🧠 AI-VAPT Autonomous AI-Driven Vulnerability Assessment & Penetration Testing Framework
AI-VAPT (Artificial Intelligence – Vulnerability Assessment and Penetration Testing) is a next-generation, fully automated cybersecurity framework that merges artificial intelligence, automation, and traditional penetration testing methodologies to deliver a self-learning, adaptive, and accurate security assessment engine.
It’s designed for pentesters, red teams, and security researchers who want to move beyond manual recon and exploit discovery — into an AI-augmented security testing era.
⚡ Key Highlights
🤖 AI-Augmented Reconnaissance — Uses neural pattern recognition to find hidden assets, misconfigured endpoints, and shadow subdomains.
🔍 Automated Multi-Vector Scanning — Performs Web, Network, API, Cloud, and IoT scans with intelligent prioritization.
🔬 Machine Learning Exploit Prediction — Detects exploitability levels using ML-based vulnerability scoring models.
📊 Smart Reporting Engine — Generates detailed PDF/HTML reports with severity ranking, impact mapping, and remediation paths.
🔒 Privacy by Design — Zero data stored, zero data reused. Fully offline-capable operation mode.
🧩 Modular & Extensible Architecture — Easily plug in new scanners, ML models, or third-party tools.
⚙️ Continuous Security Validation — Supports automated periodic testing pipelines through CI/CD integration.
🧠 Architecture Overview Layer Description AI Layer NLP-driven analysis for exploit prediction, CVE correlation, and anomaly detection. Recon Layer Subdomain, DNS, Port, Directory, and Service enumeration using hybrid AI+dictionary techniques. Vulnerability Layer CVE mapping, version fingerprinting, misconfiguration detection, and exploit validation. Exploitation Layer Controlled exploitation simulation and payload validation (safe mode). Reporting Layer Risk-based visual reporting engine with auto-generated insights and recommendations. 🧰 Integrated Tools
Reconnaissance: Amass, Subfinder, Nmap, Shodan API, CRT.sh
Web Scanning: Nikto, Dirsearch, Wapiti, BurpSuite API
Exploit Mapping: CVE Trends, Exploit-DB, ML-based CVE Exploitability Model
Post-Exploitation: Metasploit integration, local privilege check, token dumping modules
Reporting: AI-generated executive and technical summaries
🧑💻 Use Cases
Automated Red Team Assessments
Continuous Vulnerability Management
AI-assisted Bug Bounty Recon
SOC Validation Testing
Compliance Audits (ISO 27001, NIST, PCI-DSS, etc.)
🧩 1. Prerequisites
#Make sure you have Node.js and npm (or yarn/pnpm) installed: node -v npm -v
#If not installed, run: sudo apt update sudo apt install nodejs npm -y
🚀 Getting Started
git clone https://github.com/vikramrajkumarmajji/AI-VAPT.git
cd AI-VAPT
npm install
yarn install
npm run dev
Then open the displayed local URL (usually http://localhost:5173) in your browser.
npm run build
📈 Future Roadmap
🔹 Integration with LLM-based reasoning engines for contextual vulnerability explanation
🔹 Real-time exploit chain mapping visualization
🔹 Threat intelligence enrichment through OSINT automation
🔹 Cloud-native agent for AWS, Azure, and GCP audits
🛡️ Philosophy
“Security is no more an option — Privacy by design, trust by vision.” — Vikram Raj Kumar Majji