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.
When to Use
Trigger phrases:
"performing alert triage with elastic siem"
"Perform systematic alert triage in Elastic Security SIEM to rapidly classify, pr"
When conducting security assessments that involve performing alert triage with elastic siem
When following incident response procedures for related security events
When performing scheduled security testing or auditing activities
When validating security controls through hands-on testing
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
- Scope the task — define objectives, boundaries, and success criteria
- Gather information — collect all necessary data and context before proceeding
- Execute the core workflow — follow the domain-specific steps methodically
- Validate results — verify outputs against expected outcomes or baselines
- Document findings — record results, anomalies, and recommendations
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
This section covers detection rules for triage for performing alert triage with elastic siem.
- Ensure all prerequisites are met before proceeding
- Follow the documented workflow steps in sequence
- Record results and any anomalies encountered during this phase
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
This section covers ai-assisted triage for performing alert triage with elastic siem.
- Ensure all prerequisites are met before proceeding
- Follow the documented workflow steps in sequence
- Record results and any anomalies encountered during this phase
Elastic AI Assistant Integration
- Open alert in Elastic Security
- Click AI Assistant panel
- 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 |
When NOT to Use
- You don't have explicit written authorization to test
- Task is about defense/detection, not offense (use detection skills)
- You need to implement security controls (use implementing-* skills)
- Task requires compliance auditing (use auditing-* skills)
- You're investigating an incident (use incident response skills)
- Target is out of scope for your engagement
- Task is about vulnerability scanning only (use scanning tools)
Red Flags
- Performing actions without explicit written authorization from the asset owner
- Testing against production systems without a defined scope and rules of engagement
- Destroying potential evidence during the containment phase
- Failing to document the chain of custody for all collected artifacts
- Communicating incident details over unencrypted or monitored channels
Verification
- All steps executed successfully against a test environment before production use
- Output documented with screenshots or logs demonstrating expected behavior
- Timeline of events reconstructed with corroborating evidence
- Root cause identified and documented with contributing factors
- Post-incident review completed with lessons learned and action items
References
- Elastic Security - Triage Alerts Documentation
- SOC Analyst's Guide to Triage with Elastic
- Elastic Blog - AI and 2025 SIEM Landscape
- Reducing False Positives with Elastic and Tines
Process
- Analyze the task requirements
- Apply domain expertise
- Verify output quality
Anti-Rationalization Table
| Rationalization | Reality |
|---|---|
| "We are too small to be targeted" | Automated attacks target everyone. Size does not matter. |
| "Security slows us down" | A breach slows you down 100x more. Build security in from the start. |
| "We will fix it after launch" | Vulnerabilities in production are exploited within hours. Fix before deploy. |