Information is correlated from multiple sources
Sophisticated attacks rarely trigger a single high-confidence alert. They generate low-confidence signals across multiple systems: one failed login here, one unusual process there, one unexpected outbound connection. Correlation is the practice of connecting these dots: combining signals from different sources to reveal a pattern that is invisible when each signal is viewed in isolation. Organizations that analyze each alert independently miss multi-stage attacks that become obvious in aggregate.
Implementation steps
- 1
Centralize logs from all security-relevant sources
Ensure that all security-relevant log sources feed into a single platform where they can be correlated: endpoint logs, network logs, authentication logs, application logs, cloud service logs, and DNS logs. Standardize timestamps to UTC and normalize field names across sources so that cross-source queries work reliably. Identify any log source gaps and close them.
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Implement multi-source correlation rules
Write correlation rules that span multiple log sources: a rule that fires when the same user has a failed login from one location followed by a successful login from a different country within an hour; a rule that fires when a host makes a connection to a newly registered domain shortly after receiving an email with a link. These compound detections require all relevant data to be present and queryable together.
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Integrate threat intelligence feeds for enrichment and correlation
Subscribe to threat intelligence feeds that provide indicators of compromise (IOCs): known malicious IP addresses, domains, file hashes, and attack patterns. Automatically enrich security events with this intelligence and write rules that trigger when any event matches a known IOC. This enables correlation between your internal activity and global threat data, catching known-bad infrastructure before you have observed malicious behavior from it.
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Evidence required
Log source inventory and centralization evidence
Evidence that logs from multiple sources are aggregated in a common platform for correlation.
- · SIEM data source inventory listing all connected log sources
- · Log pipeline configuration showing normalization and routing
- · Coverage assessment showing percentage of critical assets with logs flowing
Correlation rule configuration
Evidence that multi-source correlation rules are implemented and active.
- · SIEM detection rule library showing cross-source correlation logic
- · Threat intelligence integration configuration
- · Sample correlation alert demonstrating multi-source analysis
Related controls
Alert thresholds are established
Adverse Event Analysis
Cyber threat intelligence and other contextual information are integrated into the analysis
Adverse Event Analysis
Networks and network services are monitored to detect adverse events
Continuous Monitoring
Computing hardware and software, runtime environments, and their data are monitored to find potentially adverse events
Continuous Monitoring