AI-Augmented SOC &
Threat Detection
Smarter Detection, Faster Response
Traditional SOC operations are overwhelmed by alert volume. AI-augmented detection changes the equation, using machine learning to baseline normal behavior, surface genuine anomalies, and reduce the false positive noise that burns out security teams.
Endurance Security designs and implements AI-augmented detection architectures that integrate with your existing SIEM, EDR, and log pipeline. We tune detection models to your environment and validate outputs against real-world threat intelligence.
The result is a SOC that spends analyst time on confirmed threats, not chasing phantom alerts generated by static rules written years ago.
SOC & Detection Services
- AI-powered SIEM rule development and tuning
- Behavioral analytics and UEBA implementation
- Threat hunting with ML-assisted anomaly detection
- SOAR playbook design and automation
- Detection engineering and ATT&CK coverage mapping
- Network traffic analysis with AI-based baselining
- Cloud detection (AWS GuardDuty, Azure Sentinel, GCP)
- Insider threat detection program design
- SOC maturity assessment and capability uplift
Detection
Engineering Process
Environment Baselining
Establish behavioral baselines across network, endpoint, identity, and cloud (the foundation for meaningful anomaly detection).
Detection Architecture
Design detection logic aligned to MITRE ATT&CK, integrating AI/ML models with traditional signature-based rules for layered coverage.
Tuning & Validation
Iterative tuning of detection thresholds and ML models against real threat data to maximize precision and minimize alert fatigue.
Automation & Response
SOAR playbook development for automated triage, enrichment, and containment of high-confidence detections.
