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Wazuh Active Response

Organization
gensecaihq
wazuh-active-response

How Wazuh active response actually works — commands, agent-side scripts, dispatch vs execution, permanence, blast radius, pre-checks and verification caveats — for planning and verifying containment; use before proposing or verifying any response action.

Overview

Publishergensecaihq
RepositoryWazuh-Autopilot
Skill namewazuh-active-response
Stars
61
Forks
15
Bundled files
Instructions only
LicenseMIT
Links
Skill sourceRepositoryHomepage
  • 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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Wazuh Active Response 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/gensecaihq/Wazuh-Autopilot/tree/main/backend/app/skills/wazuh-active-response
  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/gensecaihq/Wazuh-Autopilot.git /tmp/Wazuh-Autopilot
mkdir -p .claude/skills
cp -r /tmp/Wazuh-Autopilot/backend/app/skills/wazuh-active-response .claude/skills/wazuh-active-response
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Wazuh Active Response 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 Wazuh Active Response 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 Wazuh Active Response 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.

Wazuh Active Response

Agents never execute actions. The response-planner proposes (propose_action); the autonomy policy and human approvers decide; the platform executor calls the Wazuh MCP action tool; the responder verifies. This skill explains what happens underneath so plans are realistic and verification is honest.

How Wazuh AR works

  1. The Wazuh API (via the MCP server) sends an active-response command to one or more agents.
  2. The agent runs a script of that name from its active-response bin directory. If the script isn't deployed on that agent, nothing happens on the host.
  3. The API returns as soon as the manager accepts and dispatches the command ("AR command was sent to the agent") — this is not proof of execution.
  4. The script logs its outcome; Wazuh turns that log into an alert in the active_response group.
  5. API-triggered AR is permanent: Wazuh ignores the timeout for API-triggered commands, so a block stays until explicitly removed (rollback), unlike rule-triggered AR with a timeout.

What each platform action sends

Platform actionMCP toolAR commandStock script?Rollback
block_ipwazuh_block_ip!firewall-drop (-srcip) on one agent or all_agentsYeswazuh_firewall_allow — per agent; needs an undo script configured on the MCP server
firewall_dropwazuh_firewall_drop!firewall-dropYeswazuh_firewall_allow
host_denywazuh_host_deny!host-deny (adds to /etc/hosts.deny, Linux)Yeswazuh_host_allow
disable_userwazuh_disable_user!disable-accountYes (Linux)wazuh_enable_user
isolate_hostwazuh_isolate_host!host-isolationNo — custom script requiredwazuh_unisolate_host
kill_processwazuh_kill_process!kill-process (PID)No — custom script requiredNone
quarantine_filewazuh_quarantine_file!quarantine (path)No — custom script requiredwazuh_restore_file
restart_wazuhwazuh_restartWazuh API restart of agent or managern/an/a
active_responsewazuh_active_responseAllowlisted command names onlyDependsDepends

If the org hasn't deployed the custom scripts, isolate/kill/quarantine will be "dispatched" and do nothing. Say so in the plan and prefer actions with stock scripts, or recommend a manual step.

Blast radius

  • block_ip with no agent means all_agents=true: fleet-wide and permanent. Name the agents that actually see the attacker (from the alerts) instead, unless the IP is confirmed malicious and internet-only. Fleet-wide blocks can only be rolled back agent by agent.
  • Never target the manager (agent 000) — the MCP server refuses it by default.
  • Protected targets (policy) are refused before execution; don't propose them.
  • Isolation cuts the host off except for the manager: confirm the business owner impact first.

Pre-checks (responder and response-planner)

  1. Agent connected? check_agent_health agent_id="<id>" — AR to a disconnected agent is queued or lost.
  2. Already done? wazuh_check_blocked_ip / wazuh_check_agent_isolation / wazuh_check_user_status before proposing a duplicate.
  3. Target still valid? For kill_process, confirm the PID with get_agent_processes (syscollector is a periodic inventory — PIDs can be stale or reused).
  4. Evidence preserved? Kill and quarantine destroy volatile evidence — record process details first.

Verification caveats

The wazuh_check_* tools infer state; they are not live host queries:

CheckEvidence it uses
wazuh_check_blocked_ipAR alert history in the active_response group for that IP — e.g. rule 601 (level 3, "Host Blocked by firewall-drop Active Response") or its JSON-log equivalent rule 651 (level 3); host-deny: rule 603 / rule 653 (level 3)
wazuh_check_agent_isolationAgent connectivity plus AR history mentioning isolation
wazuh_check_processSyscollector process inventory (periodic) — a killed PID can still appear until the next scan; read inventory_scan_time
wazuh_check_user_statusAR history mentioning the username
wazuh_check_file_quarantineA FIM "File deleted" alert — rule 553 (level 7) — for the exact path

Unblock evidence: rule 602 / rule 652 (level 3, "Host Unblocked by firewall-drop Active Response"). rule 658 (level 5) means the AR was activated but may not have had an effect — treat as not verified. No AR alert at all usually means the script didn't run (missing script, agent offline, AR disabled).

Report verification as verified / not verified / inconclusive with the evidence, never as "done" because the API said so.

Roles

  • response-planner: pick the least destructive action that contains the threat, order it (evidence → contain → eradicate), include rollback and blast radius in the rationale, then propose. Hand off to responder only via the platform (verification runs automatically after execution).
  • responder: run the matching wazuh_check_*, look for the AR alerts above, record the finding, and if something went wrong recommend rollback — hand off to response-planner for any new action.

Output

add_finding with action, target agent(s), AR command, stock/custom script status, pre-check results, verification evidence (rule and timestamp) and rollback path; refs such as MITRE-D3FEND:D3-ITF, NIST-800-61r3:Respond.

Frequently asked questions

What does the Wazuh Active Response AI skill do?

How Wazuh active response actually works — commands, agent-side scripts, dispatch vs execution, permanence, blast radius, pre-checks and verification caveats — for planning and verifying containment; use before proposing or verifying any response action.

Why use Wazuh Active Response on TypingMind?

Because you install it once and use it with any model. Wazuh Active Response 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 Wazuh Active Response in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/gensecaihq/Wazuh-Autopilot/tree/main/backend/app/skills/wazuh-active-response. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Wazuh Active Response?

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 Wazuh Active Response?

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

Is the Wazuh Active Response AI skill free?

Yes. It is published on GitHub by gensecaihq under the MIT 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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