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IBM QRadar SIEM

Redefine SIEM to unleash analyst potential and outpace adversaries with speed, scale and accuracy

Empowering the modern SOC with threat visibility

Overwhelmed by a flood of alerts and fragmented data, today’s security operations centers (SOCs) face mounting challenges in keeping pace with evolving threats. Nearly half of SOC analysts can address a portion of daily alerts, leaving organizations exposed to advanced attacks.

Security data is often siloed across tools, making it difficult to gain full visibility. Without centralized insight and real-time detection, threats like ransomware, malware and insider attacks can go unnoticed for weeks. Manual processes slow down response times, increasing the risk of damage.

IBM® QRadar® SIEM helps organizations take control by centralizing security visibility, enabling real-time threat detection, streamlining compliance and reducing operational costs. This solution empowers security teams to respond faster and more effectively before incidents escalate.

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Why QRadar SIEM

Why QRadar SIEM

QRadar SIEM delivers meaningful results 0,000+ Analysts saved more than 14,000 hours over 3 years on identifying false positives.*

With QRadar SIEM, analysts can reduce repetitive manual tasks such as case creation and risk prioritization to focus on critical investigation and remediation efforts.

0% Analysts saw a 90% reduction in time spent investigating incidents.*

Disrupt advanced cyberattacks and respond faster with cutting-edge content, including native integration with the open source SIGMA community. No additional context is needed with correlated log event data, including IBM X-Force® Threat Intelligence, user behavior analytics and network analytics.

0% There was a 60% reduction in the risk of experiencing a significant security breach.*

Easily work across all data source types and security tools with robust interoperability. Equipped with over 700 prebuilt integrations and partner extensions*, QRadar SIEM seamlessly integrates with your existing threat detection tools to ensure that you get complete visibility across your security ecosystem.

Features

User behavior analytics (UBA) Sigma rules Network threat analytics
User behavior analytics (UBA)

Gain greater visibility into insider threats, uncover anomalous behavior, quickly identify risky users and generate meaningful insights.

Explore QRadar SIEM's UBA feature

Use cases

Use cases

Advanced threat detection

Responding to advanced threats is resource-intensive, time consuming and time sensitive. Strengthen your detection capabilities by monitoring the full attack path and allow QRadar SIEM to do the heavy lifting.

Learn about advanced threat detection
Threat hunting

Generate comprehensive intelligence and help your analysts hunt for cyberthreats in near real time by turning disparate datasets into action.


Check out how threat hunting works
Ransomware

Fast ransomware attacks demand faster responses. With attackers moving faster, organizations must take a proactive, threat-driven approach to cybersecurity.

Explore ransomware
Compliance

Show evidence of compliance and declaration of conformity with applicable regulatory statutes and internal audits for your environment.

See how QRadar helps with compliance
Experience QRadar SIEM

Experience QRadar SIEM

Demo

Explore the demo video to see how QRadar SIEM helps accelerate threat detection.

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Case study

Case study

Sutherland logo
Sutherland reduced MTTD from days or weeks to just hours

By using IBM QRadar SIEM, Sutherland was able to establish a unified security ecosystem. Analysts use the platform to collect and correlate data from various sources across the IT environment. This feature enables them to build a holistic view of security events.

Read the case study

IBM QRadar SIEM Support

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Schedule time to get a custom demonstration of QRadar SIEM or consult with one of our product experts.

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Footnotes

*The Total Economic ImpactTM of IBM QRadar SIEM is a commissioned study conducted by Forrester Consulting on behalf of IBM, April 2023. Based on projected results of a composite organization modeled from 4 interviewed IBM customers. Actual results vary based on client configurations and conditions; as a result, typical outcomes cannot be provided.