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3 Ways XDR Will Streamline Your SOC

Your security stack represents your toolkit: each tool allows you to parse the constant streams of application, log, and server data flowing throughout your organization into genuine threat intel. In the last half-decade, many tools have pushed the boundaries of their own niches – next-gen firewalls, for instance, have seen increasingly impressive ways of digging deeper into packet data. In an effort to gain the best overview possible, many organizations cram their security stacks with as many hyper-specified tools as budgets allow for. While each siloed tool keeps track of its own piece of the security puzzle, it’s still up to analysts to accurately build the wider picture.

Extended Detection and Response (XDR) solutions take a step back from the edge of high-fidelity data collection, and focus on transforming the threat info being recorded by each tool into wider, cross-referenced insight into your wider security wellbeing. This article will examine what XDR can offer SOC teams, and assess the tool’s on-the-ground impact.

How Does XDR Work?

Integrating security data from multiple sources across an organization’s IT environment requires a careful and methodological approach. XDR builds this functionality across seven key areas:

1. Data Collection

XDR platforms collect security telemetry data from various sources, such as endpoint detection and response (EDR), network detection and response (NDR), cloud access security brokers (CASB), and identity and access management (IAM) solutions. These are gathered through a number of different connectors – APIs allow cloud and on-prem data to be shared, while log sources are streamed via Syslog protocols. Finally, sensors allow for network activity to be recorded at the very edge.

2. Data Aggregation

The collected data is aggregated into a central data lake or repository, providing a unified view of the organization’s security posture. Data, regardless of its origin, gets normalized into a standard data model. Common fields like source IP, timestamp, or logon type are collated. Sensors further allow deep packet inspection (DPI), intrusion detection system (IDS), and malware sandbox results to be collated into a single manageable software file.

3. Data Enrichment

XDR platforms then enrich the collected data with third-party threat intelligence. Individual pieces of data are further enriched with geolocation and asset context to increase the value of all collected telemetry.

4. Threat Detection

Advanced analytics, machine learning, and artificial intelligence algorithms are applied to the aggregated and enriched data to detect suspicious activities, complex behavioral patterns, and early warning signs of potential threats. Unsupervised machine learning further allows XDR customers to identify anomalous behavior that doesn’t line up with expectations. After a few weeks of establishing a baseline, it then becomes possible to detect novel and zero-day threats.

5. Threat Investigation

XDR platforms ease some of the strain placed on analysts by doing away with old-school alerts. Instead, events are automatically correlated into cohesive incidents. By focusing on incidents instead of alerts, the threat investigation process can closely follow the attack-kill chain.

6. Automated Response

Based on predefined rules and playbooks, XDR can automate certain response actions, such as blocking malicious traffic, isolating compromised endpoints, or triggering incident response workflows

7. Reporting and Analytics

XDR platforms offer reporting and analytics capabilities to help security teams measure the effectiveness of their security controls, identify areas for improvement, and demonstrate compliance with regulatory requirements.

Benefits of XDR to Cybersecurity

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