SIEM Fundamentals

Security Information and Event Management platforms serve as the technological foundation of most security operations. SIEM systems collect logs from across your environment, normalize them into consistent formats, and provide the search and correlation capabilities that enable analysts to detect and investigate threats.

What SIEM Does

At its core, a SIEM solves the log aggregation problem. Large organizations generate millions of log events daily across hundreds or thousands of systems. No analyst could manually review logs from each system individually. SIEM brings these logs together, making centralized analysis possible.

Beyond aggregation, SIEMs normalize data into consistent formats. A login event from a Windows domain controller looks different from one generated by a Linux SSH server or a cloud IAM service. Normalization ensures analysts can search for "authentication failures" regardless of the source system's native log format.

Correlation represents the analytical power that distinguishes SIEM from simple log storage. Rules define patterns that indicate security concerns—multiple failed logins followed by success might indicate password guessing. A rare process execution on a critical server might reveal malware. These correlation rules transform raw events into actionable alerts.

SIEM Components

Modern SIEM platforms consist of several cooperating components. Understanding this architecture helps you troubleshoot issues and optimize performance.

Data collection begins at the source, where agents or forwarders capture log data and transmit it to central components. Syslog serves as a traditional collection protocol, while modern platforms often use proprietary agents with additional capabilities.

Indexers receive incoming data, parse it according to predefined formats, and store it in searchable indices. Index design affects both search performance and storage efficiency. Fields extracted during indexing enable powerful queries without full-text searching through raw logs.

Search heads provide the interface analysts use to query data, create dashboards, and investigate incidents. In distributed deployments, search heads coordinate queries across multiple indexers, combining results into unified views.

Working with SIEM Data

Effective use of a SIEM requires understanding its query language and capabilities. Whether you're using Splunk's SPL, Elastic's query language, or another platform's syntax, the concepts remain similar.

Filtering narrows results to relevant events. Selecting only authentication logs, only events from specific hosts, or only warnings and errors reduces noise and focuses your investigation. Time ranges are particularly important—most investigations focus on specific windows when suspicious activity occurred.

Field extraction and aggregation transform raw events into useful summaries. Counting authentication failures by user identifies accounts under attack. Grouping network connections by destination reveals command-and-control communication patterns.

Visualization makes patterns visible that might be invisible in tabular data. Charts showing event volumes over time reveal anomalies. Geographic maps plot connection destinations. Relationship diagrams show how entities interact.