When you start as a Tier 1 SOC analyst, the SIEM is your primary workspace. Here is what a typical shift looks like:
1. Check the Dashboard
Review open alerts sorted by severity. Check alert volume — is today normal or is there a spike? Note any alerts assigned to you from the previous shift.
2. Triage Alerts
For each alert: read the rule that fired, check source/destination, look at the raw logs, determine true positive vs false positive. Document your finding.
3. Investigate
For confirmed true positives: pivot on the source IP across all log sources. Check if the same IP triggered other alerts. Build a timeline. Determine scope.
4. Escalate or Close
If you can handle it, contain and document. If it exceeds your scope, escalate to Tier 2 with your findings, timeline, and recommended next steps.
Common SIEM Search Patterns
Splunk: index=firewall src_ip="10.0.5.102" action=deny | stats count by dest_ip Sentinel: SecurityEvent | where EventID == 4625 | summarize count() by TargetAccount Elastic: event.action:"denied" AND source.ip:"10.0.5.102"
SIEM Data Pipeline
Click each stage to learn how data flows through a SIEM:
Collection
→
Parsing
→
Normalization
→
Correlation
→
Alerting
SIEM Correlation in Action
Correlation is the SIEM's superpower — connecting related events across systems to identify attacks. Here's an example:
Scenario: Detecting Password Spray Attack
The SIEM receives these events from different sources:
[10:15:01] auth.log | Failed login for user 'jsmith' from 192.168.1.50
[10:15:02] auth.log | Failed login for user 'mjones' from 192.168.1.50
[10:15:03] auth.log | Failed login for user 'twilliams' from 192.168.1.50
[10:15:04] auth.log | Successful login for user 'admin' from 192.168.1.50