Security Generate Security Sample Data logo

Security Generate Security Sample Data

Organization
elastic
security-generate-security-sample-data

Generate sample security events, attack scenarios, and synthetic alerts for Elastic Security. Use when demoing, populating dashboards, testing detection rules, or setting up a POC.

Overview

Publisherelastic
Repositoryagent-skills
Skill namesecurity-generate-security-sample-data
Stars
589
Forks
53
Bundled files
5
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.

  • 5 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 Generate Security Sample Data 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/generate-security-sample-data
  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/generate-security-sample-data .claude/skills/security-generate-security-sample-data
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Security Generate Security Sample Data 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 Generate Security Sample Data 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 Generate Security Sample Data 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.

Generate Security Sample Data

Generate ECS-compliant security events, multi-step attack scenarios, and synthetic alert documents that populate Elastic Security dashboards, the Alerts tab, and Attack Discovery.

Quick start

For a zero-friction experience that generates everything and opens Kibana:

bash
node skills/security/generate-security-sample-data/scripts/demo-walkthrough.js

Workflow

text
- [ ] Step 1: Set environment variables
- [ ] Step 2: Generate sample data
- [ ] Step 3: Explore in Kibana
- [ ] Step 4: Clean up when done

Step 1: Set environment variables

bash
export ELASTICSEARCH_URL="https://your-project.es.region.aws.elastic.cloud"
export ELASTICSEARCH_USERNAME="admin"
export ELASTICSEARCH_PASSWORD="your-password"
export KIBANA_URL="https://your-project.kb.region.aws.elastic.cloud"

Step 2: Generate sample data

Generate everything at once
bash
node skills/security/generate-security-sample-data/scripts/sample-data.js \
  system endpoint okta aws windows --scenarios --alerts
Generate only events
bash
node skills/security/generate-security-sample-data/scripts/sample-data.js \
  system endpoint --count 100
Generate only attack scenarios
bash
node skills/security/generate-security-sample-data/scripts/sample-data.js --scenarios
Generate only synthetic alerts
bash
node skills/security/generate-security-sample-data/scripts/sample-data.js --alerts

Step 3: Explore in Kibana

After generating data, direct the user to these pages:

  • Security > Alerts — synthetic alerts with MITRE ATT&CK mappings
  • Security > Attack Discovery — requires an LLM connector to analyze alerts
  • Security > Hosts — host activity from sample events
  • Security > Overview — summary of all security data
  • Discover — raw events across all data streams

Step 4: Clean up when done

bash
node skills/security/generate-security-sample-data/scripts/sample-data.js --cleanup

What gets generated

Sample data spans 5 packages (system, endpoint, windows, aws, okta) and 4 focused attack scenarios covering the most common demo themes: Windows credential theft, AWS cloud privilege escalation, Okta identity takeover, and a full ransomware kill chain. Synthetic alert documents are indexed into .alerts-security.alerts-default with MITRE ATT&CK mappings, severity levels, and risk scores.

All events use RFC 5737 / RFC 2606 safe addresses. For full tables of packages, scenarios, and alerts see references/sample-data-reference.md.

Continuous mode

Stream events to simulate a live environment:

bash
node skills/security/generate-security-sample-data/scripts/sample-data.js \
  --continuous --interval 15

Every 5th batch includes an attack scenario; every 10th batch adds synthetic alerts. Press Ctrl+C to stop.

Tool reference

sample-data.js

FlagDescription
--count, -nEvents per package (default: 50)
--scenariosRun all attack simulation scenarios
--scenario NAMERun a specific scenario
--alertsGenerate synthetic alert documents
--cleanupRemove all sample data and alerts
--continuousStream live events (Ctrl+C to stop)
--interval NSeconds between continuous batches (default: 30)
--json, -jOutput results as JSON
--yes, -ySkip confirmation prompts

demo-walkthrough.js

Zero-friction runner that generates everything and opens Kibana.

FlagDescription
--cleanupRemove all sample data, alerts, case
--continuousGenerate then stream live events
--count NEvents per package (default: 50)
--interval NSeconds between batches (default: 30)

Examples

Quick demo for a stakeholder

"Set up a demo environment so I can show Attack Discovery to my VP."

bash
node skills/security/generate-security-sample-data/scripts/demo-walkthrough.js

Targeted scenario testing

"Generate only the ransomware attack chain to test our detection rules."

bash
node skills/security/generate-security-sample-data/scripts/sample-data.js \
  --scenario ransomwareChain --alerts

Simulating a live SOC

"Keep generating events so the dashboards stay active during the demo."

bash
node skills/security/generate-security-sample-data/scripts/demo-walkthrough.js --continuous

Cleaning up after a demo

"Remove all sample data from my project."

bash
node skills/security/generate-security-sample-data/scripts/sample-data.js --cleanup

Guidelines

  • All generated documents are tagged with tags: ["elastic-security-sample-data"] for safe cleanup. The cleanup command only deletes documents with this marker.
  • If marker fields are not indexed in a data stream, cleanup falls back to scanning _source.tags for matching sample documents from the last 14 days.
  • Synthetic alerts are indexed directly into .alerts-security.alerts-default — they do not require detection rules to be installed or enabled.
  • Attack Discovery requires an LLM connector (OpenAI, Anthropic, Google Gemini, or similar) configured in Kibana under Stack Management > Connectors. The "Complete" project tier unlocks the feature, but the connector must be set up separately.
  • Use the case-management skill for creating investigation cases from alerts.

Production use

  • Do not run against production clusters unless you intend to inject synthetic data alongside real alerts. Sample events and alerts are tagged for cleanup but will appear in dashboards, the Alerts tab, and Attack Discovery alongside real data.
  • All write operations (generate, --cleanup, --continuous) prompt for confirmation. Pass --yes or -y to skip when called by an agent.
  • --cleanup runs deleteByQuery across all sample data indices — verify environment variables point to the intended cluster before running.
  • --continuous mode indexes events indefinitely until manually stopped with Ctrl+C.

Environment variables

VariableRequiredDescription
ELASTICSEARCH_URLYesElasticsearch URL
ELASTICSEARCH_API_KEYYes*Elasticsearch API key
ELASTICSEARCH_USERNAMEYes*Elasticsearch username (alternative)
ELASTICSEARCH_PASSWORDYes*Elasticsearch password (alternative)
KIBANA_URLNoKibana URL (for case creation and links)
KIBANA_USERNAMENoKibana username (if using Kibana features)
KIBANA_PASSWORDNoKibana password (if using Kibana features)

*Either API key or username/password is required for Elasticsearch.

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 Generate Security Sample Data AI skill do?

Generate sample security events, attack scenarios, and synthetic alerts for Elastic Security. Use when demoing, populating dashboards, testing detection rules, or setting up a POC.

Why use Security Generate Security Sample Data on TypingMind?

Because you install it once and use it with any model. Security Generate Security Sample Data 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 Generate Security Sample Data in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/elastic/agent-skills/tree/main/plugins/security/skills/generate-security-sample-data. 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 Generate Security Sample Data?

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 Generate Security Sample Data?

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

Is the Security Generate Security Sample Data 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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