Machine Learning-Based Anomaly Detection for the Cloud

Quickly uncover, assess, and respond to known and unknown risk using the Threat Stack Cloud Security Platform® with ThreatML™, powered by:

  • Unrivaled cloud intrusion detection telemetry
  • Real-time behavioral rules engine
  • Advanced machine learning (ML) anomaly detection
  • Deep human expertise, backed by 24/7 in-house security analysts

What is ThreatML?

ThreatML enhances the Threat Stack platform’s rules engine and our Oversight and Insight services by intelligently surfacing anomalous activities across cloud workloads. It learns and baselines user behavior with proven investigation techniques used by Threat Stack’s security services teams to uncover suspicious trends that could otherwise go undetected.

ThreatML anomaly detection complements Threat Stack’s continuous security telemetry collection, robust rules and alerting capabilities, and professional services, all of which enable security teams to improve their risk visibility, context, and response to both known and unknown threats.

Want to learn more?

Download the Solution Brief

ThreatML Blogs

Learn more about the Threat Stack Cloud Security Platform® with ThreatML™, the types of risks and threats we surface, and how you can leverage Threat Stack’s rich telemetry with ML-based anomaly detection to secure your cloud infrastructure and applications.

How We Stack Up

Alert Logic
Cloud and Container Telemetry Collection (API & Agent Based)
24/7/365 Managed In-House SOC Service
Custom Reporting and Advisory Service (DAAS)
Multi-Operating System Support
Native AppSec Libraries (RASP)
Rules Based Engine
Custom Rules for Compliance & Known Threats
Cloud Optimized Deployment
Dedicated Account Team
Support included with Platform
ML-based Anomaly Detection
Automated Risk Scoring and Prioritization

What you don't know can hurt your cloud security posture.

Protect your critical infrastructure from unknown risk with ThreatML.