zakirkun

guardian-cli

An enterprise-grade, AI-powered penetration testing automation CLI tool. Orchestrates multiple specialized AI agents (Planner, ToolAgent, Analyst, Reporter) backed by 4 AI providers (OpenAI, Claude, Gemini, OpenRouter) and 19 integrated security tools through YAML-defined workflows. Produces professional Markdown, HTML, or JSON security reports with full evidence capture and traceability.

zakirkun 1,445 304 Updated 3mo ago

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npx skillscat add zakirkun/guardian-cli

Install via the SkillsCat registry.

SKILL.md

Guardian CLI – Skill Reference

1. Project Overview

Guardian (v2.0) is a Python 3.11+ CLI application that automates penetration testing workflows using a multi-agent AI system. It is designed for authorized security assessments only.

guardian-cli/
├── ai/               # AI provider integrations & prompt templates
│   ├── providers/    # base_provider, openai, claude, gemini, openrouter
│   └── prompt_templates/
├── cli/              # CLI entry-point (Typer) & commands
│   └── commands/     # init, scan, recon, analyze, report, workflow, ai, models
├── core/             # Multi-agent orchestration engine
│   ├── agent.py          # BaseAgent
│   ├── planner.py        # PlannerAgent  – decides next test step
│   ├── tool_agent.py     # ToolAgent     – selects & executes tools
│   ├── analyst_agent.py  # AnalystAgent  – interprets tool output
│   ├── reporter_agent.py # ReporterAgent – generates final reports
│   ├── memory.py         # PentestMemory, ToolExecution, Finding dataclasses
│   └── workflow.py       # WorkflowEngine – top-level orchestrator
├── tools/            # 19 security-tool wrappers (one Python file each)
├── workflows/        # YAML workflow definitions (8 built-in)
├── utils/            # logger, scope_validator, helpers
├── config/           # guardian.yaml configuration file
├── reports/          # Output directory for generated reports & session state
└── docs/             # Guides (WORKFLOW_GUIDE, TOOLS_DEVELOPMENT_GUIDE, …)

2. Architecture

2.1 Agent Pipeline

Target Input
    │
    ▼
WorkflowEngine.run_workflow()  ──or──  WorkflowEngine.run_autonomous()
    │
    ├──► PlannerAgent.decide_next_action()   — Strategic AI reasoning
    │
    ├──► ToolAgent.execute_tool()            — Runs the chosen security tool
    │
    ├──► AnalystAgent.interpret_output()     — Parses & links findings to executions
    │
    └──► ReporterAgent.execute()             — Generates markdown / HTML / JSON report

Each agent inherits from BaseAgent and uses a shared PentestMemory object that stores:

Store Class Purpose
findings Finding Vulnerabilities discovered
tool_executions ToolExecution Full command + raw output
completed_actions list[str] Phase progress tracker
current_phase str reconnaissance → scanning → analysis → reporting

2.2 AI Provider Abstraction

All providers implement the same BaseProvider interface, making them interchangeable at runtime:

Provider Env Var Default Model
openai OPENAI_API_KEY gpt-4o
claude ANTHROPIC_API_KEY claude-3-5-sonnet-20241022
gemini GOOGLE_API_KEY gemini-2.5-pro
openrouter OPENROUTER_API_KEY anthropic/claude-3.5-sonnet

Switch provider via config/guardian.yaml or --provider CLI flag.


3. CLI Commands

Run with python -m cli.main <command> (or guardian <command> after installation).

Command Purpose
init Create/validate config/guardian.yaml
scan One-shot vulnerability scan on a target
recon Passive / active reconnaissance
analyze Re-analyze an existing session
report Generate / re-generate a report for a session
workflow list List available workflows
workflow run Execute a named workflow against a target
ai Query AI about a finding or custom prompt
models List configured AI providers and models
version Show version

Common Flags

--target <IP/domain/CIDR>   # Required for scan/recon/workflow run
--provider <openai|claude|gemini|openrouter>
--name <workflow-name>       # For workflow run
--format <markdown|html|json>
--session <SESSION_ID>       # For report regeneration

4. Workflow System

4.1 Running a Workflow

# List available workflows
python -m cli.main workflow list

# Web penetration test
python -m cli.main workflow run --name web_pentest --target https://target.example.com

# Full network assessment
python -m cli.main workflow run --name network --target 192.168.1.0/24

# Autonomous AI-driven pentest
python -m cli.main workflow run --name autonomous --target example.com

4.2 Built-in Workflows

File Name Description
recon.yaml recon Passive + active reconnaissance
web_pentest.yaml web_pentest HTTP discovery, vuln scan, report
network_pentest.yaml network Port scan, service detect, analysis
advanced_recon.yaml advanced_recon Deep subdomain + DNS enumeration
full_vuln_scan.yaml full_vuln_scan Comprehensive vulnerability sweep
wordpress_audit.yaml wordpress_audit WordPress-specific audit
autonomous.yaml autonomous AI-decides-everything mode

4.3 Workflow YAML Schema

name: my_workflow
description: "Short description"

steps:
  - name: http_discovery
    type: tool              # tool | analysis | report
    tool: httpx             # tool name (must match tools/ wrapper)
    objective: "Describe what to find"
    parameters:             # Override config/guardian.yaml defaults
      tech_detect: true
      threads: 100

  - name: analyze
    type: analysis
    agent: analyst
    objective: "Correlate findings"

  - name: generate_report
    type: report
    # format defaults to config output.format

settings:
  max_parallel_tools: 3
  require_confirmation: true
  save_intermediate: true

Parameter Priority: Workflow YAML > config/guardian.yaml > Tool defaults

4.4 Fuzzy Workflow Matching

The engine resolves --name webweb_pentest.yaml automatically using substring matching on the filename stem.


5. Integrated Security Tools (19)

Category Tools
Network nmap, masscan
Web Recon httpx, whatweb, wafw00f
Subdomain / DNS subfinder, amass, dnsrecon
Vulnerability nuclei, nikto, sqlmap, wpscan
SSL/TLS testssl, sslyze
Content Discovery gobuster, ffuf, arjun
Security Analysis xsstrike, gitleaks, cmseek

Each tool has a self-contained Python wrapper in tools/<toolname>.py that:

  1. Builds the shell command from parameters
  2. Executes it asynchronously (asyncio subprocess)
  3. Returns {"success": bool, "command": str, "raw_output": str, "exit_code": int, "duration": float}

Guardian works with a subset of tools available; the AI adapts based on what is installed.


6. Configuration (config/guardian.yaml)

Key sections:

ai:
  provider: openai          # Active provider
  openai:
    model: gpt-4o
    api_key: null            # Or set OPENAI_API_KEY env var
  temperature: 0.2
  max_tokens: 8000

pentest:
  safe_mode: true            # Disable destructive actions
  require_confirmation: true
  max_parallel_tools: 3
  tool_timeout: 300          # seconds

output:
  format: markdown           # markdown | html | json
  save_path: ./reports
  verbosity: normal          # quiet | normal | verbose | debug

scope:
  blacklist:                 # Never scan these
    - 127.0.0.0/8
    - 10.0.0.0/8
    - 172.16.0.0/12
    - 192.168.0.0/16

7. Output & Evidence

Every scan session produces:

File Contents
reports/report_<SESSION_ID>.md Full penetration test report
reports/session_<SESSION_ID>.json Raw session state (findings, executions, phase)

Evidence capture includes:

  • Execution ID linked to every finding (execution_id field on Finding)
  • Full raw output (up to 2000-char snippets) of every tool run
  • AI reasoning trace embedded in reports (when include_reasoning: true)

Report formats are selected via the output.format config key or the --format CLI flag and map to file extensions .md, .html, .json.


8. Adding a New Tool

  1. Create tools/mytool.py inheriting from BaseTool (see tools/base_tool.py)
  2. Implement async def run(self, target: str, **kwargs) -> dict; return the standard result dict
  3. Register the tool in tools/__init__.py
  4. Reference it by name in any workflow YAML step (tool: mytool)

See docs/TOOLS_DEVELOPMENT_GUIDE.md for full documentation.


9. Adding a New AI Provider

  1. Create ai/providers/myprovider_provider.py inheriting BaseProvider (ai/providers/base_provider.py)
  2. Implement async def complete(self, messages, system_prompt) -> dict
  3. Register in ai/ai_client.py provider factory
  4. Add the config block to config/guardian.yaml under ai:

10. Development

# Setup
python -m venv venv
.\venv\Scripts\activate        # Windows
pip install -e ".[dev]"

# Run
python -m cli.main --help

# Test
pytest tests/

# Lint / Format
black .
ruff check .

Core dependencies: typer[all], rich, langchain, langchain-google-genai, langchain-openai, langchain-anthropic, pyyaml, python-dotenv, pydantic, asyncio, aiofiles, jinja2


11. Legal & Ethics

⚠️ Guardian is designed exclusively for authorized security testing and educational purposes.
You are fully responsible for obtaining explicit written permission before testing any system.
Unauthorized access is illegal (CFAA, GDPR, and equivalent laws worldwide).