Security Alert Triage logo

Security Alert Triage

Organization
elastic
security-alert-triage

Triage Elastic Security alerts — gather context, classify threats, create cases, and acknowledge. Use when triaging alerts, performing SOC analysis, or investigating detections.

Overview

Publisherelastic
Repositoryagent-skills
Skill namesecurity-alert-triage
Stars
589
Forks
53
Bundled files
6
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 6 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by elastic on GitHub. Read the source before you install it.

Installation

Install the Security Alert Triage AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/elastic/agent-skills/tree/main/plugins/security/skills/alert-triage
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/elastic/agent-skills.git /tmp/agent-skills
mkdir -p .claude/skills
cp -r /tmp/agent-skills/plugins/security/skills/alert-triage .claude/skills/security-alert-triage
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Security Alert Triage in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Security Alert Triage on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Security Alert Triage is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Alert Triage

Analyze Elastic Security alerts one at a time: gather context, classify, create a case, and acknowledge. This skill depends on the case-management skill for case creation.

Prerequisites

Install dependencies before first use from the skills/security directory:

bash
cd skills/security && npm install

Set the required environment variables (or add them to a .env file in the workspace root):

bash
export ELASTICSEARCH_URL="https://your-cluster.es.cloud.example.com:443"
export ELASTICSEARCH_API_KEY="your-api-key"
export KIBANA_URL="https://your-cluster.kb.cloud.example.com:443"
export KIBANA_API_KEY="your-kibana-api-key"

Quick start

All commands from workspace root. Always fetch → investigate → document → acknowledge. Call the tools directly — do not read the skill file or explore the workspace first.

bash
node skills/security/alert-triage/scripts/fetch-next-alert.js
node skills/security/case-management/scripts/case-manager.js find --tags "agent_id:<id>"
node skills/security/alert-triage/scripts/run-query.js --query-file query.esql --type esql
node skills/security/case-management/scripts/case-manager.js create --title "..." --description "..." --tags "classification:..." "agent_id:<id>" --severity <level> --yes
node skills/security/case-management/scripts/case-manager.js attach-alert --case-id <id> --alert-id <id> --alert-index <index> --rule-id <uuid> --rule-name "<name>" --yes
node skills/security/alert-triage/scripts/acknowledge-alert.js --related --agent <id> --timestamp <ts> --window 60 --yes

Common multi-step workflows

TaskTools to call (in order)
End-to-end triagefetch_next_alert → run_query (context) → case_manager create (case) → acknowledge_alert
Gather contextrun_query (process tree, network, related alerts)
Create case after classificationcase_manager create → case_manager attach-alert
Acknowledge after triageacknowledge_alert (related mode for batch)

Always complete the full workflow: fetch → investigate → document → acknowledge. Do not stop after gathering context — create or update a case with findings before acknowledging.

Critical execution rules:

  • Start executing tools immediately — do not read SKILL.md, browse the workspace, or list files first.
  • For ES|QL queries, write the query to a temporary .esql file then pass it via --query-file. Do not use edit_file — use a single shell call with echo "..." > query.esql && node ... --query-file query.esql.
  • Keep context gathering focused: run 2-4 targeted queries (process tree, network, related alerts), not 10+.
  • Report only what tools return. Copy identifiers verbatim — do not paraphrase IDs, timestamps, or hostnames.

Critical principles

  • Do NOT classify prematurely. Gather ALL context before deciding benign/unknown/malicious.
  • Most alerts are false positives, even if they look alarming. Rule names like "Malicious Behavior" or severity "critical" are NOT evidence.
  • "Unknown" is acceptable and often correct when evidence is insufficient.
  • MALICIOUS requires strong corroborating evidence: persistence + C2, credential theft, lateral movement — not only suspicious API calls.
  • Report tool output verbatim. Copy IDs, hostnames, timestamps, and counts exactly as returned by tools. Do not round numbers, abbreviate IDs, or paraphrase error messages.

Workflow

When triaging multiple alerts, group first, then triage each group:

text
- [ ] Step 0: Group alerts by agent/host and time window
- [ ] Step 1: Check existing cases
- [ ] Step 2: Gather full context (DO NOT SKIP)
- [ ] Step 3: Create or update case (only AFTER context gathered)
- [ ] Step 4: Acknowledge alert and all related alerts
- [ ] Step 5: Fetch next alert group and repeat

Step 0: Group alerts before triaging

When the user asks about multiple open alerts, group them first to avoid redundant investigation: query open alerts, group by agent.id, sub-group by time window (~5 min = likely one incident), triage each group as a single unit.

Use ES|QL for an overview (write to file first for PowerShell):

esql
FROM .alerts-security.alerts-*
| WHERE kibana.alert.workflow_status == "open" AND @timestamp >= "<start>"
| STATS alert_count=COUNT(*), rules=VALUES(kibana.alert.rule.name) BY agent.id
| SORT alert_count DESC

For full query templates, see references/classification-guide.md.

Step 1: Check existing cases

Before creating a new case, check if this alert belongs to an existing one. Use the case-management skill:

bash
node skills/security/case-management/scripts/case-manager.js find --tags "agent_id:<agent_id>"
node skills/security/case-management/scripts/case-manager.js cases-for-alert --alert-id <alert_id>

Look for cases with the same agent ID, user, or related detection rule within a similar time window.

Note: find --search may return 500 errors on Serverless. Use find --tags or list instead.

Step 2: Gather context

This is the most important step. Do not skip or shortcut it. Complete ALL substeps before forming any classification opinion.

Time range warning: Alerts may be days or weeks old. NEVER use relative time like NOW() - 1 HOUR. Extract the alert's @timestamp and build queries around that time with +/- 1 hour window.

Substeps: (2a) Related alerts on same agent/user; (2b) Rule frequency across env (high = FP-prone); (2c) Entity context — process tree, network, registry, files; (2d) Behavior investigation — persistence, C2, lateral movement, credential access.

Example — process tree (use ES|QL with KEEP; avoid --full which produces 10K+ lines):

esql
FROM logs-endpoint.events.process-*
| WHERE agent.id == "<agent_id>" AND @timestamp >= "<alert_time - 5min>" AND @timestamp <= "<alert_time + 10min>"
  AND process.parent.name IS NOT NULL
  AND process.name NOT IN ("svchost.exe", "conhost.exe", "agentbeat.exe")
| KEEP @timestamp, process.name, process.command_line, process.pid, process.parent.name, process.parent.pid
| SORT @timestamp | LIMIT 80
Data typeIndex pattern
Alerts.alerts-security.alerts-*
Processeslogs-endpoint.events.process-*
Networklogs-endpoint.events.network-*
Logslogs-*

For full query templates and classification criteria, see references/classification-guide.md.

Step 3: Create or update case

After gathering context, create a case and attach alert(s). Use --rule-id and --rule-name (required; 400 error without them):

bash
node skills/security/case-management/scripts/case-manager.js create \
  --title "<concise summary>" \
  --description "<findings, IOCs, attack chain, MITRE techniques>" \
  --tags "classification:<benign|unknown|malicious>" "confidence:<0-100>" "mitre:<technique>" "agent_id:<id>" \
  --severity <low|medium|high|critical>

node skills/security/case-management/scripts/case-manager.js attach-alert \
  --case-id <case_id> --alert-id <alert_id> --alert-index <index> \
  --rule-id <rule_uuid> --rule-name "<rule name>"

# Multiple alerts: attach-alerts --alert-ids <id1> <id2>
# Add notes: add-comment --case-id <id> --comment "Findings..."

Case description: Summary (1-2 sentences); Attack chain; IOCs (hashes, IPs, paths); MITRE techniques; Behavioral findings; Response context (remediation, credentials at risk).

Step 4: Acknowledge alerts

Acknowledge ALL related alerts together. Use --dry-run first to confirm scope, then run without it:

bash
# By host name — preferred when triaging a host
node skills/security/alert-triage/scripts/acknowledge-alert.js --query --host <hostname> --dry-run
node skills/security/alert-triage/scripts/acknowledge-alert.js --query --host <hostname> --yes

# By agent ID — preferred when agent.id is known
node skills/security/alert-triage/scripts/acknowledge-alert.js --related --agent <id> --timestamp <ts> --window 60 --dry-run
node skills/security/alert-triage/scripts/acknowledge-alert.js --related --agent <id> --timestamp <ts> --window 60 --yes

Increase --window for longer attack chains (e.g., 300 for 5 minutes). Report the exact count of acknowledged alerts from the tool output. Pass --yes to skip the confirmation prompt (required when called by an agent).

Step 5: Repeat

bash
node skills/security/alert-triage/scripts/fetch-next-alert.js

Tool reference

fetch-next-alert.js

Fetches the oldest unacknowledged Elastic Security alert.

bash
node skills/security/alert-triage/scripts/fetch-next-alert.js [--days <n>] [--json] [--full] [--verbose]

run-query.js

Runs KQL or ES|QL queries against Elasticsearch.

PowerShell warning: ES|QL queries contain pipe characters (|) which PowerShell interprets as shell pipes. ALWAYS use --query-file for ES|QL:

bash
# Write query to file, then run
node skills/security/alert-triage/scripts/run-query.js --query-file query.esql --type esql

KQL queries without pipes can be passed directly:

bash
node skills/security/alert-triage/scripts/run-query.js "agent.id:<id>" --index "logs-*" --days 7
ArgDescription
queryKQL query (positional)
--query-file, -qRead query from file (required for ES|QL on PowerShell)
--type, -tkql or esql (default: kql)
--index, -iIndex pattern (default: logs-*)
--size, -sMax results (default: 100)
--days, -dLimit to last N days
--jsonRaw JSON output
--fullFull document source

acknowledge-alert.js

Acknowledges alerts by updating workflow_status to acknowledged.

ModeCommand
Singlenode skills/security/alert-triage/scripts/acknowledge-alert.js <alert_id> --index <index> --yes
Relatednode skills/security/alert-triage/scripts/acknowledge-alert.js --related --agent <id> --timestamp <ts> [--window 60] --yes
By hostnode skills/security/alert-triage/scripts/acknowledge-alert.js --query --host <hostname> [--time-start <ts>] [--time-end <ts>] --yes
Querynode skills/security/alert-triage/scripts/acknowledge-alert.js --query --agent <id> [--time-start <ts>] [--time-end <ts>] --yes
Dry runAdd --dry-run to any mode (no confirmation needed)
ConfirmAll write modes prompt for confirmation; pass --yes to skip

Examples

  • "Fetch the next unacknowledged alert and triage it"
  • "Investigate alert ID abc-123 — gather context, classify, and create a case if malicious"
  • "Process the top 5 critical alerts from the last 24 hours"

Guidelines

  • Report only tool output — do not invent IDs, hostnames, IPs, or details not present in the tool response.
  • Preserve identifiers from the request — use exact values the user provides in tool calls and responses.
  • Confirm actions concisely using the tool's return data.
  • Distinguish facts from inference — label conclusions beyond tool output as your assessment.

Production use

  • All write operations (acknowledge-alert.js) prompt for confirmation. Pass --yes or -y to skip when called by an agent.
  • Use --dry-run before bulk acknowledgments to preview scope without modifying data.
  • The acknowledge script uses the Kibana Detection Engine API, which is compatible with both self-managed and Serverless deployments.
  • Verify environment variables point to the intended cluster before running any script — no undo for acknowledgments.

Environment variables

VariableRequiredDescription
ELASTICSEARCH_URLYesElasticsearch URL
ELASTICSEARCH_API_KEYYesElasticsearch API key
KIBANA_URLYesKibana URL (for case management)
KIBANA_API_KEYYesKibana API key (for case management)

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Security Alert Triage AI skill do?

Triage Elastic Security alerts — gather context, classify threats, create cases, and acknowledge. Use when triaging alerts, performing SOC analysis, or investigating detections.

Why use Security Alert Triage on TypingMind?

Because you install it once and use it with any model. Security Alert Triage is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Security Alert Triage in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/elastic/agent-skills/tree/main/plugins/security/skills/alert-triage. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Security Alert Triage?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Security Alert Triage?

As many as you like. As long as a model supports skills, you can use Security Alert Triage with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Security Alert Triage AI skill free?

Yes. It is published on GitHub by elastic under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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