Inside Stellar Cyber’s Data Pipeline: The Hidden Engine Behind Smarter Security

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AI-driven security, Cybersecurity, IT technology, MSSPs, Network Security, Open XDR, Open XDR Platform

Executive Summary

Modern SOCs are overwhelmed by data volume and complexity. The ability to filter, normalize, enrich, and route security data at scale without losing fidelity directly impacts detection accuracy, analyst efficiency, and compliance posture. With the full understanding of the significance of the data challenges and needs of such ability, Stellar Cyber’s data pipeline is not an add-on but a core capability of our AI-Driven SecOps Platform from inception. This white paper outlines the technical underpinnings of Stellar Cyber’s pipeline and how its unique architecture helps security teams unify their data sources, cut noise, and accelerate incident response.

Introduction: Beyond Data Pipelines

While some products focus only on collecting and moving data, Stellar Cyber integrates a full security operations platform with a deeply engineered data pipeline at its core. This pipeline doesn’t just ingest and transport data; it transforms the data through a multi-step process. It filters, normalizes, enriches , correlates, and routes it into proper storage for detection and response workflows and to backup storage like S3. This enables true end-to-end visibility, detection and action.

Core Principles of the Stellar Cyber Data Pipeline

To deliver pervasive visibility across an organization’s entire attack surface, Stellar Cyber’s solution offers multiple methods of data collection. It can gather logs and network telemetry through its distributed modular sensors, integrate with numerous applications via their native APIs, and deploy server sensors to capture data from both Linux and Windows servers.

1. Traffic Filtering at the Edge

Unlike tools that only filter at the ingestion point in a central location, Stellar Cyber’s sensors apply traffic and application filters before data leaves the source. Events that reach the pipeline are immediately processed by advanced Forwarders. They apply fine-grained filtering rules at scale so only the data needed for compliance, detection, or analytics is retained. This pre-ingestion filtering:
  • Removes irrelevant events early (noise reduction at the edge).
  • Lowers bandwidth and storage requirements by discarding non-critical logs upfront.
  • Provides flexibility by supporting policy-driven filtering based on application type, port, protocol, or custom rules.

2. Normalization Across Diverse Sources

The Interflow normalization engine standardizes log formats and schemas from numerous disparate sources. This enables:

  • Automated detection via either Machine Learning or rules
  • Automated correlation of individual alerts into cases through normalized artifacts.
  • Consistent enrichment for contextualization
  • Fast downstream analytics without repeated parsing.
  • Accurate, easy-to-understand dashboards, reports, and investigations.

3. Real-Time Contextual Enrichment at Ingestion

As data flows into the Stellar Cyber Open XDR platform, it is enriched inline in real time – not post-ingestion – delivering high-context telemetry to drive rapid, accurate detection and response.

Key enrichment dimensions include:
  • GeoIP & ASN Lookups: Instantly adds country, city, and autonomous system data to every event with IPs.
  • Real-Time Threat Intelligence: Correlates with multiple threat intel feeds (commercial, open-source, and customer-defined), applying real-time risk scoring.
  • User & Entity Resolution: Maps logs and traffic to human- and machine-identities via Active Directory, Okta, IAM systems, and asset inventories.
  • Application identification: Deep Packet Inspection(DPI) engine and application fingerprinting enhance event clarity beyond port-based heuristics.
  • Custom Tagging & Context Injection: Administrators can inject business-specific context (e.g., asset criticality, function, compliance zones) into the data stream.
This deep, inline enrichment ensures that every alert and investigation starts with rich, actionable context such as where, when, who, what – minimizing triage time, elevating detection precision, and empowering faster root cause analysis.

4. Masking and PII/PHI Redaction

The pipeline includes regex-based filters and masking features to automatically redact sensitive fields such as personally identifiable or protected health information. This helps organizations meet regulatory requirements while still leveraging data for security analytics.

5. Routing and Multiplexing

With routing profiles, enriched events can be sent to multiple destinations simultaneously (SIEMs, any S3 compatible data lakes or Snowflake, ticketing systems, or analytics clusters). This allows teams to:
  • Avoid vendor lock-in.
  • Satisfy diverse storage, compliance, or analytics needs.
  • Feed separate teams or tools without duplicating ingestion efforts.

6. Real-Time Anomaly Detection and Deduplication

Inline anomaly detection and post-ingestion ML modules identify outliers as data arrives. Deduplication and aggregation further reduce data volume without sacrificing fidelity ideal for high-EPS, multi-terabyte/day environments.

7. Multi-Tenant MSSP Architecture

From inception, Stellar Cyber built multi-tenant capabilities into its platform. MSSPs can securely manage multiple customers with full isolation of data, different storage options, different retention periods, policies, and reporting, etc. This gives MSSPs the control to offer different options to meet their customers’ needs.

8. Native Platform Integration

The pipeline is part of Stellar Cyber’s native architecture with no bolt-ons or third-party dependencies. This ensures:
  • Lower latency.
  • Faster updates and scalability.
  • Consistent security and compliance posture
  • Immediate feedback loop between post processing and the data engine.

9. Data Migration Flexibility

Stellar Cyber supports migration from legacy SIEMs to new data lakes or analytics platforms using connectors and routing profiles, preserving continuity and avoiding expensive rip-and-replace projects.

Scalability and Maturity

Stellar Cyber’s pipeline architecture has been proven in global, multi-terabyte/day deployments. Customers routinely scale to tens of thousands of endpoints and dozens of data sources without bottlenecks. The platform’s maturity allows security teams to deploy quickly, integrate broadly, and trust the pipeline in production.

Why Stellar Cyber’s Data Pipeline Matters

Because the pipeline is embedded in an AI-Driven SecOps Platform, analysts get not just clean data but also automated detection, investigation, and response all driven from a single unified environment. This means:
  • Faster MTTR.
  • Higher analyst efficiency.
  • Reduced infrastructure costs.
  • Full visibility from ingestion to remediation.

Conclusion

Stellar Cyber’s data pipeline is more than just a transport mechanism; it’s the backbone of a unified, AI-powered security operations platform. By filtering at the source, normalizing across diverse feeds, enriching with context, and routing data flexibly, Stellar Cyber empowers SOC teams to operate at scale, cut through noise, and respond to threats faster.

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