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Containment Playbooks

Organization
gensecaihq
containment-playbooks

Reference for every Wazuh containment action type — when to use it, required parameters, D3FEND mapping, verification and rollback tools; use when proposing, reviewing or verifying a specific response action.

Overview

Publishergensecaihq
RepositoryWazuh-Autopilot
Skill namecontainment-playbooks
Stars
61
Forks
15
Bundled files
Instructions only
LicenseMIT
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.

  • 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 Containment Playbooks 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/containment-playbooks
  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/containment-playbooks .claude/skills/containment-playbooks
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Containment Playbooks 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 Containment Playbooks 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 Containment Playbooks 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.

Containment Playbooks

The response-planner proposes these actions with propose_action. Any other agent holding this skill (e.g. responder) hands off to response-planner instead. The platform executor runs the Wazuh MCP tool only after policy and approval. No agent can call the executor tools listed below. Parameters must match what the executor expects or execution fails. Load wazuh-active-response for how Wazuh AR scripts, timeouts and agent-side requirements work.

Action reference

TypeExecutor tool (not callable by agents)params for propose_actionVerify (read-only)RollbackD3FEND
block_ipwazuh_block_ipip_address + (agent_id, or none for fleet-wide)wazuh_check_blocked_ipwazuh_firewall_allow (per agent only)D3-ITF Inbound Traffic Filtering
firewall_dropwazuh_firewall_dropip_address (sent as src_ip), agent_idwazuh_check_blocked_ipwazuh_firewall_allowD3-ITF Inbound Traffic Filtering
host_denywazuh_host_denyip_address (sent as src_ip), agent_idwazuh_check_blocked_ipwazuh_host_allowD3-ITF Inbound Traffic Filtering
isolate_hostwazuh_isolate_hostagent_idwazuh_check_agent_isolationwazuh_unisolate_hostD3-NI Network Isolation
kill_processwazuh_kill_processagent_id + process_id (a PID; names are not accepted)wazuh_check_processnone (process gone)D3-PT Process Termination
disable_userwazuh_disable_useragent_id, usernamewazuh_check_user_statuswazuh_enable_userD3-AL Account Locking
quarantine_filewazuh_quarantine_fileagent_id, file_pathwazuh_check_file_quarantinewazuh_restore_fileD3-FEV File Eviction
active_responsewazuh_active_responseagent_id, command (+ parameters)depends on commanddepends on commandnone
restart_wazuhwazuh_restartagent_id, or target: "manager"check_agent_healthnonenone

Before proposing, check the current state with the read-only tools: is the IP already blocked (wazuh_check_blocked_ip)? Is the agent connected (check_agent_health)? A disconnected agent can't run AR, so propose nothing it can't execute. Say so and escalate.

Outbound C2 blocking maps to D3-OTF Outbound Traffic Filtering; say so in the rationale when the blocked IP is a C2 destination rather than an inbound attacker.

When to use

block_ip — external attacker IP (brute force, exploitation, scanning with success risk). Through the Wazuh MCP Server the block is permanent until removed: there is no timeout. Undoing it needs wazuh_firewall_allow per agent plus an undo script the operator has deployed. Put the intended review time in the rationale. Omitting agent_id blocks fleet-wide, which can't be rolled back automatically, so prefer the affected agent unless the whole internet-facing fleet is under attack. Never block internal infrastructure IPs (DNS, proxies, NAT gateways): it blocks everyone behind them. Beware shared cloud/CDN IPs.

firewall_drop / host_deny — same intent as block_ip on a specific agent; host_deny uses TCP wrappers (/etc/hosts.deny) and affects only wrapper-aware services (e.g. sshd builds with libwrap). Prefer block_ip unless policy requires these.

isolate_host — confirmed compromise with active attacker, lateral movement or C2. Cuts the host off except for the Wazuh manager. High business impact on servers — state the service impact. Capture evidence first (host-forensics finding).

kill_process — single malicious process (miner, reverse shell) on an otherwise healthy host. Evidence first: record PID, path, command line, parent, hash from get_agent_processes (syscollector inventory, so confirm the PID is current). Malware may respawn: pair with persistence removal (human step) or isolation.

disable_user — account confirmed used maliciously. Note whether it's a service / break-glass account and the impact. Credential reset and session revocation are human recovery steps.

quarantine_file — malicious file on disk (web shell, dropped binary). Include the hash in the rationale. Quarantine, never delete.

active_response — custom AR scripts deployed by the operator. Use only when the command name is known to exist in the environment; otherwise don't propose. The default autonomy policy disables this type, so expect a refusal unless an admin enabled it.

restart_wazuh — agent misbehaving (not collecting, stuck), never as a security containment step. Low security value, may lose volatile context.

Rationale checklist

  1. Evidence (alert ids, finding titles).
  2. Why this action and not a less disruptive one.
  3. Business impact and blast radius.
  4. Dependencies / ordering.
  5. Rollback path and verification tool.

Output

  • response-planner: propose_action with exact params above. Others: hand off to response-planner with the proposed action spelled out.
  • For reviews, add_finding titled Containment review noting parameter problems, protected-target conflicts, or missing rollback paths. standard_refs: MITRE-D3FEND:<id>, NIST-CSF-2:RS.MI.

Frequently asked questions

What does the Containment Playbooks AI skill do?

Reference for every Wazuh containment action type — when to use it, required parameters, D3FEND mapping, verification and rollback tools; use when proposing, reviewing or verifying a specific response action.

Why use Containment Playbooks on TypingMind?

Because you install it once and use it with any model. Containment Playbooks 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 Containment Playbooks in TypingMind?

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

Which AI models can use Containment Playbooks?

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 Containment Playbooks?

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

Is the Containment Playbooks 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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