Skip to main content
Glama

GhostMap v2

AI-Augmented Autonomous Network Reconnaissance & Evasion Framework

Python License Status

Legal Disclaimer — This tool is intended strictly for authorized penetration testing, academic research, and lab environments. Always obtain explicit written permission before scanning any network. The author assumes no liability for unauthorized or illegal use.


Overview

GhostMap v2 is a modular AI-augmented red-team reconnaissance framework that autonomously orchestrates the full recon pipeline — from host discovery to exploitation chain synthesis — using Google Gemini Flash as the decision-making engine.

Unlike traditional static scanners, GhostMap v2 makes real-time evasion decisions per host, dynamically adapting its scanning posture based on vendor signatures and risk assessment.


Related MCP server: pentestMCP

Architecture

┌─────────────────────────────────────────────────────────┐
│                     GhostMap v2                         │
├─────────────────────────────────────────────────────────┤
│  Phase 1 │ ARP Host Discovery (arp-scan)                │
│  Phase 3 │ AI Evasion Assessment (Gemini Flash)         │
│          │ → Dynamic T1–T4 speed + MAC spoof decision   │
│  Phase 2 │ Service Fingerprinting (Nmap)                │
│  Phase 2 │ CVE Mapping (NVD API v2 + SQLite cache)      │
│  Phase 4 │ Attack Chain Synthesis (Gemini Flash)        │
│          │ → JSON report saved to disk                  │
└─────────────────────────────────────────────────────────┘

Features

  • AI-Driven Evasion : Gemini Flash dynamically assigns Nmap timing profiles (T1–T4) and MAC spoofing decisions per host based on vendor risk signatures and ambiguity scoring

  • CVE Mapping Pipeline : NVD API v2 integration with local SQLite caching (24h TTL), automatically correlating discovered service versions to CVSS ≥ 7.0 vulnerabilities sorted by severity

  • Attack Chain Synthesis : AI-generated prioritized exploitation chain blueprints from per-host CVE findings for downstream red-team triage

  • MCP Server : All recon capabilities exposed as callable FastMCP tools, enabling AI-agent interoperability and natural language orchestration

  • Throttled Credential Auditing : Hydra integration with single-thread execution and 30s inter-attempt delays to evade standard SIEM detection thresholds

  • Structured Reporting : Timestamped JSON reports per run capturing full topology, open services, CVE findings, and AI-generated attack chain blueprints


Tech Stack

Component

Technology

Language

Python 3.11+

AI Orchestration

Google Gemini 2.5 Flash (free)

MCP Server

FastMCP

CVE Intelligence

NVD API v2 + SQLite cache

Host Discovery

arp-scan

Service Fingerprint

Nmap

Credential Auditing

Hydra

Output Validation

Pydantic

CLI

argparse + colorama


Project Structure

GhostMap/
├── GhostMap.py          # CLI entry point
├── orchestrator.py      # Main pipeline coordinator
├── server.py            # FastMCP server — exposes tools to AI agents
├── cve_mapper.py        # NVD API v2 integration with SQLite caching
├── config.py            # Centralised configuration and constants
├── requirements.txt
├── tools/
│   ├── __init__.py
│   ├── network.py       # MAC spoofing + ARP discovery
│   ├── scanner.py       # Nmap XML parsing wrapper
│   └── auditor.py       # Hydra credential auditing wrapper
└── README.md

Prerequisites

System dependencies:

sudo apt install nmap arp-scan hydra

Python: 3.11 or higher

Gemini API key (free): https://aistudio.google.com/app/apikey


Setup

# Clone the repository
git clone https://github.com/Samir12218415/GhostMap.git
cd GhostMap

# Create and activate virtual environment
python3 -m venv .venv
source .venv/bin/activate

# Install dependencies
pip install -r requirements.txt

# Set your Gemini API key
export GEMINI_API_KEY='your_google_ai_studio_key'

Usage

# Standard run — auto-detects hosts, applies AI evasion
sudo -E .venv/bin/python3 GhostMap.py -i wlan0

# Skip MAC spoofing (useful for isolated lab environments)
sudo -E .venv/bin/python3 GhostMap.py -i wlan0 --no-mac-spoof

# Debug mode — prints raw Nmap scan output per host
sudo -E .venv/bin/python3 GhostMap.py -i wlan0 --debug

# Run on a wired interface
sudo -E .venv/bin/python3 GhostMap.py -i eth0

MCP server (for AI-agent integration):

python3 server.py

Output

Each run produces a timestamped JSON report:

ghostmap_report_20260605_142300.json

Containing per-host: metadata, open services, CVE findings with CVSS scores, and AI-generated attack chain blueprint.


Evasion Profile Logic

Condition

Speed

MAC Spoof

Known security appliance / SIEM

T1

Yes

Unknown vendor / ambiguous host

T2

Yes

Confirmed consumer device (router/NAS)

T3

Optional

Confirmed isolated lab environment

T4

No


This tool is provided for educational and authorized security testing purposes only.

  • Only use on networks you own or have explicit written permission to test

  • Credential auditing features must only be used against systems you are authorized to assess

  • The author accepts no responsibility for misuse or damage caused by this tool


Author

Samir Pandey
B.Tech CSE (Minor: Cybersecurity) — Lovely Professional University
ISC2 Certified in Cybersecurity (CC)
LinkedIn · GitHub

F
license - not found
-
quality - not tested
B
maintenance

Maintenance

Maintainers
Response time
Release cycle
Releases (12mo)
Commit activity

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Related MCP Servers

  • A
    license
    -
    quality
    -
    maintenance
    Enables AI-assisted penetration testing by connecting MCP clients to a Windows API server for executing penetration testing tools like nmap, ffuf, nuclei, and other security tools. Allows AI agents to perform automated security assessments, solve CTF challenges, and assist with ethical hacking tasks through natural language commands.
    Last updated
    10
  • F
    license
    -
    quality
    B
    maintenance
    An MCP server that exposes over 20 standard penetration testing utilities, such as Nmap, SQLMap, and OWASP ZAP, as callable tools for AI agents. It enables natural language control over complex security workflows for automated and interactive penetration testing.
    Last updated
    89
  • A
    license
    -
    quality
    D
    maintenance
    Enables AI assistants to autonomously execute over 200 open-source penetration testing tools via MCP, including reconnaissance, web exploitation, and brute-forcing, through a unified server architecture with Docker sandboxing for safe execution.
    Last updated
    51
    MIT
  • A
    license
    -
    quality
    B
    maintenance
    AI-powered penetration testing framework that can operate as an MCP server, enabling automated security assessments through natural language commands.
    Last updated
    2
    MIT

View all related MCP servers

Related MCP Connectors

  • MCP server for Pentest-Tools.com: run scans, manage findings and reports via your preffered LLM.

  • Security scanner for MCP servers. Detect vulnerabilities, prompt injection, and tool poisoning.

  • OCR, transcription, file extraction, and image generation for AI agents via MCP.

View all MCP Connectors

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Samir12218415/GhostMap-v2-AI-augmented-recon-framework-with-MCP-and-CVE-pipeline'

If you have feedback or need assistance with the MCP directory API, please join our Discord server