About
Elastic Security is an open, AI-driven security analytics platform that brings together SIEM, XDR, and cloud security into one all-inclusive solution built for the modern security operations center. Powered by the open-source Elasticsearch engine, it enables organizations to ingest data from any source, detect threats with open and community-backed detection rules, and respond rapidly using ML and generative AI—all without moving or duplicating data. At its core, Elastic Security combines transparency with power. Its 2,300+ open-source detection rules are publicly reviewable and customizable, ensuring analysts can trust every alert. Machine learning surfaces anomalies in user and entity behavior, while GenAI provides grounded, explainable insights that show the logic, source, and path behind every decision. The platform supports multi-cloud environments (AWS, Azure, Google Cloud) and on-premises deployments through a unified UI with no agents required for cloud security. For organizations not ready for full migration, the Elastic AI SOC Engine (EASE) lets teams augment existing SIEM and EDR tools with AI incrementally. Elastic Security achieved 100% protection rates in all of AV-Comparatives' 2025 Business Security Tests and was named a Leader in The Forrester Wave™: Security Analytics Platforms, Q2 2025. Ideal for enterprise security teams, SOC analysts, and DevSecOps professionals, Elastic Security is the platform of choice for organizations that demand open, scalable, and AI-powered threat detection and response.
Key Features
- Unified SIEM, XDR & Cloud Security: Combines next-gen SIEM, endpoint XDR, and multi-cloud security (AWS, Azure, GCP) into a single platform with no extra SKUs or bolt-ons.
- AI-Powered Threat Detection: Uses machine learning and generative AI to surface critical threats, analyze user and entity behavior, and provide explainable, contextual insights for every alert.
- Open Detection Rules: Over 2,300 community-backed, open-source detection rules are publicly reviewable and customizable, ensuring full transparency and trust in every detection.
- Elastic AI SOC Engine (EASE): Modular AI capabilities that integrate with existing SIEM and EDR tools, allowing teams to adopt AI incrementally without a full platform replacement.
- Flexible Deployment & Open Architecture: Run on any cloud or on-premises environment, ingest any data source, and build custom pipelines on the trusted open-source Elasticsearch foundation.
Use Cases
- Enterprise SOC teams using Elastic Security to unify alert triage, investigation workflows, and automated response across endpoints, cloud, and network telemetry.
- Multi-cloud organizations monitoring AWS, Azure, and GCP environments for misconfigurations, vulnerabilities, and active threats through a single security console.
- Security analysts leveraging open detection rules and AI-powered behavioral analytics to hunt for advanced persistent threats (APTs) and insider risks.
- Organizations augmenting legacy SIEM investments with the Elastic AI SOC Engine to gain AI-driven triage and investigation without a full platform migration.
- DevSecOps teams ingesting custom application and infrastructure data into Elastic Security to correlate security events with development and operational context.
Pros
- Truly Open and Transparent: Open-source detection rules, open architecture, and explainable AI outputs give security teams full visibility and control over their defenses.
- All-Inclusive Platform: SIEM, XDR, cloud security, and AI are bundled in one unified experience with no hidden add-ons, reducing tool sprawl and licensing complexity.
- Proven Security Performance: Achieved 100% protection rates in all of AV-Comparatives' 2025 Business Security Tests and recognized as a Forrester Wave Leader in Security Analytics.
- Flexible Adoption Path: The EASE package allows organizations to augment existing tools with AI gradually, avoiding a disruptive rip-and-replace migration.
Cons
- Enterprise-Focused Complexity: The breadth of features and configuration options can be overwhelming for smaller teams or organizations without dedicated security operations resources.
- Cost Scales with Data Volume: Pricing is tied to data ingestion and infrastructure, which can become significant for high-volume environments if not carefully managed.
- Learning Curve for Full Platform: Maximizing value from the unified platform requires familiarity with Elasticsearch, Elastic Query Language (EQL), and the broader Elastic Stack.
Frequently Asked Questions
What is Elastic Security AI?
Elastic Security AI is an open, AI-driven security analytics platform that unifies SIEM, XDR, and cloud security. It uses machine learning and generative AI to help organizations detect, investigate, and respond to cyber threats at scale.
Is Elastic Security open source?
Elastic Security is built on the open-source Elasticsearch engine and features fully open-source detection rules maintained by an active community. The platform itself offers both open-source and commercial licensing tiers.
What is the Elastic AI SOC Engine (EASE)?
EASE is a modular package of AI capabilities that lets organizations integrate Elastic's AI-powered features into their existing SIEM, EDR, and alerting tools without replacing their entire security stack. It provides a migration path to the full Elastic Security platform over time.
Which cloud providers does Elastic Security support?
Elastic Security supports multi-cloud environments including Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP), as well as on-premises deployments and hybrid configurations.
How does Elastic Security use AI for threat detection?
Elastic Security combines supervised and unsupervised machine learning for behavioral analytics and anomaly detection with generative AI for automated triage, investigation summaries, and natural language querying. All AI outputs are grounded, contextual, and explainable—showing the logic and data sources behind every finding.
