
With XDR, security teams can automatically perform endpoint health checks, using indicators of compromise and attack to detect in-progress and pending threats. XDR also provides visibility across endpoints, enabling security teams to determine where the threats originated, how they spread, and how to isolate and stop them.
XDR vs. SIEM
XDR and enterprise security information and event management (SIEM) systems offer different but complementary capabilities.
SIEMs aggregate large quantities of data and identify security threats and anomalous behavior. Because they can ingest data from virtually any source, they provide high visibility. They also streamline log management, event and incident management, and compliance reporting. SIEMs can work with security orchestration, automation and response (SOAR) systems to respond to cyberthreats but require extensive customization and don’t offer automatic attack disruption capabilities.
Unlike SIEMs, XDR systems ingest data from only those sources that have prebuilt connectors. However, they automatically collect, correlate, and analyze a much deeper, richer set of security telemetry and activity data. They also provide cross-domain cyberthreat visibility and contextual alerts that enable security teams to focus on the highest priority events and initiate quick and targeted responses.
By combining XDR with SIEM, enterprises gain comprehensive detection, analysis, and automated response capabilities across every layer of their digital estate—as well as a foundation for introducing generative AI capabilities. Enterprises also gain greater visibility across their cyber kill chain—a framework, also known as a cyberattack chain, that outlines the stages of common cybercrimes.
Future XDR trends
As XDR adoption continues to grow, vendors continue to enhance existing XDR capabilities and introduce new ones. Here are some emerging XDR trends that promise to help enterprises stay ahead of ever-changing security challenges:
Platform unification
To provide visibility across the entire cybersecurity attack chain, XDR platforms will be combined with SIEM solutions. These unified systems are crucial for introducing AI tools that deliver real-time analytics and insights to help teams identify vulnerabilities and monitor and remediate threats faster.
AI and automation
XDR platforms will implement increasingly powerful algorithms to enable faster, more accurate analysis of expanding data volumes and attack surfaces. Through machine learning, they will continuously learn and improve system performance over time. XDR will also automate more threat detection and response processes, reducing human errors and workloads and leading to better response outcomes.
Cloud-native XDR
Cloud-native XDR platforms will become more prevalent to support hybrid and cloud infrastructures. Cloud-native XDR systems are designed to strengthen security across channels and environments—and can scale to collect massive data volumes. They also streamline system deployment, updates, and maintenance.
Internet-of-Things and operational technology
Connections to IoT and operational technology (OT) devices will become necessary XDR components. Able to use XDR to quickly and proactively identify vulnerabilities in connected devices, enterprises can better protect their IoT and OT networks.
Threat intelligence sharing
Worldwide threat intelligence from numerous sources will be more easily shared through XDR systems, giving enterprises deep pools of data from which they can generate insights into cybercriminals and their activities. Threat intelligence sharing also promotes greater collaboration and coordination among security teams.
Proactive threat hunting
Threat hunting is becoming more proactive and predictive. In the future, XDR systems will offer the capabilities—and threat intelligence—to track attacker patterns over time and predict when and where attacks will occur next. With these insights, security teams can stop them faster.
User behavior analytics
User behavior analytics (UBA) will play a larger role in correlating cross-domain data to identify abnormal, malicious user activities. Through machine learning and behavioral modeling, it will help detect compromised accounts and insider threats by pinpointing activities that deviate from baselines of normal user behavior.
Zero trust integration
In the future, XDR platforms could integrate with Zero Trust architectures, which protect all organizational resources through authentication instead of just guarding access to the corporate network. Using XDR platforms with Zero Trust capabilities, enterprises can achieve more granular, effective security, including for remote access, personal devices, and third-party apps.
Simplified interfaces, tools, and features
XDR platforms will continue to become more user friendly and intuitive. Advanced visualizations will help security teams quickly understand threatening scenarios. Streamlined reporting and auditing features can aid in regulatory compliance.
Implement XDR for your business
Today’s cybersecurity landscape is complex and multilayered—and rapidly changing. Fortunately, XDR provides a flexible, holistic approach for proactively detecting and responding to cyberthreats—no matter where they lurk. It also boosts productivity and efficiency.
Get started implementing XDR for your business with an XDR platform and other security solutions from Microsoft.
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Frequently asked questions
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An XDR platform is a SaaS-based security tool that draws on an enterprise’s existing security tools, integrating them into a centralized security system. An XDR pulls raw telemetry data from across multiple tools like cloud applications, email security, and identity and access management. Using AI, including machine learning, the XDR then performs automatic analysis, investigation, and response in real time. XDR also correlates security alerts into larger incidents, allowing security teams greater visibility into attacks, and provides incident prioritization, helping analysts understand the risk level of the threat.
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When considering XDR versus EDR, keep in mind that they are similar but different. XDR is a natural evolution from endpoint detection and response (EDR), which primarily focuses on endpoint security. XDR broadens EDR’s scope, offering integrated security across a wider range of products, including an organization’s endpoints, hybrid identities, cloud applications and workloads, email, and data stores. XDR offers flexibility and integration across an enterprise’s range of existing security tools and products.
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Native XDR systems integrate with an enterprise’s existing portfolio of security tools, while hybrid XDR also uses third-party integrations for telemetry data collection.
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XDR offers a range of integrations, including an enterprise’s existing SOAR and SIEM systems, endpoints, cloud environments, and on-premises systems.
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Managed detection and response (MDR) is a human-managed security service provider. Often MDRs use XDR systems to meet an enterprise’s security needs.
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