Security Alert Triage
ElasticOfficialCreated by elastic
- Skill
- Workflow
- Security
- Apache-2.0
- No issues found
AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
This skill provides a structured approach to triaging the Elastic Security alert queue. It calculates a weighted risk score for alerts based on base risk, MITRE tactics, workflow status, entity risk, and asset criticality. By clustering alerts into entity groups, it helps security analysts identify the most urgent threats to focus on at the start of their shift or during active monitoring.
What it does
- Calculates weighted risk scores for security alerts.
- Clusters individual alerts into entity-based groups.
- Applies boosts for MITRE tactics, entity risk, and asset criticality.
- Adjusts scores based on alert workflow status (e.g., acknowledged or in a case).
- Provides a ranked list of the top 10 entity groups for immediate attention.
- Returns the top alert ID for each group to facilitate further investigation.
When to use it
- When an analyst needs to know which alerts are most urgent.
- When starting a shift and requiring a prioritized starting point.
- When prioritizing a specific set of alert IDs.
- When filtering the queue by a specific time window.
Advantages
- Reduces noise by clustering related alerts into entity groups.
- Provides a clear, data-driven rationale for alert prioritization.
- Integrates contextual data like asset criticality and entity risk.
- Maintains a read-only stance to prevent accidental state changes.
- Offers a consistent scoring model across the security queue.
Usage examples
- “What should I focus on right now?”
- The agent analyzes the last 24 hours of open alerts, clusters them by entity, applies risk boosts, and returns a ranked list of the top 10 groups with their respective scores and top alert IDs.
- “Prioritize these alerts: [alert_id_1, alert_id_2]”
- The agent fetches the specific alerts provided, calculates their weighted risk scores, and presents them in a ranked order, ignoring standard time-window filters.
- “Prioritize the queue. Include acknowledged alerts.”
- The agent performs the standard triage process but expands the scope to include both open and acknowledged alerts in the final ranking.
Install
Download the skill as a ZIP:
https://autogineer.com/agent-skills/elastic/security-alert-triage/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip security-alert-triage.zip -d .agents/skills
Documentation by elastic
Alert Triage
Prioritize the Elastic Security alert queue by weighted risk and return ranked entity groups — a starting point before investigation begins, not an investigation itself.
<!-- begin-partial: preamble -->
Environment Configuration
This skill executes Elasticsearch operations through the elastic CLI. If the
elastic CLI is not installed, tell the user what it is needed for. Do
not guess credentials, call the HTTP API directly, or attempt other workarounds.
This skill references operations in HTTP-shorthand form (e.g., GET /, GET /_cat/indices, GET /{index}/_mapping,
GET /{index}/_settings/index.mode, POST /_query). The Operations table at the end of this document
maps each shorthand to the equivalent elastic CLI command — always use the CLI rather than calling the HTTP API
directly.
<!-- end-partial: preamble -->
When to use this skill
Use this skill when:
An analyst asks "what should I focus on right now?" or "which alerts are most urgent?"
An analyst wants to prioritize the queue for a specific time window (for example, "last 8 hours")
An analyst provides a set of alert IDs and asks "which of these are most important?"
An analyst is starting a shift and needs a ranked starting point before investigation begins
Do not use this skill to investigate a single known alert — use the security-alert-analysis skill for that. This skill does not acknowledge alerts, create cases, or gather per-alert context. Those actions belong in the investigation phase.
Scoring model
The score for each alert is computed as:
alert_score = base_risk_score + mitre_boost + status_modifier
group_score = MAX(alert_score across group) + entity_risk_boost + asset_criticality_boostThe weights, mirroring the Kibana Agent Builder alert-triage skill, are:
| Signal | Level | Boost |
|---|---|---|
| MITRE tactic | Exfiltration, Impact, Command and Control, Lateral Movement | +30 |
| MITRE tactic | Credential Access, Privilege Escalation, Defense Evasion | +20 |
| MITRE tactic | Persistence, Execution, Initial Access | +10 |
| Workflow status | Alert is acknowledged | −5 |
| Workflow status | Alert already attached to a case (kibana.alert.case_ids is non-empty) | −5 |
| Entity Analytics risk | Critical | +25 |
| Entity Analytics risk | High | +15 |
| Entity Analytics risk | Moderate | +5 |
| Asset criticality | extreme_impact | +20 |
| Asset criticality | high_impact | +12 |
| Asset criticality | medium_impact | +6 |
Status modifiers are additive: an acknowledged alert already in a case receives −10 total. Entity Analytics enrichment is best-effort; when the Risk Engine or asset criticality index is absent, both boosts are 0 and scoring continues normally.
Process
Step 1 — Establish scope
Decide:
Time window: default 24 hours, range 1–168 hours.
Workflow filter:
"open"(default) or"open+acknowledged"to include acknowledged alerts.Specific alert IDs: when the user supplies alert IDs, score exactly those and skip the time-window and workflow-status filters so a selected alert is never silently dropped regardless of age or status.
Data needed: time window or alert IDs; workflow scope.
Step 2 — Fetch and score the queue
Run one POST /_query with ES|QL. Elasticsearch computes every score field; no arithmetic is needed after the query
returns.
Queue path (no explicit IDs):
FROM .alerts-security.alerts-* METADATA _id, _index
| WHERE kibana.alert.workflow_status == "open"
AND @timestamp >= NOW() - 24 hours
AND kibana.alert.building_block_type IS NULL
| EVAL tactics = COALESCE(MV_CONCAT(kibana.alert.rule.threat.tactic.name, "|"), "")
| EVAL mitre_boost = CASE(
tactics LIKE "*Exfiltration*" OR tactics LIKE "*Impact*"
OR tactics LIKE "*Command and Control*" OR tactics LIKE "*Lateral Movement*", 30,
tactics LIKE "*Credential Access*" OR tactics LIKE "*Privilege Escalation*"
OR tactics LIKE "*Defense Evasion*", 20,
tactics LIKE "*Persistence*" OR tactics LIKE "*Execution*"
OR tactics LIKE "*Initial Access*", 10,
0)
| EVAL status_modifier = CASE(kibana.alert.workflow_status == "acknowledged", -5, 0)
+ CASE(kibana.alert.case_ids IS NULL, 0, -5)
| EVAL alert_score = COALESCE(kibana.alert.risk_score, 0) + mitre_boost + status_modifier
| EVAL entity = CASE(
host.name IS NOT NULL, CONCAT("host:", MV_FIRST(host.name)),
user.name IS NOT NULL, CONCAT("user:", MV_FIRST(user.name)),
CONCAT("ungrouped:", _id))
| KEEP _id, _index, @timestamp, entity, host.name, user.name, kibana.alert.rule.name,
kibana.alert.severity, kibana.alert.workflow_status, kibana.alert.risk_score,
mitre_boost, status_modifier, alert_score
| SORT alert_score DESC, @timestamp DESC
| LIMIT 100For the explicit-IDs path, replace the WHERE clause with WHERE _id IN ("<id1>", "<id2>", ...) and keep all other
stages, but raise LIMIT to the number of IDs (maximum 500) so a selected alert is never truncated. This path also
drops the building-block exclusion on purpose: an alert the analyst selects explicitly is always scored, even if it is a
building block. Kibana keeps that filter on both paths.
For "open+acknowledged" scope, change kibana.alert.workflow_status == "open" to
kibana.alert.workflow_status IN ("open", "acknowledged").
Query design notes:
METADATA _idis required. The top alert_idper group is mandatory output — analysts use it to hand off to investigation or file a case directly.kibana.alert.building_block_type IS NULLexcludes building-block alerts (sub-components of parent alerts) the same way the Kibana skill does withmust_not exists.MV_FIRSTonhost.name/user.namegives a stable group key when a field has multiple values.CASEtiers are ordered 30 → 20 → 10, so the first match wins. This reproduces Kibana's per-tactic maximum without an elementwise operation.kibana.alert.rule.threat.tactic.nameis a flatkeywordfield in the alerts mapping.MV_CONCATcollapses any multi-value results into one string thatLIKEcan match across all values.
Data needed: scored alert rows with entity key, top alert _id, and score breakdown.
Step 3 — Cluster into entity groups
Rows arrive sorted by alert_score descending. For each distinct entity value, the first row is the group's top
alert and the row count is alert_count. Group by entity value.
Kibana uses a transitive union-find algorithm, so an alert that mentions both host A and user B merges both into one group. This skill keys on the primary entity (host first, then user) to match Kibana's primary-entity selection while keeping the ES|QL approach simple. Groups may differ from Kibana's on alerts that bridge a host and a user; document this if analysts report discrepancies.
Kibana also applies entity risk and asset criticality boosts to every group before it takes the top 10. This skill selects the top 10 by base score and then enriches only those, so a group ranked 11th or lower on base score can't surface through enrichment boosts. Document this if analysts report a missing high-criticality group.
Return at most 10 ranked groups — the long tail is not useful at the prioritization stage.
Data needed: per-entity group with alert_count, top alert _id, top rule name, severity, and alert_score breakdown
(base + MITRE boost + status modifier).
Step 4 — Enrich the top groups (best-effort)
Before querying Entity Analytics, preflight each index with GET /_resolve/index/{pattern}. If either index is absent
or returns no results, skip the corresponding boost (set to 0) and continue.
When the Risk Engine is available, look up the primary entity of each of the top 10 groups:
FROM risk-score.risk-score-latest-*
| WHERE host.name IN ("<host1>", "<host2>") OR user.name IN ("<user1>", "<user2>")
| KEEP host.name, host.risk.calculated_level, host.risk.calculated_score_norm,
user.name, user.risk.calculated_level, user.risk.calculated_score_norm
| LIMIT 50When asset criticality is available:
FROM .asset-criticality.asset-criticality-*
| WHERE (id_field == "host.name" AND id_value IN ("<host1>", "<host2>"))
OR (id_field == "user.name" AND id_value IN ("<user1>", "<user2>"))
| KEEP id_field, id_value, criticality_level
| LIMIT 50Add the entity risk boost and asset criticality boost to each group's score using the weight table above. Re-sort the
ten groups by updated group_score.
When an entity enrichment re-ranks a group above a higher base-score peer, explain why: cite the entity risk level and asset criticality boost explicitly.
Data needed: entity risk level and asset criticality for the primary entity of each top group.
Step 5 — Rank and report
Sort the ten groups by group_score descending. Summarize the top 2–3 groups in detail; list the remaining groups
briefly.
For each top group, report:
The entity or context (for example, "4 alerts on host WIN-SRV01")
The group score and what drove it (base risk + MITRE boost + entity risk + asset criticality)
The primary entity's risk level and asset criticality when present (copy values verbatim, for example
Critical,extreme_impact)Whether any alerts are acknowledged or already in a case (with the score modifier noted)
The top alert rule names in the group
The top alert
_idverbatim — this is mandatory, not optional
End with a brief summary of the total alerts assessed and the number of groups identified.
Recommend the security-alert-analysis skill by name as the next step for any group the analyst wants to investigate further.
Guidelines
This skill is read-only. Do not acknowledge alerts, create cases, or run investigation queries. All writes belong in security-alert-analysis.
Do not deep-investigate. Prioritization is the output; investigation is the next step.
Copy identifiers verbatim.
entityRiskLevel,assetCriticality,entityName, and alert_ids must be copied exactly from tool output. Do not paraphrase level names or abbreviate IDs.Explain re-rankings. When entity enrichment lifts a group above a peer with a higher base score, explain why — cite the specific boost components.
Acknowledged alerts are deprioritized, not hidden. Flag the −5 modifier and surface the group.
Building-block alerts are excluded automatically by the
kibana.alert.building_block_type IS NULLfilter.If the queue is empty, tell the analyst no open alerts match the criteria and suggest widening the time window or changing the workflow scope.
Examples
Query: "What should I focus on right now?"
Scope: { timeWindowHours: 24, workflowStatus: "open" }. Run the queue path, cluster, enrich, and return the top 10
groups.
Query: "Prioritize alerts from the last 8 hours"
Scope: { timeWindowHours: 8, workflowStatus: "open" }. Adjust the @timestamp filter to >= NOW() - 8 hours.
Query: "Which of these alerts should I look at first?" (with alert IDs)
Scope: { alertIds: ["<id1>", "<id2>", ...] }. Use the explicit-IDs path so a selected alert that is acknowledged or
old is never silently dropped.
Query: "Prioritize the queue. Include acknowledged alerts."
Scope: { timeWindowHours: 24, workflowStatus: "open+acknowledged" }. Adjust the workflow filter in the ES|QL WHERE
clause.
Response format
Present results as ranked groups. The top alert _id is required in every group — analysts use it to hand off to
investigation directly.
**Group 1 — [entity or context]** (score: N)
- Alerts: N alerts | Top rule: [rule name] | Severity: critical/high
- Score drivers: base risk [N] + MITRE tactic boost [+N, tactic name] + entity risk [+N, level] + asset criticality [+N, level]
- Entity signals: risk level [Critical/High/…], asset criticality [extreme_impact/…] (omit if unavailable)
- Status: [N acknowledged (−5 each), N in a case (−5 each)] (omit if none)
- **Top alert ID: [exact _id from the query result]**
- Recommended next step: investigate with security-alert-analysis
**Group 2 — [entity or context]** (score: N)
…End with: "Total alerts assessed: N across M groups."
References
Operations
| HTTP API (shorthand) | elastic CLI command |
|---|---|
POST /_query | elastic es esql query --format tsv --query '<esql>' |
GET /_resolve/index/{pattern} | elastic es indices resolve-index --name '<pattern>' |
This skill is read-only. Acknowledgement and case management operations are deliberately not bound here — use the security-alert-analysis skill for those operations.
Files
- ATTRIBUTION.mdAdded by AutoGineer958 B
- LICENSELicence file added by AutoGineer11.1 KiB
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Requirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
The author says: Kibana 8.x or 9.x with matching Elasticsearch — self-managed, Elastic Cloud Hosted, or Elastic Cloud Serverless. Read-only: no alerts are acknowledged, updated, or moved during this skill. Entity Analytics enrichment is optional and degrades cleanly when the Risk Engine or asset criticality data is unavailable. Requires the `elastic` CLI with `es` support.
Security
No issues found by our static scan· No issues found
A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.
Attribution and licence
- Created by
- elastic
- Publisher
- Elastic (Official)
- Source
- elastic/agent-skills · skills/security/alert-triage · commit 09d879d
- Licence
- Apache License 2.0 (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
- Also distributed in
- elastic/agent-skills
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