
zen-ai-pentest-framework
AI-powered autonomous penetration testing framework with multi-agent system, real security tool execution, and compliance reporting
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/reason-machines/security-skills --skill zen-ai-pentest-framework- 01
Install
Run the command in your project. The CLI asks which agents to install for.
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Describe the task
Ask your agent for something this skill covers. It loads zen-ai-pentest-framework automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Zen AI Pentest Framework
Skill by ara.so — Security Skills collection.
Overview
Zen-AI-Pentest is a production-ready, AI-powered autonomous penetration testing framework that orchestrates 72+ real security tools through an intelligent multi-agent system. It executes actual tools (Nmap, Nuclei, SQLMap, FFuF, etc.) with safety controls, not mocks or simulations.
Key capabilities:
- Autonomous AI agents using ReAct pattern (Reason → Act → Observe → Reflect)
- Real tool execution in Docker sandbox with 4-level safety controls
- Risk engine with false positive reduction and CVSS/EPSS scoring
- FastAPI backend with WebSocket real-time updates
- PostgreSQL persistence and Redis caching
- JWT authentication with RBAC
- Professional PDF/HTML reporting with compliance mapping
- CI/CD integration (GitHub Actions, GitLab CI, Jenkins)
Installation
Prerequisites
- Python 3.10+
- Docker and Docker Compose
- PostgreSQL 13+ (or use Docker Compose)
- Redis (optional, for caching)
Quick Start with Docker Compose
# Clone repository
git clone https://github.com/SHAdd0WTAka/Zen-Ai-Pentest.git
cd Zen-Ai-Pentest
# Set environment variables
cp .env.example .env
# Edit .env with your API keys and configuration
# Start full stack
docker-compose up -d
# Access web UI
# http://localhost:3000 (default credentials: admin/admin)
# Access API docs
# http://localhost:8000/docs
Manual Installation
# Install Python dependencies
pip install -r requirements.txt
# Install security tools (Ubuntu/Debian)
sudo apt-get update
sudo apt-get install -y nmap nuclei sqlmap ffuf whatweb wafw00f subfinder httpx nikto
# Initialize database
python -m alembic upgrade head
# Run API server
uvicorn api.main:app --host 0.0.0.0 --port 8000 --reload
# In another terminal, run frontend
cd frontend
npm install
npm run dev
Configuration
Environment Variables
Create .env file in project root:
# API Keys (REQUIRED)
OPENAI_API_KEY=sk-...
ANTHROPIC_API_KEY=sk-ant-...
# Database
DATABASE_URL=postgresql://zen:zen_password@localhost:5432/zen_pentest
REDIS_URL=redis://localhost:6379/0
# Security
JWT_SECRET_KEY=your-random-secret-key-min-32-chars
JWT_ALGORITHM=HS256
ACCESS_TOKEN_EXPIRE_MINUTES=30
# API Configuration
API_HOST=0.0.0.0
API_PORT=8000
CORS_ORIGINS=http://localhost:3000,http://localhost:5173
# Safety Controls (0-3)
# 0: Read-only info gathering
# 1: Active scanning (port scans)
# 2: Vulnerability probing
# 3: Exploit validation (requires VPN)
DEFAULT_SAFETY_LEVEL=1
REQUIRE_VPN_FOR_LEVEL_3=true
# Notifications (optional)
SLACK_WEBHOOK_URL=https://hooks.slack.com/services/...
SMTP_HOST=smtp.gmail.com
SMTP_PORT=587
SMTP_USER=your-email@gmail.com
SMTP_PASSWORD=your-app-password
# Agent Configuration
MAX_ITERATIONS=10
AGENT_TIMEOUT=300
ENABLE_MEMORY=true
MEMORY_WINDOW=5
# Tool Timeouts (seconds)
NMAP_TIMEOUT=300
NUCLEI_TIMEOUT=600
SQLMAP_TIMEOUT=900
Configuration File
config/config.yaml:
agents:
default_model: "gpt-4"
fallback_model: "claude-3-opus"
temperature: 0.7
max_tokens: 4096
tools:
enabled:
- nmap
- nuclei
- sqlmap
- ffuf
- subfinder
nmap:
default_args: ["-sV", "-sC", "-T4"]
max_ports: 10000
nuclei:
templates_dir: "/nuclei-templates"
severity: ["critical", "high", "medium"]
reporting:
formats: ["pdf", "html", "json"]
templates_dir: "templates/reports"
compliance:
frameworks: ["OWASP", "PCI-DSS", "GDPR"]
Core API Usage
Authentication
import requests
API_BASE = "http://localhost:8000"
# Login
response = requests.post(
f"{API_BASE}/api/v1/auth/login",
json={"username": "admin", "password": "admin"}
)
token = response.json()["access_token"]
# Use token in headers
headers = {
"Authorization": f"Bearer {token}",
"Content-Type": "application/json"
}
Create and Execute Scan
# Create a new scan
scan_data = {
"target": "example.com",
"scan_type": "full", # Options: quick, full, custom
"tools": ["nmap", "nuclei", "whatweb"],
"safety_level": 1, # 0-3
"options": {
"ports": "1-1000",
"aggressive": False,
"parallel": True
}
}
response = requests.post(
f"{API_BASE}/api/v1/scans",
json=scan_data,
headers=headers
)
scan_id = response.json()["scan_id"]
print(f"Scan created: {scan_id}")
# Get scan status
status = requests.get(
f"{API_BASE}/api/v1/scans/{scan_id}",
headers=headers
).json()
print(f"Status: {status['state']}") # IDLE, PLANNING, EXECUTING, etc.
# Get results
results = requests.get(
f"{API_BASE}/api/v1/scans/{scan_id}/results",
headers=headers
).json()
print(f"Findings: {len(results['findings'])}")
for finding in results['findings']:
print(f" - {finding['severity']}: {finding['title']}")
WebSocket Real-Time Updates
import asyncio
import websockets
import json
async def monitor_scan(scan_id, token):
uri = f"ws://localhost:8000/api/v1/ws/scans/{scan_id}?token={token}"
async with websockets.connect(uri) as websocket:
async for message in websocket:
data = json.loads(message)
print(f"[{data['type']}] {data['message']}")
if data['type'] == 'completed':
break
# Run
asyncio.run(monitor_scan(scan_id, token))
Python SDK Usage
Basic Scan Workflow
from zen_pentest import ZenClient
from zen_pentest.agents import AutonomousAgent
from zen_pentest.tools import ToolRegistry
# Initialize client
client = ZenClient(
api_url="http://localhost:8000",
api_key=os.getenv("ZEN_API_KEY")
)
# Quick scan
scan = client.create_scan(
target="example.com",
scan_type="quick"
)
scan.wait_for_completion(timeout=600)
report = scan.get_report(format="pdf")
report.save("report.pdf")
# Advanced scan with custom agent
agent = AutonomousAgent(
llm="gpt-4",
tools=["nmap", "nuclei", "sqlmap"],
safety_level=2,
memory_enabled=True
)
result = agent.run_scan(
target="https://example.com",
objectives=[
"Map attack surface",
"Identify web vulnerabilities",
"Test for SQL injection"
]
)
print(f"State transitions: {result.state_history}")
print(f"Findings: {len(result.findings)}")
print(f"Risk score: {result.risk_score}")
Custom Tool Integration
from zen_pentest.tools import BaseTool
from zen_pentest.schemas import ToolResult
class CustomScannerTool(BaseTool):
name = "custom_scanner"
description = "Custom vulnerability scanner"
risk_level = 1
def validate_input(self, target: str) -> bool:
# Validate target (no private IPs, etc.)
return self.is_public_target(target)
def execute(self, target: str, **kwargs) -> ToolResult:
# Your custom logic
results = self._run_custom_scan(target)
return ToolResult(
success=True,
data=results,
metadata={"tool": self.name, "target": target}
)
def parse_output(self, raw_output: str) -> dict:
# Parse tool output
return {"vulnerabilities": [...]}
# Register custom tool
registry = ToolRegistry()
registry.register(CustomScannerTool())
# Use in scan
agent = AutonomousAgent(tools=["custom_scanner"])
result = agent.run_scan(target="example.com")
Multi-Agent Coordination
from zen_pentest.agents import ResearcherAgent, AnalystAgent, CoordinatorAgent
# Create specialized agents
researcher = ResearcherAgent(
tools=["subfinder", "httpx", "whatweb"]
)
analyst = AnalystAgent(
tools=["nuclei", "ffuf", "nikto"]
)
# Coordinate workflow
coordinator = CoordinatorAgent(
agents=[researcher, analyst],
strategy="sequential" # or "parallel"
)
result = coordinator.execute_mission(
target="example.com",
depth=3
)
# Researcher findings feed into analyst
for finding in result.findings:
print(f"{finding.agent}: {finding.title} [{finding.severity}]")
CLI Usage
Basic Commands
# Run quick scan
zen-pentest scan -t example.com --quick
# Full scan with specific tools
zen-pentest scan -t example.com \
--tools nmap,nuclei,sqlmap \
--safety-level 2 \
--output report.pdf
# Check scan status
zen-pentest status --scan-id abc123
# List all scans
zen-pentest list --status running
# Generate report from existing scan
zen-pentest report --scan-id abc123 \
--format pdf \
--output custom-report.pdf \
--compliance OWASP,PCI-DSS
# Export results
zen-pentest export --scan-id abc123 \
--format json \
--output results.json
Advanced CLI Features
# Custom agent configuration
zen-pentest scan -t example.com \
--agent-config config/custom-agent.yaml \
--max-iterations 15 \
--memory enabled
# Resume interrupted scan
zen-pentest resume --scan-id abc123
# Benchmark mode
zen-pentest benchmark \
--scenario htb-academy \
--compare manual,autopentester
# Tool inventory check
zen-pentest tools --check
# Database migration
zen-pentest db upgrade head
Common Patterns
Safe Reconnaissance Scan
# Level 0: Read-only information gathering
client = ZenClient()
scan = client.create_scan(
target="example.com",
safety_level=0,
tools=["whois", "dns", "subfinder", "whatweb"]
)
results = scan.execute()
# Safe for production environments
print(f"Subdomains found: {len(results.subdomains)}")
print(f"Technologies: {results.technologies}")
Vulnerability Assessment with Validation
# Level 2: Active scanning + validation
scan = client.create_scan(
target="https://example.com",
safety_level=2,
tools=["nuclei", "ffuf"],
options={
"validate_findings": True,
"false_positive_filter": True,
"risk_scoring": True
}
)
results = scan.execute()
# Only validated, high-confidence findings
critical_findings = [
f for f in results.findings
if f.severity == "critical" and f.validated
]
for finding in critical_findings:
print(f"CVSS {finding.cvss_score}: {finding.title}")
print(f"Evidence: {finding.evidence_path}")
print(f"Remediation: {finding.remediation}")
CI/CD Integration
# .github/workflows/security-scan.yml
from zen_pentest.ci import GitHubAction
action = GitHubAction()
result = action.run_scan(
target=os.getenv("STAGING_URL"),
fail_on_severity="high",
report_format="sarif"
)
# Automatically creates GitHub Security Advisory
if result.has_findings:
action.create_security_advisory(result.findings)
exit(1 if result.severity >= "high" else 0)
Compliance Reporting
from zen_pentest.reporting import ComplianceMapper
# Generate compliance report
mapper = ComplianceMapper(frameworks=["OWASP", "PCI-DSS", "GDPR"])
compliance_report = mapper.map_findings(scan.findings)
print(f"OWASP Top 10 coverage: {compliance_report.owasp.coverage}%")
print(f"PCI-DSS gaps: {compliance_report.pci_dss.gaps}")
# Export for auditors
compliance_report.export("audit-report.pdf", template="official")
Troubleshooting
Common Issues
Tool execution fails:
# Check tool installation
zen-pentest tools --check
# Verify Docker sandbox
docker ps | grep zen-pentest-sandbox
# Check tool permissions
zen-pentest tools --test nmap
Database connection errors:
# Test database connection
from zen_pentest.db import check_connection
if not check_connection():
print("Database unreachable. Check DATABASE_URL in .env")
# Reset database
zen-pentest db reset --force
Agent timeout:
# Increase timeout and iterations
agent = AutonomousAgent(
timeout=600, # 10 minutes
max_iterations=20,
enable_checkpoints=True # Resume on failure
)
High memory usage:
# Limit concurrent scans
export MAX_CONCURRENT_SCANS=2
# Disable memory feature
export ENABLE_MEMORY=false
# Clear Redis cache
redis-cli FLUSHDB
False positives:
# Enable stricter validation
scan = client.create_scan(
target="example.com",
options={
"validation_threshold": 0.8, # 80% confidence
"llm_voting": True, # Multi-model consensus
"require_evidence": True
}
)
Debug Mode
# Enable verbose logging
export ZEN_DEBUG=true
export LOG_LEVEL=DEBUG
# Run scan with debug output
zen-pentest scan -t example.com --debug --log-file debug.log
# Check logs
tail -f logs/zen-pentest.log
Testing Installation
# Run self-test suite
from zen_pentest.tests import run_diagnostics
diagnostics = run_diagnostics()
print(diagnostics.report())
# Expected output:
# ✓ Database: Connected
# ✓ Redis: Available
# ✓ Tools: 72/72 installed
# ✓ API: Responding
# ✓ Agents: Initialized
Safety and Legal Considerations
IMPORTANT: Only scan systems you own or have explicit written permission to test.
# Built-in safety checks
from zen_pentest.safety import SafetyValidator
validator = SafetyValidator()
# Blocks private IPs, localhost, cloud metadata endpoints
if not validator.is_safe_target("10.0.0.1"):
raise ValueError("Cannot scan private network")
# Requires VPN for Level 3 (exploit validation)
if safety_level == 3 and not validator.is_vpn_active():
raise ValueError("VPN required for Level 3 scans")
Configure authorized targets in config/authorized-targets.yaml:
authorized_targets:
- domain: "*.example.com"
owner: "Your Company"
expiry: "2026-12-31"
max_safety_level: 3
Resources
- Documentation: https://shadd0wtaka.github.io/Zen-Ai-Pentest/
- API Reference: http://localhost:8000/docs (when running)
- GitHub: https://github.com/SHAdd0WTAka/Zen-Ai-Pentest
- Discord: https://discord.gg/BSmCqjhY
- Live Demo: https://zen-ai-pentest.pages.dev
Advanced Topics
See additional documentation:
- IMPLEMENTATION_SUMMARY.md - Architecture deep dive
- README_ENHANCED_TOOLS.md - Tool integration guide
- docs/TESTING.md - Testing framework
- ROADMAP_2026.md - Future features
FAQ
What does the zen-ai-pentest-framework skill do?
AI-powered autonomous penetration testing framework with multi-agent system, real security tool execution, and compliance reporting
How do I install zen-ai-pentest-framework?
Run npx skills add https://github.com/reason-machines/security-skills --skill zen-ai-pentest-framework in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/zen-ai-pentest-framework/ (personal) or .claude/skills/zen-ai-pentest-framework/ (project).
Which AI agents can use zen-ai-pentest-framework?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is zen-ai-pentest-framework safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains zen-ai-pentest-framework?
It is published by reason-machines in reason-machines/security-skills. It has 780 recorded installs.
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