In today’s hyperconnected world, cyber criminals act with increasing agility and speed. So too must security teams. IBM QRadar SIEM helps teams meet the quick response challenge with automated, near-real-time threat detection.
QRadar SIEM can analyze millions of events in near real time by using thousands of prebuilt use cases, User Behavior Analytics, Network Behavior Analytics, application vulnerability data, and X-Force® Threat Intelligence to deliver high-fidelity alerts.
Download the 2024 Threat Intelligence Index
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With attackers moving faster than ever, organizations must use automated threat detection to stay ahead.
IBM measured a 94% reduction in the average time for the deployment of ransomware attacks from 2019 to 2021.¹
The lifespan of phishing kits increased more than 2 times each year from 2019 to 2021.²
Containing a breach in under 200 days saves an average of USD 1.1 million.³
QRadar SIEM is purpose built to analyze both log events and network activity—this unique ability allows QRadar SIEM to provide comprehensive visibility across your security environment, including data across endpoints, on premises, cloud and network devices to limit blind spots where malicious activity could be hiding.
By extending your threat detection capabilities through an expansive set of 450 data source connectors and 370 applications for added functionality combined with network flows, QRadar SIEM monitors the full attack path often missed by other solutions with less visibility.
Log events and network activity are analyzed against historical data to uncover known and unknown threats. X-Force Threat intelligence provides outside world context to your environment to help identify threats from known malware, IPs and URLs, while User Behavior Analytics and Network Threat Analytics detect anomalous patterns by using a number of machine learning models. Thousands of use cases based on MITRE ATT&CK tactics are available for immediate use and on the X-Force App Exchange to help detect the latest attacker patterns.
When threat actors trigger multiple detection analytics, move across the network or change their behaviors, QRadar SIEM tracks each tactic and technique being used. More important, it will correlate, track and identify related activities throughout a kill chain and consolidate the data into a single alert.
The Magnitude Score is composed of 3 factors:
- Relevance: How impactful will this be to your network? (50% of magnitude score)
- Severity: What level of threat does this pose if it occurs? (30% of magnitude score)
- Credibility: With what level of integrity do you trust the data sources involved? (20% of magnitude score)
Complex algorithms are used to calculate the magnitude score. Factors such as the number of events, number of sources, age, known vulnerabilities, and risk of the data source all help to evaluate an event in your environment.
Attacks come in all shapes and sizes. Do you have the right set of use cases to detect PowerShell or lateral movement?
QRadar SIEM Use Case Manager aligns activity and rules to the MITRE ATT&CK tactics and techniques to visually highlight your depth of coverage across the attack phases.
Download use-case specific content packs for free from the IBM App exchange or build your own use cases with Use Case Manager.
User Behavior Analytics uses machine learning to determine normal user behavior against the individual and a learned peer group then flags anomalies such as compromised credentials or rogue privilege escalation and assigns the user a risk score. UBA uses 3 types of traffic to enrich and enable risk scoring:
- Traffic around access, authentication and account changes
- User behavior on the network, including proxies, firewalls, IPs and VPNs
- Endpoint and application logs, such as from Windows or Linux®, and SaaS applications
Network Threat Analytics (NTA) analyzes the flow records on your system to determine normal traffic patterns by using machine learning modeling and then compares all incoming flows to the latest baseline model. Each flow is assigned an outlier score based on the flow attribute values and how frequently the type of communication is observed. By using NTA, analysts can quickly identify which flows might indicate suspicious behavior and prioritize investigations.
QRadar Network Insights (QNI) provides a deeper analysis of the network metadata and application content within a flow. The basic level adds 18 additional attributes while the advanced level can capture details such as a malicious script or PI inside of files getting transferred through the network. By using in-depth packet inspection, Layer 7 content analysis and file analytics, QRadar Network Insights empowers QRadar SIEM to detect threat activity that would otherwise go unnoticed.
Threat detection from center to endpoint with QRadar SIEM protects your organization in a number of ways.
Incorporate IBM Security cyberthreat hunting solutions into your security strategy to counter and mitigate threats more quickly.
Integrate compliance packs into QRadar SIEM to ensure compliance and automate reporting.
Detect ransomware threats rapidly with QRadar SIEM, so you can take immediate, informed action to minimize or prevent the effects of the attack.