Social Engineering Engagement Plan logo

Social Engineering Engagement Plan

Organization
zero-lab-ai
social-engineering-engagement-plan

Plans authorized defensive phishing simulations, vishing exercises, and other social-engineering engagements with explicit channel and cohort scope, pretext approval, participant safety, data minimization, readiness gates, metrics, and debrief. Use before measuring human-security exposure or reviewing a proposed campaign.

Overview

Publisherzero-lab-ai
Repositoryskills
Skill namesocial-engineering-engagement-plan
Stars
232
Forks
14
Bundled files
2
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.

  • 2 bundled files

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

  • Open source

    Published by zero-lab-ai on GitHub. Read the source before you install it.

Installation

Install the Social Engineering Engagement Plan 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/zero-lab-ai/skills/tree/main/plugins/engagement-operations/skills/social-engineering-engagement-plan
  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/zero-lab-ai/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/plugins/engagement-operations/skills/social-engineering-engagement-plan .claude/skills/social-engineering-engagement-plan
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Social Engineering Engagement Plan 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 Social Engineering Engagement Plan 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 Social Engineering Engagement Plan 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.

Social-engineering engagement plan

Defensive human-security testing measures organizational exposure and validates controls, but it can cause harm even when every technical action is reversible. Sponsor authority permits a bounded exercise; it does not prove the target list, pretext, infrastructure, control cell, support route, or data handling are ready.

This skill creates a checked plan. It does not write deceptive content, call scripts, payloads, collection pages, target profiles, or execution instructions.

When to Use

  • Plan authorized human-security exercises safely.
  • Use only within explicit authorization and the stated rules of engagement.

When NOT to Use

  • Do not treat this skill as permission to access, test, or change a target.
  • Do not convert missing evidence into a clean result or a stronger claim.

Workflow

  1. Record the sponsor, window, timezone, owners, digest-bound written-authority evidence, its approving role and validity window, allowed and prohibited channels, asks, persona classes, themes, and actions. The v0.1 contract supports email and voice only; keep every other channel prohibited.
  2. Define each target cohort by opaque ID, channel, supplied population, opaque inclusion and exclusion references, list state, and evidence. Never store addresses, numbers, names, or descriptive dossiers.
  3. Describe pretexts by ID, persona class, channel, approved ask, state, evidence, and limitations. Store no message copy or scripts.
  4. Inventory the target list, sending domain, training page, callback number, control cell, and support route as applicable. Planned infrastructure is not verified.
  5. Define interaction stops for distress, participant request, reporting, active incidents, and out-of-scope people or data. Define campaign pauses for cumulative distress, client incidents, scope-risking defects, and loss of the control cell. Record whether a pause fired and bind a threshold-triggered pause to evidence.
  6. Minimize data before execution. Allow only named event types; use opaque identities, aggregate reporting, no individual ranking, no public identification, and an owner for retention or disposition. Before readiness, choose no retention or a bounded retention period and name the disposition method. An unapproved event is not a useful extra metric.
  7. Link each planned action to one authorization, cohort, approved pretext, safety policy, data policy, and every required infrastructure item. Keep it planned until all readiness evidence exists.
  8. For executed actions, cite chronologically valid event-export or operator-log evidence and record bounded aggregate counts. Keep unexecuted and unapproved event fields null: zero is an observed measurement, not absence of collection. Never infer opens, delivery, reports, distress, or control adherence.
  9. Cover authorization, cohort, pretext, infrastructure, safety, data handling, deconfliction, debrief, measurement, and reporting for every allowed channel.
  10. Record immediate and organization-wide debrief ownership, participant support, feedback timing, and no-shaming rules.

Boundary with adjacent skills

  • Use osint-scanner or social-engineering-recon to collect public intelligence.
  • Use opsec-planning to compare detection risk and operational artifacts.
  • Use this skill to govern authorized interaction with people and participant care.
  • Use findings-report after evidenced results exist.
  • Credential collection, payload delivery, physical-entry methods, and target-system access require separate capabilities and explicit authority.

Rationalizations to reject

  • "The sponsor approved phishing, so the campaign is ready." Approval does not verify the target list, pretext, infrastructure, control cell, or support route.
  • "Open rate is standard." If open tracking was not approved, it is prohibited data collection rather than a free metric.
  • "A click means the participant was compromised." It proves only the approved event that was observed; credentials, execution, and access remain separate.
  • "We can exclude people manually during launch." Exclusions belong in the checked target manifest before contact.
  • "Stopping one call handles distress." Individual stops and campaign-wide pause thresholds solve different safety problems; both are required.
  • "Zero means we did not collect it." Zero is a measured result. Prohibited or uncollected events stay null so the record cannot disguise unauthorized telemetry.
  • "Recording helps evidence." Recording requires explicit authorization and legal review. A useful artifact does not create permission.
  • "Individual rankings make training actionable." They increase harm and suppress reporting. Report cohort and process controls unless individual handling is approved.
  • "A successful test should stay secret until the report." Timely debrief and a private support route are part of the engagement, not optional cleanup.

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 Social Engineering Engagement Plan AI skill do?

Plans authorized defensive phishing simulations, vishing exercises, and other social-engineering engagements with explicit channel and cohort scope, pretext approval, participant safety, data minimization, readiness gates, metrics, and debrief. Use before measuring human-security exposure or reviewing a proposed campaign.

Why use Social Engineering Engagement Plan on TypingMind?

Because you install it once and use it with any model. Social Engineering Engagement Plan 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 Social Engineering Engagement Plan in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zero-lab-ai/skills/tree/main/plugins/engagement-operations/skills/social-engineering-engagement-plan. 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 Social Engineering Engagement Plan?

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 Social Engineering Engagement Plan?

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

Is the Social Engineering Engagement Plan AI skill free?

Yes. It is published on GitHub by zero-lab-ai 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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