Ir Playbook Lateral Movement logo

Ir Playbook Lateral Movement

Organization
gensecaihq
ir-playbook-lateral-movement

Incident-response playbook for lateral movement — SMB/admin shares, WinRM/PowerShell remoting, RDP, SSH, PsExec/WMI remote execution, pass-the-hash and remote services/tasks; use when Wazuh shows internal-to-internal authentication or remote-execution chains (e.g. rules 92652, 92653, 92650, 92068, 91823, or SSH success rule 5715 from an internal source).

Overview

Publishergensecaihq
RepositoryWazuh-Autopilot
Skill nameir-playbook-lateral-movement
Stars
61
Forks
15
Bundled files
1
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.

  • 1 bundled files

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

  • Open source

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

Installation

Install the Ir Playbook Lateral Movement 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/ir-playbook-lateral-movement
  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/ir-playbook-lateral-movement .claude/skills/ir-playbook-lateral-movement
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ir Playbook Lateral Movement 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 Ir Playbook Lateral Movement 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 Ir Playbook Lateral Movement 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.

IR Playbook — Lateral Movement

Severity critical: lateral movement means an adversary already has a foothold and valid credentials. Correlate across hosts before containment. Rule IDs are from the stock Wazuh 4.14 ruleset (levels official); several need Sysmon or PowerShell script-block logging on the endpoints. Full procedure: references/playbook.md.

1. Detection signals

TechniqueWazuh rules (level)Needs
T1550.002 Pass-the-hash (NTLM remote logon)rules 92652 (L6), 92657 (L6, NTLM + RDP)Security log, Event ID 4624 logon type 3/10
T1021.001 RDPrule 92653 (L3, RDP logon), rule 92656 (L15, RDP from loopback — tunnelling)Security log
T1021.002 SMB / admin sharesrules 92105 (L3), 92106 (L3); rule 92650 (L12, service binary in Windows root — dropped via admin share); rules 92202, 92218 (L6, executable dropped in Windows root)Sysmon Event ID 3 / 11
T1569.002 PsExec / remote servicerule 92068 (L3, PsExec execution); rule 61138 (L5, new service, Event ID 7045)Sysmon Event ID 1, System log
T1021.006 WinRM / PS remotingrule 92110 (L4, WinRM network activity); rule 91823 (L14, Invoke-Command on a remote computer); rule 92220 (L6, binary dropped by WinRM process)Sysmon, PowerShell/Operational
T1047 WMIrule 92070 (L6, WMI spawned PowerShell); rule 92071 (L12, WMI PowerShell with base64)Sysmon Event ID 1
T1053.005 Scheduled taskrule 60228 (L4, Event ID 4698)Security log
T1003.001 Credential access before movementrules 92900 (L12), 92403 (L12) — LSASS accessedSysmon Event ID 10 / 8
T1021.004 SSH (Linux)rule 5715 (L3, success) from an internal source after rules 5716, 5760 (L5) failures; rule 92603 (L6, file copied in via SCP); rule 92602 (L12, Impacket signature)sshd logs, auditd
Account manipulation during spreadrules 60109 (L8, account created/enabled), 60154 (L12, Administrators group changed)Security log

High-confidence patterns: one account authenticating to ≥3 hosts within 10 min; workstation-to-workstation admin logons; service accounts used interactively; logons outside the account's baseline. Wazuh has no stock rule for the fan-out pattern — create it as custom rule 100230 (frequency rule over group authentication_success, <same_field>dstuser</same_field>, <different_field>agent.id</different_field>; validate with wazuh-logtest). Explicit-credential logons (Event ID 4648) have no stock rule either; add custom rule 100231 if you rely on them.

2. Triage / investigation (investigation agent)

  1. Scope: search_security_events for the account and the source host across all agents (time_range: "24h", then "7d"); get_wazuh_alerts with rule_groups: ["authentication_success","sysmon_eid3_detections","sysmon_eid1_detections"] on each suspected host. search_cases for the host/account first.
  2. Answer:
    • Which account, which source host? Admin jump host (expected) or workstation?
    • How many destinations, over what window? Any domain controllers or crown-jewel servers?
    • Which technique (SMB, WinRM, RDP, WMI, PsExec, SSH)?
    • Initial compromise on the source (phishing, brute force, malware)? If brute force → ir-playbook-bruteforce.
  3. On each touched host (DCs and servers first):
    • get_agent_processes: psexesvc, wmiprvse children, wsmprovhost, unusual powershell, credential tools.
    • get_agent_ports: new listeners, RDP/WinRM exposure, outbound C2.
    • check_agent_health: agents stopped or tampered with during the spread.
    • Hand off to threat-intel for hashes/external C2 reputation.
  4. add_entities (account = compromised, source host, each destination host with agent_id), link_mitre, update_case severity critical unless proven sanctioned (change ticket, jump host, known admin).
  5. add_finding: host-hop timeline, compromised accounts, confirmed/suspected hosts, first hop time, and a containment recommendation to response-planner.

3. Response (response-planner)

Check current state first (wazuh_check_agent_isolation, wazuh_check_user_status), then propose:

SituationProposal
Source host confirmed compromisedpropose_action(type="isolate_host", target=<src id>, params={"agent_id": <src id>}) (D3-NI)
Compromised account active on a hostpropose_action(type="disable_user", params={"agent_id": <host>, "username": <account>}) (D3-AL)
Remote-execution tooling runningpropose_action(type="kill_process", params={"agent_id": <host>, "process_id": <pid>})
External C2 seen from touched hostspropose_action(type="block_ip", params={"ip_address": <c2>, "all_agents": true})
Destination hosts with confirmed attacker activityisolate_host per host, ordered by criticality

Sequencing: isolate the source before killing processes; disable accounts after isolation so the attacker can't pivot during the change; never isolate domain controllers without a human decision (keep DCs in protected targets). Domain-level account disable, krbtgt reset and GPO changes are human tasks — add_finding with owner and urgency.

4. Eradication and recovery

  • Reset credentials for every account in the chain (krbtgt twice if Kerberos abuse is suspected).
  • Remove persistence created during movement (services, scheduled tasks, WMI subscriptions — rules 89501, 89502 flag WMI consumers).
  • Rebuild or clean isolated hosts; un-isolation is a human-approved rollback in the approvals UI.
  • Tighten: LAPS, tiered admin model, block workstation-to-workstation SMB/RDP, restrict WinRM.

5. Verification

The responder verifies each executed action (wazuh_check_agent_isolation, wazuh_check_user_status, wazuh_check_process) and records verification findings.

6. Evidence and records

  • Findings with standard_refs such as MITRE-ATTACK:T1021.002, MITRE-ATTACK:T1550.002, NIST-800-61r3:Respond.
  • Preserve references to Event IDs 4624, 4648, 4672, 7045 and 4698 before hosts are reimaged.
  • Coverage gaps (no Sysmon, no script-block logging, no fan-out rule) → hand off to detection-engineer.
  • Hand off to reporting for the incident report with blast radius and credential-reset status.

Escalation

ConditionEscalate to
Domain controller touched or domain admin usedIR lead + identity team (human)
> 10 hosts touchedMajor incident process
Ransomware precursors (backup/VSS tampering)ir-playbook-ransomware immediately

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 Ir Playbook Lateral Movement AI skill do?

Incident-response playbook for lateral movement — SMB/admin shares, WinRM/PowerShell remoting, RDP, SSH, PsExec/WMI remote execution, pass-the-hash and remote services/tasks; use when Wazuh shows internal-to-internal authentication or remote-execution chains (e.g. rules 92652, 92653, 92650, 92068, 91823, or SSH success rule 5715 from an internal source).

Why use Ir Playbook Lateral Movement on TypingMind?

Because you install it once and use it with any model. Ir Playbook Lateral Movement 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 Ir Playbook Lateral Movement in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/gensecaihq/Wazuh-Autopilot/tree/main/backend/app/skills/ir-playbook-lateral-movement. 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 Ir Playbook Lateral Movement?

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 Ir Playbook Lateral Movement?

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

Is the Ir Playbook Lateral Movement 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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