Help Reduce False Positives
Focus on Real Threats
Correlation-driven detection links related signals across your security stack to reduce noise and surface real threats. Results may vary based on environment configuration and alert volume.
Intelligent Threat Detection Capabilities
Machine learning models and intelligent agents work together to detect threats, reducing false positives and identifying real security incidents across your security tools
Threat Detection Process
From multiple alerts to prioritized threats
Alert Ingestion
Collect alerts from SIEM, EDR, network, cloud, and identity tools
Multiple alerts
Correlation Analysis
Identify relationships and patterns
Cross-tool analysis
Threat Prioritization
Focus on real threats
Prioritized incidents
Illustrative example based on a simulated environment to show how alerts can be consolidated. Numbers are for demonstration only; actual impact varies by environment, alert volume, and configuration. The correlation engine identifies relationships between alerts to distinguish real threats from noise.
Intelligent Threat Detection
Machine learning models analyze patterns across your security tools to detect threats that traditional rule-based systems miss. Behavioral analytics and anomaly detection identify suspicious activities in real-time—so you catch threats before they become incidents.
- Behavioral analytics and anomaly detection
- Machine learning-based threat detection
- Real-time pattern analysis across your security tools
- Cross-domain threat correlation
Intelligent Correlation Engine
Help reduce false positives by identifying relationships between alerts across SIEM, EDR, network, and cloud security tools. Machine learning models continuously learn from your environment to improve accuracy over time.
- Help reduce false positives
- Cross-tool alert correlation
- ML-based relationship identification
- Continuous learning and adaptation
Proactive Threat Hunting
Guided investigation workflows and correlation insights help surface suspicious patterns early, with analysts in control.
- Guided investigations across your security tools
- Cross-domain correlation insights
- Analyst-in-the-loop escalation
- Threat intelligence context
Real-Time Security Monitoring
Designed for around-the-clock monitoring of security events across SIEM, EDR, network, cloud, and identity sources. Intelligent agents analyze events in real-time to detect threats as they occur—providing broad security event coverage. Actual coverage and response times depend on configuration and deployment.
- Continuous monitoring
- Real-time event analysis and detection
- Multi-source security monitoring
- Real-time threat detection and alerting
Detection Across All Threat Types
Detect threats across all security domains: EDR, NDR, CSPM, SIEM, IAM, with XDR-aligned correlation across tools.
Endpoint Detection & Response (EDR)
Detect threats on endpoints using behavioral analytics, process monitoring, and file analysis. Identify malware, ransomware, and advanced persistent threats.
Network Detection & Response (NDR)
Monitor network traffic to detect anomalies, lateral movement, and command-and-control communications. Identify network-based attacks and data exfiltration.
Security Information & Event Management (SIEM)
Correlate security events from multiple sources to detect complex attack patterns. Identify security incidents through log analysis and event correlation.
Identity & Access Management (IAM)
Detect identity-based threats including privilege escalation, account compromise, and unauthorized access. Monitor authentication and authorization events.
Extended Detection & Response (XDR)
XDR-aligned detection across endpoint, network, cloud, and identity signals using cross-domain correlation.