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Red Team Tools

CommunityPopular
zebbern
red-team-tools

This skill should be used when the user asks to "follow red team methodology", "perform bug bounty hunting", "automate reconnaissance", "hunt for XSS vulnerabilities", "enumerate subdomains", or needs security researcher techniques and tool configurations from top bug bounty hunters.

Overview

Publisherzebbern
Repositoryclaude-code-guide
Skill namered-team-tools
Stars
4.6K
Forks
464
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 zebbern on GitHub. Read the source before you install it.

Installation

Install the Red Team Tools 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/zebbern/claude-code-guide.git /tmp/claude-code-guide
mkdir -p .claude/skills
cp -r /tmp/claude-code-guide/skills/red-team-tools .claude/skills/red-team-tools
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Red Team Tools 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 Red Team Tools 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 Red Team Tools 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 Tools and Methodology

Purpose

Implement proven methodologies and tool workflows from top security researchers for effective reconnaissance, vulnerability discovery, and bug bounty hunting. Automate common tasks while maintaining thorough coverage of attack surfaces.

Inputs/Prerequisites

  • Target scope definition (domains, IP ranges, applications)
  • Linux-based attack machine (Kali, Ubuntu)
  • Bug bounty program rules and scope
  • Tool dependencies installed (Go, Python, Ruby)
  • API keys for various services (Shodan, Censys, etc.)

Outputs/Deliverables

  • Comprehensive subdomain enumeration
  • Live host discovery and technology fingerprinting
  • Identified vulnerabilities and attack vectors
  • Automated recon pipeline outputs
  • Documented findings for reporting

Core Workflow

1. Project Tracking and Acquisitions

Set up reconnaissance tracking:

bash
# Create project structure
mkdir -p target/{recon,vulns,reports}
cd target

# Find acquisitions using Crunchbase
# Search manually for subsidiary companies

# Get ASN for targets
amass intel -org "Target Company" -src

# Alternative ASN lookup
curl -s "https://bgp.he.net/search?search=targetcompany&commit=Search"

2. Subdomain Enumeration

Comprehensive subdomain discovery:

bash
# Create wildcards file
echo "target.com" > wildcards

# Run Amass passively
amass enum -passive -d target.com -src -o amass_passive.txt

# Run Amass actively
amass enum -active -d target.com -src -o amass_active.txt

# Use Subfinder
subfinder -d target.com -silent -o subfinder.txt

# Asset discovery
cat wildcards | assetfinder --subs-only | anew domains.txt

# Alternative subdomain tools
findomain -t target.com -o

# Generate permutations with dnsgen
cat domains.txt | dnsgen - | httprobe > permuted.txt

# Combine all sources
cat amass_*.txt subfinder.txt | sort -u > all_subs.txt

3. Live Host Discovery

Identify responding hosts:

bash
# Check which hosts are live with httprobe
cat domains.txt | httprobe -c 80 --prefer-https | anew hosts.txt

# Use httpx for more details
cat domains.txt | httpx -title -tech-detect -status-code -o live_hosts.txt

# Alternative with massdns
massdns -r resolvers.txt -t A -o S domains.txt > resolved.txt

4. Technology Fingerprinting

Identify technologies for targeted attacks:

bash
# Whatweb scanning
whatweb -i hosts.txt -a 3 -v > tech_stack.txt

# Nuclei technology detection
nuclei -l hosts.txt -t technologies/ -o tech_nuclei.txt

# Wappalyzer (if available)
# Browser extension for manual review

5. Content Discovery

Find hidden endpoints and files:

bash
# Directory bruteforce with ffuf
ffuf -ac -v -u https://target.com/FUZZ -w /usr/share/seclists/Discovery/Web-Content/raft-medium-directories.txt

# Historical URLs from Wayback
waybackurls target.com | tee wayback.txt

# Find all URLs with gau
gau target.com | tee all_urls.txt

# Parameter discovery
cat all_urls.txt | grep "=" | sort -u > params.txt

# Generate custom wordlist from historical data
cat all_urls.txt | unfurl paths | sort -u > custom_wordlist.txt

6. Application Analysis (Jason Haddix Method)

Heat Map Priority Areas:

  1. File Uploads - Test for injection, XXE, SSRF, shell upload
  2. Content Types - Filter Burp for multipart forms
  3. APIs - Look for hidden methods, lack of auth
  4. Profile Sections - Stored XSS, custom fields
  5. Integrations - SSRF through third parties
  6. Error Pages - Exotic injection points

Analysis Questions:

  • How does the app pass data? (Params, API, Hybrid)
  • Where does the app talk about users? (UID, UUID endpoints)
  • Does the site have multi-tenancy or user levels?
  • Does it have a unique threat model?
  • How does the site handle XSS/CSRF?
  • Has the site had past writeups/exploits?

7. Automated XSS Hunting

bash
# ParamSpider for parameter extraction
python3 paramspider.py --domain target.com -o params.txt

# Filter with Gxss
cat params.txt | Gxss -p test

# Dalfox for XSS testing
cat params.txt | dalfox pipe --mining-dict params.txt -o xss_results.txt

# Alternative workflow
waybackurls target.com | grep "=" | qsreplace '"><script>alert(1)</script>' | while read url; do
    curl -s "$url" | grep -q 'alert(1)' && echo "$url"
done > potential_xss.txt

8. Vulnerability Scanning

bash
# Nuclei comprehensive scan
nuclei -l hosts.txt -t ~/nuclei-templates/ -o nuclei_results.txt

# Check for common CVEs
nuclei -l hosts.txt -t cves/ -o cve_results.txt

# Web vulnerabilities
nuclei -l hosts.txt -t vulnerabilities/ -o vuln_results.txt

9. API Enumeration

Wordlists for API fuzzing:

bash
# Enumerate API endpoints
ffuf -u https://target.com/api/FUZZ -w /usr/share/seclists/Discovery/Web-Content/api/api-endpoints.txt

# Test API versions
ffuf -u https://target.com/api/v1/FUZZ -w api_wordlist.txt
ffuf -u https://target.com/api/v2/FUZZ -w api_wordlist.txt

# Check for hidden methods
for method in GET POST PUT DELETE PATCH; do
    curl -X $method https://target.com/api/users -v
done

10. Automated Recon Script

bash
#!/bin/bash
domain=$1

if [[ -z $domain ]]; then
    echo "Usage: ./recon.sh <domain>"
    exit 1
fi

mkdir -p "$domain"

# Subdomain enumeration
echo "[*] Enumerating subdomains..."
subfinder -d "$domain" -silent > "$domain/subs.txt"

# Live host discovery
echo "[*] Finding live hosts..."
cat "$domain/subs.txt" | httpx -title -tech-detect -status-code > "$domain/live.txt"

# URL collection
echo "[*] Collecting URLs..."
cat "$domain/live.txt" | waybackurls > "$domain/urls.txt"

# Nuclei scanning
echo "[*] Running Nuclei..."
nuclei -l "$domain/live.txt" -o "$domain/nuclei.txt"

echo "[+] Recon complete!"

Quick Reference

Essential Tools

ToolPurpose
AmassSubdomain enumeration
SubfinderFast subdomain discovery
httpx/httprobeLive host detection
ffufContent discovery
NucleiVulnerability scanning
Burp SuiteManual testing
DalfoxXSS automation
waybackurlsHistorical URL mining

Key API Endpoints to Check

/api/v1/users
/api/v1/admin
/api/v1/profile
/api/users/me
/api/config
/api/debug
/api/swagger
/api/graphql

XSS Filter Testing

html
<!-- Test encoding handling -->
<h1><img><table>
<script>
%3Cscript%3E
%253Cscript%253E
%26lt;script%26gt;

Constraints

  • Respect program scope boundaries
  • Avoid DoS or fuzzing on production without permission
  • Rate limit requests to avoid blocking
  • Some tools may generate false positives
  • API keys required for full functionality of some tools

Examples

Example 1: Quick Subdomain Recon

bash
subfinder -d target.com | httpx -title | tee results.txt

Example 2: XSS Hunting Pipeline

bash
waybackurls target.com | grep "=" | qsreplace "test" | httpx -silent | dalfox pipe

Example 3: Comprehensive Scan

bash
# Full recon chain
amass enum -d target.com | httpx | nuclei -t ~/nuclei-templates/

Troubleshooting

IssueSolution
Rate limitedUse proxy rotation, reduce concurrency
Too many resultsFocus on specific technology stacks
False positivesManually verify findings before reporting
Missing subdomainsCombine multiple enumeration sources
API key errorsVerify keys in config files
Tools not foundInstall Go tools with go install

Frequently asked questions

What does the Red Team Tools AI skill do?

This skill should be used when the user asks to "follow red team methodology", "perform bug bounty hunting", "automate reconnaissance", "hunt for XSS vulnerabilities", "enumerate subdomains", or needs security researcher techniques and tool configurations from top bug bounty hunters.

Why use Red Team Tools on TypingMind?

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

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

Which AI models can use Red Team Tools?

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 Red Team Tools?

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

Is the Red Team Tools AI skill free?

Yes. It is published on GitHub by zebbern 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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