With the rise of sophisticated attacks, a widening attack surface, more assets to protect, and limited security staff, threat detection and response is much more challenging today than in past years. Traditional tools, including Endpoint Detection and Response (EDR), Network Detection and Response (NDR), and Security Information and Event Management (SIEM), aren’t sufficient to address these new challenges. In addition to being hamstrung by limited technology, security teams are under-resourced due to budget constraints. To address these challenges, enterprises are turning to Extended Detection and Response (XDR) solutions.
Emergence of XDR
Extended Detection and Response (XDR) is a threat detection and incident response tool that unifies and contextualizes information from multiple security products into a single security operations system. Discover what XDR is. Primary XDR functions include the collection, centralization, and normalization of data in a repository for analysis and query. XDR solutions can detect today’s modern threats, including those that move slowly through an organization.
XDR goes beyond traditional reactive point solutions, including EDR, SIEM, and Network Traffic Analysis (NTA). XDR platforms integrate, analyze, and contextualize results from existing security control components giving you a unified view of your organization’s security posture across the entire environment. Extended Detection and Response solutions can detect an entire kill chain.
XDR platforms integrate into Incident Response (IR) or Security Orchestration, Automation, and Response (SOAR) solutions, saving security teams from integrating each security tool separately.
Most Extended Detection and Response solutions are vendor-specific. While vendor-specific solutions can simplify deployment by integrating their common security control components, the single vendor approach can add time and expense if customers have to replace competing control products first. Also, they’re limited to the vendor’s technology stack and expertise.
Introducing Gurucul XDR
Gurucul XDR is a vendor-agnostic Extended Detection and Response platform. It unifies control points, security telemetry, analytics, and operations into one enterprise system allowing the security operations team to detect and respond to threats faster and more effectively. As a vendor-agnostic solution, customers can leverage their best-of-breed security control products while deriving the benefits of a unified threat detection and response system. Gurucul has over 350 out-of-the-box integrations with the most popular security and identity products in use today. New connectors can quickly and easily be built using the Gurucul flex connector framework.
Gurucul XDR offers several advantages:
- Avoids vendor lock-in
- Collects and stores massive amounts of data without performance impact
- Delivers real-time, intelligent telemetry and contextual analytics powered by ML and AI
- Converts correlation into causation
- Turns security alerts into risk-prioritized narratives
Intelligent, Telemetry-Based Analytics
Gurucul XDR’s intelligent telemetry-based analytics applies advanced analytics to detect, predict, investigate, hunt, and remediate threats before they can damage an organization’s ecosystems. It reduces noise and false positives, delivering extensive context that enables the security operations team to focus on the activities that present the highest risks. Unified telemetry data is transformed into risk-prioritized alerts, allowing security teams to detect and respond to threats faster and more efficiently.
The analytics engine uses machine learning (ML) rather than static rules, which allows the system to perform endpoint anomaly detection without having to anticipate and define parameters in advance. Gurucul’s machine learning engine includes more than 2000 data models out-of-the-box. These models are available on day one to deliver immediate impact. The models are tuned to run on high-frequency network data streams to detect real-time anomalies and risk-rank the threats. Customers have the flexibility to fine-tune existing models and create their own.
Gurucul’s analytics unifies data received from distributed networks, cloud environments, SaaS applications, identity stores, and various endpoints. It combines their behavior with user and entity behavior to deliver rich context for further analysis or remediation. Gurucul XDR enables security teams to quickly discover:
- Which device triggered the incident?
- Which systems were connected, where was the connection made, and at what frequency?
- What transactions were performed?
- How much data was transferred?
- Who was using the device?
- What else did the user access on the network?
- Is the behavior of this device normal and expected, relative to its peers?
Augmented Threat Detection
Gurucul XDR ingests vast amounts of information from Gurucul’s Security Data Lake and then leverages machine learning, Artificial Intelligence (AI), and open analytics to connect the dots to provide visibility into unknown and previously undetected threats. By leveraging big data and machine learning, Gurucul XDR allows organizations to identify what “normal” behavior looks like, making it easy to spot suspicious and anomalous activities.
The solution is incredibly powerful for identifying previously unknown malware, zero-day exploits, and attacks that are slow to develop. It can also identify rogue behavior by insiders (or attackers using legitimate insider’s credentials). For example, Gurucul’s XDR can detect endpoint malware that is missed by software dependent on signatures and known patterns, based entirely on the malware’s behaviors.
Gurucul XDR provides a solid foundation with one of the largest libraries of machine learning models available, including 2,000+ pre-packaged ML models pre-tuned to detect and predict threats for specific use cases, data telemetry, industry verticals, and threat and compliance frameworks (MITRE, PCI-DSS etc.). Security teams can utilize these pre-packaged rules to detect signatures of existing cyber threats, or write their own rules tailored for their specific environment.
Automated Incident Response
Traditional threat detection and response systems can overwhelm SOC teams with a flood of alerts triggered by their rule and signature-based systems. This causes operator fatigue and increases the likelihood of missing something important. In comparison, Gurucul XDR can automatically correlate a series of low-confidence events to deliver risk prioritized alerts based on contextual behavior with much higher confidence. It eliminates noise and allows SOC members to prioritize and focus on what’s important, responding to the threats that represent the greatest risk to their organization.
The solution utilizes AI-enabled automated response modules that run on Gurucul’s Security Data Lake. SOC analysts can dive straight into investigations and remediation without having to access multiple sources of information to tie a security narrative together. Gurucul Extended Detection and Response automatically creates these narratives.
Automated Incident Timelines create a smart link of the entire attack lifecycle for pre and post incident analysis. Timelines can span days and even years of data in easy to understand visualizations. Visualization and Dashboarding enable analysts to view threats from different perspectives using several widgets including Tree Map, Bubble Chart, etc., that provide full drill down capabilities into events without leaving the interface. The unique scorecard widget generates a spider chart representation of cyber threat hunting outcomes such as impact, sustaining mitigation measures, process improvements score, etc.