| name | sec-alerts-splunk |
| description | Triages security alerts in Splunk Enterprise Security by classifying severity, investigating notable events, correlating related telemetry, and making escalation or closure decisions using SPL queries and the Incident Review dashboard. Use when SOC analysts face queued alerts from correlation searches, need to prioritize investigation order, or must document triage decisions for handoff to Tier 2/3 analysts.
|
| domain | cybersecurity |
| subdomain | soc-operations |
| tags | ["soc","splunk","alert-triage","siem","notable-events","correlation-search","incident-review"] |
| version | 1.0 |
| author | mahipal |
| license | Apache-2.0 |
| nist_csf | ["DE.CM-01","DE.AE-02","RS.MA-01","DE.AE-06"] |
Triaging Security Alerts in Splunk
When to Use
Use this skill when:
- SOC Tier 1 analysts need to process the Incident Review queue in Splunk Enterprise Security (ES)
- Notable events require rapid severity classification and initial investigation before escalation
- Alert volume exceeds capacity and analysts need a systematic triage methodology
- Management requests metrics on alert disposition (true positive, false positive, benign)
Do not use for deep forensic investigation — escalate to Tier 2/3 after initial triage confirms malicious activity.
Prerequisites
- Splunk Enterprise Security 7.x+ with Incident Review dashboard configured
- CIM-normalized data sources (Windows Event Logs, firewall, proxy, endpoint)
- Role with
ess_analyst capability for notable event status updates
- Familiarity with SPL (Search Processing Language)
Workflow
Step 1: Access Incident Review and Prioritize Queue
Open the Incident Review dashboard in Splunk ES. Sort notable events by urgency (calculated from severity x priority). Apply filters to focus on unassigned events:
| `notable`
| search status="new" OR status="unassigned"
| sort - urgency
| table _time, rule_name, src, dest, user, urgency, status
| head 50
Focus on Critical and High urgency events first. Group related alerts by src or dest to identify attack chains rather than treating each alert independently.
Step 2: Investigate the Notable Event Context
For each notable event, pivot to raw events. Example for a brute force alert:
index=wineventlog sourcetype="WinEventLog:Security" EventCode=4625
src_ip="192.168.1.105"
earliest=-1h latest=now
| stats count by src_ip, dest, user, status
| where count > 10
| sort - count
Check if the source IP is internal (lateral movement) or external (perimeter attack). Cross-reference with asset and identity lookups:
| `notable`
| search rule_name="Brute Force Access Behavior Detected"
| lookup asset_lookup_by_cidr ip AS src OUTPUT category, owner, priority
| lookup identity_lookup_expanded identity AS user OUTPUT department, managedBy
| table _time, src, dest, user, category, owner, department
Step 3: Correlate Across Data Sources
Check if the same source appears in other telemetry:
index=proxy OR index=firewall src="192.168.1.105" earliest=-24h
| stats count by index, sourcetype, action, dest_port
| sort - count
