How the PropelZ™ Splunk Connector transforms mainframe security monitoring from batch-based compliance checking into real-time threat detection and operational intelligence.
Security operations centers (SOCs) monitor thousands of events per second: application logs, network traffic, user authentication attempts, system alerts. They use sophisticated tools like Splunk to correlate these events, identify patterns that indicate security threats, and respond to incidents before they become breaches.
But there’s often a glaring blind spot in this monitoring: the mainframe.
Mainframes generate some of the most security-relevant data in the enterprise—SMF records that track every system activity, RACF logs that document authentication and authorization events, job execution logs that show exactly what processing occurred when. Yet this data typically flows through separate processes, analyzed by different teams, on different timelines.
The PropelZ Splunk Connector changes this equation entirely, bringing mainframe security data into your existing SOC infrastructure in real-time.
The Mainframe Security Data Goldmine
Mainframes produce extraordinarily detailed audit data that security teams dream of having from other platforms:
- SMF Records: Complete system activity logs that track job executions, resource usage, file access, network connections, and performance metrics. Every significant system event generates an SMF record.
- RACF Security Logs: Authentication attempts, authorization decisions, privilege escalations, failed access attempts, and security policy violations—all logged with detailed context about users, resources, and outcomes.
- Console Messages: Real-time alerts about system conditions, security events, resource constraints, and operational issues that could indicate security problems.
- Job Control Logs: Detailed records of what jobs ran when, what resources they accessed, what outputs they generated—a complete audit trail of computational activity.
- System Integrity Data: Information about system modifications, security parameter changes, and administrative actions that could affect the security posture.
This data is incredibly valuable for security analysis, but it’s often trapped in mainframe-specific formats and processing systems.
Traditional Approaches: Batch Processing Limitations
Most mainframe security monitoring follows an outdated model:
- Batch Extraction: Security data is extracted from mainframe systems during scheduled batch windows—typically daily or weekly.
- Separate Analysis: Mainframe security data is analyzed using mainframe-specific tools, separate from the enterprise SOC infrastructure.
- Delayed Response: Security incidents involving mainframe data are discovered hours or days after they occur, when the next batch processing cycle completes.
- Manual Correlation: Correlating mainframe security events with distributed system events requires manual processes and specialized expertise.
- Compliance Focus: Analysis focuses on compliance reporting rather than real-time threat detection and response.
This approach misses the opportunity to leverage mainframe data for active security monitoring and incident response.
Real-Time Integration: Mainframe Data in Your SOC
PropelZ’s Splunk Connector transforms mainframe security monitoring by streaming structured data directly into your existing Splunk environment:
- Immediate Ingestion: SMF records, RACF logs, and other mainframe security data flow into Splunk as they’re generated—no batch delays, no processing windows.
- Structured Format: Raw mainframe data is transformed into structured formats that Splunk can index, search, and analyze using standard tools and dashboards.
- Context Preservation: All the rich metadata from mainframe security events—user IDs, resource names, timestamps, system contexts—is preserved and searchable.
- Unified Timeline: Mainframe security events appear in the same timeline as events from other systems, enabling correlation and pattern analysis across your entire infrastructure.
- Standard Tooling: Your SOC analysts can use the same Splunk searches, dashboards, and alerting rules for mainframe data that they use for other security data.
Use Cases: Real-Time Threat Detection
With mainframe data flowing into Splunk in real-time, security teams can implement sophisticated threat detection scenarios:
- Privilege Escalation Detection: Monitor RACF logs for unusual privilege escalations or administrative account usage. Correlate these events with network activity, application access patterns, and user behavior analytics to identify potential insider threats or compromised accounts.
- Lateral Movement Analysis: Track user sessions across mainframe and distributed systems simultaneously. Identify suspicious patterns where users authenticate to multiple systems in rapid succession or access resources outside their normal patterns.
- Data Exfiltration Monitoring: Correlate mainframe file access logs with network egress monitoring to identify potential data theft. SMF records showing large file accesses combined with unusual network activity can indicate data exfiltration attempts.
- Operational Anomaly Detection: Use mainframe job execution patterns to detect unusual system activity that could indicate malicious code execution, unauthorized process spawning, or system compromise.
- Compliance Violation Alerting: Generate real-time alerts when mainframe activities violate security policies—unauthorized file access, privilege abuse, system configuration changes, or access outside approved time windows.
Advanced Analytics: Machine Learning on Mainframe Data
Splunk’s machine learning capabilities become available for mainframe security data:
- Behavioral Baselines: Establish normal patterns for mainframe usage—typical job execution times, standard resource access patterns, regular user behavior—then alert on deviations.
- Anomaly Detection: Use statistical analysis to identify unusual patterns in SMF records, RACF logs, or system performance data that could indicate security incidents.
- Predictive Analytics: Analyze historical patterns to predict potential security issues before they occur—capacity constraints that could enable denial-of-service attacks, privilege creep that could lead to unauthorized access.
- Threat Hunting: Enable security analysts to hunt for advanced persistent threats by searching across years of mainframe security data using sophisticated queries and correlation techniques.
Incident Response: Complete Visibility
When security incidents occur, having mainframe data in Splunk provides comprehensive visibility:
- Timeline Reconstruction: Build complete timelines of security incidents that span mainframe and distributed systems, showing exactly what happened when and where.
- Impact Analysis: Quickly determine which mainframe resources were accessed, what data was potentially compromised, and what systems were affected.
- Evidence Collection: Gather digital evidence from mainframe systems using the same tools and procedures used for other platforms.
- Response Coordination: Coordinate incident response activities across mainframe and distributed system teams using shared data and common tools.
Compliance and Reporting: Automated Documentation
Real-time mainframe data in Splunk dramatically simplifies compliance reporting:
- Automated Reports: Generate compliance reports automatically using current data rather than waiting for batch processing cycles.
- Real-Time Dashboards: Provide compliance teams with real-time visibility into security metrics and policy violations.
- Audit Trail Preservation: Maintain complete, searchable audit trails that meet regulatory requirements for data retention and accessibility.
- Cross-Platform Reporting: Generate compliance reports that span mainframe and distributed systems, providing auditors with comprehensive views of security controls.
Implementation Considerations: Getting Started
Organizations implementing mainframe-to-Splunk integration should consider several factors:
- Data Volume Planning: Mainframes generate significant amounts of security data. Plan Splunk capacity accordingly and implement data lifecycle management policies.
- Network Bandwidth: Real-time streaming requires adequate network connectivity between mainframe and Splunk environments.
- Security Controls: Implement appropriate encryption, authentication, and authorization controls for security data in transit and at rest.
- Team Training: Ensure SOC analysts understand mainframe security events and how to interpret them within Splunk dashboards and searches.
- Alert Tuning: Start with conservative alerting policies and refine them based on operational experience to minimize false positives.
The ROI Calculation: Security Value Delivered
The business value of real-time mainframe security monitoring becomes clear when you consider the alternatives:
- Faster Incident Detection: Security incidents involving mainframe data are detected in minutes rather than days, reducing potential damage and compliance exposure.
- Reduced Investigation Time: Security analysts can investigate incidents using familiar tools and unified data rather than learning mainframe-specific systems.
- Improved Compliance Posture: Real-time monitoring and automated reporting reduce compliance risks and audit findings.
- Enhanced Threat Detection: Machine learning and advanced analytics applied to mainframe data identify threats that would be missed by traditional monitoring.
- Operational Efficiency: SOC teams handle mainframe security using existing skills and tools rather than requiring specialized mainframe security expertise.
Pricing and Deployment: Enterprise-Ready Solution
At $25,000 annually for z/OS environments, the Splunk Connector represents a strategic investment in enterprise security capabilities:
- Comprehensive Coverage: Includes both console logging and Splunk API integration—everything needed for complete mainframe security monitoring.
- Production Ready: Built for enterprise-scale deployments with appropriate security, reliability, and performance characteristics.
- Integration Support: Designed to work with existing Splunk deployments and security operations procedures.
- Ongoing Innovation: Regular updates and enhancements based on customer feedback and evolving security requirements.
What This Means for Your Security Program
If your organization operates mainframes and uses Splunk for security monitoring, the integration opportunity is significant:
- Close Security Gaps: Eliminate the blind spot that exists when mainframe security data flows through separate processes.
- Improve Threat Detection: Leverage advanced analytics and machine learning for mainframe security data.
- Accelerate Incident Response: Respond to security incidents using complete data and familiar tools.
- Strengthen Compliance: Meet regulatory requirements with real-time monitoring and automated reporting.
The result: a security program that provides comprehensive visibility across your entire infrastructure, not just the distributed systems.
Next Steps
- Watch the PropelZ Splunk demo.
- Watch the webinar PropelZ™ for PCI DSS 4.0: Accelerating Evidence Collection with Splunk.
- Schedule a PropelZ briefing.
- Try PropelZ.
Learn More
- Visit our Customer Briefing Center.
- Review all VirtualZ Use Cases, Thought Leadership papers, and Solution Briefs.
- Explore our YouTube channel, podcasts, and blog.
- Still have questions? Contact us.
