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Thinking Red Team

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tjboudreaux
thinking-red-team

For authorized security review of code, auth, or APIs you control, model the attacker, map the attack surface, and report only findings with a reproducible exploit path and verified mitigation.

Overview

Publishertjboudreaux
Repositorycc-thinking-skills
Skill namethinking-red-team
Stars
1.3K
Forks
158
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 tjboudreaux on GitHub. Read the source before you install it.

Installation

Install the Thinking Red Team 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.
  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/tjboudreaux/cc-thinking-skills.git /tmp/cc-thinking-skills
mkdir -p .claude/skills
cp -r /tmp/cc-thinking-skills/skills/thinking-red-team .claude/skills/thinking-red-team
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Thinking Red Team 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 Thinking Red Team 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 Thinking Red Team 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.

Red Team

Adversarial security review of systems you are authorized to assess. Attack before an outsider does, but report only what you can actually break: every finding needs a concrete exploit path and a check that the proposed fix closes it.

When to Use

  • Security review of code, authentication, authorization, APIs, data handling, or infrastructure you control and are permitted to probe.
  • Pre-launch hardening of systems that handle auth, money, personal data, or privileged actions.
  • Checking whether a specific vulnerability class (injection, XSS, IDOR, auth bypass, SSRF, secret exposure, etc.) is present with a real path.
  • Validating that a claimed control actually blocks the attack, not only that a scanner is quiet.

When NOT to Use

  • No authorization to attack the target — stop; do not probe systems you do not own or have written leave to test.
  • Speculative "best practice" notes without a reproducible exploit path — drop them; they are not findings.
  • Plan, strategy, or decision stress-testing — use pre-mortem (how the plan fails) or steel-manning (strongest case against the decision).
  • Architecture resilience without a security objective — use systems or pre-mortem.
  • Scanner output alone as a report — patterns are leads; red-team requires an exploit path.
  • Non-security root-cause or hypothesis localization — use scientific-method or five-whys-plus.

Procedure

  1. Confirm authorization and objective. State target, allowed scope, out-of-scope assets, success condition (e.g., unauthorized data read, privilege escalation), and stop rules. Refuse or narrow if authorization is unclear.
  2. Build the threat model. Name adversary profiles (anonymous external, authenticated user, privileged insider) and their goals under realistic access. Attacks without an actor and goal are noise.
  3. Map the attack surface. Enumerate entry points and trust boundaries: public endpoints, auth flows, APIs, uploads, admin surfaces, jobs, webhooks, secrets, and data stores. Note exposure and required privileges.
  4. Trace exploit paths. For each high-value surface, attempt concrete abuse: input manipulation, authz gaps, token/session misuse, injection, SSRF, IDOR, mass assignment, rate-limit bypass, secret leakage. Record exact steps and observed behavior.
  5. Apply the anti-fabrication gate. Keep a finding only if you can complete: entry point → ordered steps → realized impact on this code/config. Incomplete paths are dropped, not listed as "informational."
  6. Score severity and attempt defense bypass. Rate impact and exploitability. For each relevant control (rate limit, validation, session check), try a realistic bypass and record held vs broken.
  7. Prescribe and verify mitigations. For each kept finding, give a minimal concrete fix and state how to re-test that the path is closed. Prefer fixes that remove the exploit precondition. Stop when in-scope surfaces are covered or authorization/budget ends; zero findings is valid.

Output

text
Target/scope: <in | out | goal | authorization>
Threat model: <actors, access, goals>
Attack surface: <entry points + trust boundaries>
Findings (only complete paths):
  - Title | Severity
    Entry: <endpoint/param/file>
    Steps: <1..n>
    Impact: <realized effect>
    Bypass attempts: <control → result>
    Mitigation: <minimal fix>
    Re-test: <how to confirm closed>
Summary: <kept count; dropped speculative count>

Verification

  • Falsify any finding missing entry, steps, or realized impact; treat "could be vulnerable" as non-finding.
  • Stop when in-scope attack surfaces are exhausted under authorization, or when re-test shows mitigations close the paths.
  • Over-application guard: do not pad with best-practice laundry lists; do not use this skill for non-security plan critique; do not attack without authorization.

Frequently asked questions

What does the Thinking Red Team AI skill do?

For authorized security review of code, auth, or APIs you control, model the attacker, map the attack surface, and report only findings with a reproducible exploit path and verified mitigation.

Why use Thinking Red Team on TypingMind?

Because you install it once and use it with any model. Thinking Red Team 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 Thinking Red Team in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/tjboudreaux/cc-thinking-skills/tree/main/skills/thinking-red-team. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Thinking Red Team?

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 Thinking Red Team?

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

Is the Thinking Red Team AI skill free?

Yes. It is published on GitHub by tjboudreaux 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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