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Successful Integration with Google SecOps SIEM
Published in: Security

Accelerate Threat Detection and Reduce Triage Time with Successful Integration with Google SecOps SIEM

From Indicators to Intelligence: Transforming TeamCymru's Threat Data into Actionable Insights with Google SecOps SIEM

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Case Study

Accelerate Threat Detection and Reduce Triage Time with Successful Integration with Google SecOps SIEM

Successful Integration with Google SecOps SIEM

Executive Summary

The customer, through this project, improved its threat detection and investigation in Google SecOps SIEM through proper utilization of its high-value threat intelligence capabilities. Faced with huge amounts of telemetry data consisting of unfamiliar IPs, domains and hashes, the security analysts lacked context to ensure rapid triage and investigation. There were several other challenges like inconsistent format of threat indicators to ingest into UDM leading to higher overheads due to manual processing of data.

Crest Data developed end-to-end integration between customer’s platform and Google SecOps SIEM, enabling the organization’s security team to enhance their threat detection capabilities within Google SecOps using customer’s comprehensive threat intelligence. This integration allows organization’s security teams to perform use cases such as automatic enrichment, manual analyst-driven enrichment of security telemetry with IP and domain intelligence, improving detection accuracy and accelerating investigations in Google SecOps using customer’s threat intelligence data.

About the Customer

The customer is one of the leading companies that provide comprehensive visibility into the global cyber threat activities and provides vital intelligence to vendors dealing with cyber security and threat intelligence. It provides robust solutions to detect threats and vulnerabilities across the enterprise networks, find and close detection gaps and accelerate incident response.

Customer Challenge

The customer was facing critical problems that significantly hampered their ability to strategically leverage their threat intelligence information to consolidate their threat detection capabilities:

  • Insufficient context: Security analysts encountered unfamiliar IPs, domains, and hashes in telemetry but lacked the enriched metadata needed for rapid triage and investigation.
  • Format inconsistency: Although the customer supplies high-value indicators, varying formats and inconsistent metadata prevented direct ingestion into Google SecOps’s Unified Data Model (UDM).
  • Manual processing overhead: Without standardized mapping and automated normalization, analysts wasted valuable time manually cleaning and cross-referencing indicators before enrichment.
  • Limited visualization: There was no dedicated visualization capability to surface indicator trends and patterns across the threat landscape.

Organizations needed a standardized way to transform customer’s high-value threat intelligence into actionable context within Google SecOps SIEM, enabling rapid triage and investigation of unfamiliar IPs, domains, and hashes regardless of their original format.

Proposed Solution

Crest Data developed a comprehensive integration between customer’s platform and Google SecOps SIEM with the following key components:

  • Threat Indicator Feed : Scheduled and on-demand feed pulls indicator to ensure fresh, relevant indicators. Analysts can configure which indicator types (IP, domain, URL, hash) or feed subsets to ingest, reducing noise and focusing on relevant threat types.
  • Normalization : Raw fields supported by the customer are translated into Google SecOps’s Unified Data Model. When an indicator references an asset, the integration creates entity artifacts in Google SecOps. So analysts can pivot from an indicator to the asset’s historical telemetry.
  • Enrichment : Analysts can put indicator lists into a Google SecOps data table or reference list, these inputs trigger the enrichment pipeline, enabling ad-hoc research and bulk lookups.
  • Real-time correlation : Ingested indicators are automatically matched against incoming telemetry (logs, network events) in Google SecOps, when a match occurs it is surfaced as an indicator-hit event and displayed in IOC Matches in Google SecOps.
  • Visualization : Dashboard that surfaces ingestion volume, top indicators, timeline views for investigations.

Note: The above solution could be easily migrated to the Content pack once it is GA.

The Crest Difference

  • Threat Intelligence, Made Actionable: This solution brings customer’s intelligence directly into Google SecOps UDM – fully normalized, enriched, and instantly usable for investigations and detections, not just ingested as raw data.
  • Beyond Ingestion with UDM Expertise: We layered IOC and entity data models to enable seamless automatic correlation, reliable search and detection experience across Google SecOps.
  • Deep Google SecOps & Security Operations Expertise: Our profound understanding of how security teams actually use these platforms ensures that the integrations we build are not just technically sound but intuitively useful and highly effective in real-world scenarios.

About Crest Data

Crest Data is a data and AI-first product engineering and technology solutions provider with deep expertise in cloud and AI, cybersecurity, observability, data analytics, and workflow automation. In this case study, Crest Data applied its CloudOps and DevSecOps capabilities to help the customer migrate from on-prem infrastructure to a secure, scalable, and cost-efficient AWS environment, supported by infrastructure automation and proactive monitoring.

With 1,200+ experts and a track record of 5,500+ successful projects across 150+ global customers, and backed by strong partnerships with AWS, Google, Microsoft, Datadog, Dynatrace, ServiceNow, and NetApp, Crest Data delivers outcome-focused solutions that strengthen security, improve platform reliability, and enable sustainable digital growth.