Skills Development Elastic SIEM Alert Triage

Elastic SIEM Alert Triage

v20260317
performing-alert-triage-with-elastic-siem
Outlines a structured workflow inside Elastic Security SIEM for SOC analysts to triage alerts, investigate related activity with ES|QL queries, enrich findings via threat intelligence, and document escalation steps so teams can prioritize real threats and reduce noise.
Get Skill
394 downloads
Overview

Performing Alert Triage with Elastic SIEM

Overview

Alert triage in Elastic Security is the systematic process of reviewing, classifying, and prioritizing security alerts to determine which represent genuine threats. Elastic's AI-driven Attack Discovery feature can triage hundreds of alerts down to discrete attack chains, but skilled analyst triage remains essential. A structured triage workflow typically takes 5-10 minutes per alert cluster using Elastic's built-in tools.

Prerequisites

  • Elastic Security deployed (version 8.x or later)
  • Elastic Agent or Beats configured for endpoint and network data collection
  • Detection rules enabled and generating alerts
  • Elastic Common Schema (ECS) compliance across data sources
  • Analyst access to Kibana Security app with appropriate privileges

Alert Triage Workflow

Step 1: Initial Alert Assessment (2 minutes)

When viewing an alert in Elastic Security, review the alert details panel:

Alert Details Panel:
- Rule Name and Description
- Severity and Risk Score
- MITRE ATT&CK Mapping
- Host and User Context
- Process Tree (for endpoint alerts)
- Timeline of related events

Key Fields to Examine First

Field Purpose ECS Field
Rule severity Initial priority assessment kibana.alert.severity
Risk score Quantified threat level kibana.alert.risk_score
Host name Affected system host.name
User name Affected identity user.name
Process name Executing process process.name
Source IP Origin of activity source.ip
Destination IP Target of activity destination.ip
MITRE tactic Attack stage threat.tactic.name

Step 2: Context Gathering (3 minutes)

Query Related Events with ES|QL

FROM logs-endpoint.events.*
| WHERE host.name == "affected-host" AND @timestamp > NOW() - 1 HOUR
| STATS count = COUNT(*) BY event.category, event.action
| SORT count DESC

Find All Activity from Suspicious User

FROM logs-*
| WHERE user.name == "suspicious-user" AND @timestamp > NOW() - 24 HOURS
| STATS count = COUNT(*), unique_hosts = COUNT_DISTINCT(host.name) BY event.category
| SORT count DESC

Check for Related Alerts from Same Source

FROM .alerts-security.alerts-default
| WHERE source.ip == "10.0.0.50" AND @timestamp > NOW() - 24 HOURS
| STATS alert_count = COUNT(*) BY kibana.alert.rule.name, kibana.alert.severity
| SORT alert_count DESC

Investigate Lateral Movement from Same IP

FROM logs-system.auth-*
| WHERE source.ip == "10.0.0.50" AND event.outcome == "success"
| STATS login_count = COUNT(*), hosts = COUNT_DISTINCT(host.name) BY user.name
| WHERE hosts > 3

Step 3: Threat Intelligence Enrichment (2 minutes)

Check indicators against threat intelligence:

FROM logs-ti_*
| WHERE threat.indicator.ip == "203.0.113.50"
| KEEP threat.indicator.type, threat.indicator.provider, threat.indicator.confidence, threat.feed.name

Check File Hash Against Known Threats

FROM logs-endpoint.events.file-*
| WHERE file.hash.sha256 == "abc123..."
| STATS occurrences = COUNT(*) BY host.name, file.path, user.name

Step 4: Classification Decision (2 minutes)

Classification Criteria Action
True Positive Confirmed malicious activity Escalate to incident, begin containment
Benign True Positive Expected behavior matching rule Document in alert notes, acknowledge
False Positive Rule triggered on benign activity Mark as false positive, create tuning task
Needs Investigation Insufficient data for determination Assign for deeper investigation

Step 5: Documentation and Escalation (1 minute)

For each triaged alert, document:

  • Classification decision with rationale
  • Evidence artifacts examined
  • Related alerts or investigations
  • Recommended next steps

Detection Rules for Triage

Pre-Built Detection Rules

Elastic Security includes 1000+ pre-built detection rules organized by:

  • MITRE ATT&CK Tactic: Initial Access, Execution, Persistence, etc.
  • Platform: Windows, Linux, macOS, Cloud
  • Data Source: Endpoint, Network, Cloud, Identity

Custom Alert Correlation Rule

{
  "name": "Multiple Failed Logins Followed by Success",
  "type": "threshold",
  "query": "event.category:authentication AND event.outcome:failure",
  "threshold": {
    "field": ["source.ip", "user.name"],
    "value": 5,
    "cardinality": [
      {
        "field": "user.name",
        "value": 3
      }
    ]
  },
  "severity": "high",
  "risk_score": 73,
  "threat": [
    {
      "framework": "MITRE ATT&CK",
      "tactic": {
        "id": "TA0006",
        "name": "Credential Access"
      },
      "technique": [
        {
          "id": "T1110",
          "name": "Brute Force"
        }
      ]
    }
  ]
}

AI-Assisted Triage

Elastic AI Assistant Integration

  1. Open alert in Elastic Security
  2. Click AI Assistant panel
  3. Use quick prompts:
    • "Summarize this alert" - Get initial assessment
    • "Generate ES|QL query to find related activity" - Expand investigation
    • "What are the recommended response actions?" - Get playbook guidance
    • "Is this likely a false positive?" - Get AI confidence assessment

Attack Discovery

Elastic's Attack Discovery automatically:

  • Groups related alerts into attack chains
  • Maps alerts to MITRE ATT&CK kill chain stages
  • Filters false positives using ML models
  • Prioritizes based on business impact
  • Provides narrative summary of the attack

Triage Prioritization Matrix

Risk Score Severity Asset Criticality Response SLA
90-100 Critical High 15 minutes
70-89 High High 30 minutes
70-89 High Medium 1 hour
50-69 Medium Any 4 hours
21-49 Low Any 8 hours
1-20 Informational Any 24 hours

Triage Metrics and KPIs

Metric Target Measurement
Mean Time to Triage (MTTT) < 10 minutes Time from alert creation to classification
False Positive Rate < 30% False positives / total alerts
Escalation Rate 10-20% Escalated alerts / total alerts
Alert Coverage > 80% Triaged alerts / generated alerts per shift
Reclassification Rate < 5% Changed classifications / total classified

References

Info
Category Development
Name performing-alert-triage-with-elastic-siem
Version v20260317
Size 17.15KB
Updated At 2026-03-18
Language