Overview
Exaforce integrates with Elastic Security to centralize SIEM alerts and enrich them with cross-platform telemetry. By correlating Elastic detection rule findings with identity events, endpoint activity, cloud API logs, and network traffic, Exaforce helps security teams validate alert intent, filter noise, and build complete attack narratives from fragmented signals.
How it works
Exaforce connects to Elastic Security via API to continuously ingest alerts generated by detection rules, machine learning jobs, and behavioral analytics. Once ingested, alerts are normalized into Exaforce's unified schema and automatically correlated with telemetry from identity providers, cloud platforms, endpoint agents, and network sources already flowing into Exaforce. The platform's AI triage engine evaluates each alert against historical baselines, user behavior patterns, and business context to determine whether the activity represents a true positive, benign operation, or edge case requiring investigation.
Core capabilities
Automated alert triage and validation
Exaforce applies behavioral analysis and contextual enrichment to Elastic alerts, comparing detected activity against known-good patterns, user roles, and asset criticality. Alerts flagged by Elastic detection rules are cross-referenced with correlated events from other systems to validate whether the underlying behavior is consistent with legitimate operations or represents genuine malicious activity. This reduces the volume of alerts requiring manual review and prioritizes findings based on actual risk.
Cross-system correlation for complete attack chains
Elastic alerts often capture isolated signals, such as an unusual process execution, a suspicious network connection, or an anomalous authentication attempt. Exaforce reconstructs the full sequence by linking these alerts to upstream and downstream activity across identity systems, cloud control planes, SaaS applications, and endpoints. Analysts can trace an Elastic detection back to the initial access vector, follow lateral movement through correlated network and cloud events, and identify data exfiltration or privilege escalation in a single, unified timeline.
Enriched alert context
Each Elastic alert ingested into Exaforce is automatically enriched with additional metadata, including user identity attributes, device details, asset ownership and criticality tags, threat intelligence on observed IPs, domains, and file hashes, and related detections from other sources that share common indicators or affected entities. This context is surfaced directly in the investigation interface, eliminating the need for manual lookups and providing analysts with immediate situational awareness.
Deep investigation with pivoting and natural language queries
Exaforce enables analysts to pivot from any Elastic alert into the underlying raw data and related events. Investigations can span multiple data sources without switching tools. Analysts can query using natural language to explore related activity and receive structured results grounded in correlated telemetry from Elastic and connected systems.
Detection logic transparency and tuning feedback
Exaforce preserves the original Elastic detection rule context, including rule name, severity, risk score, MITRE ATT&CK mappings, and triggered conditions. When alerts are triaged as false positives, Exaforce captures the rationale and supporting evidence, which can inform future detection tuning in Elastic or adjustment of correlation logic within Exaforce to improve precision over time.
Benefits
Exaforce reduces Elastic alert volume by filtering out false positives and benign findings through cross-system validation and behavioral baselining, which decreases time spent on alerts and allows analysts to focus on high-impact threats. It improves investigation speed and accuracy by providing a unified view of Elastic alerts alongside identity, cloud, and network events, which eliminates context-switching and manual correlation.