Professional AI-Powered Web Application Security Testing Platform
Follow this link to view our catalog on WhatsApp: https://wa.me/c/6287726594969
Versi-2.0 ini dilengkapi dengan RAG Enhanced
VYOMA is an enterprise-grade security scanner that combines traditional penetration testing with cutting-edge AI analysis to provide
comprehensive web application security assessment. Designed for security professionals, developers, and organizations that require advanced
vulnerability detection and risk assessment capabilities.
Key Features
AI-Powered Intelligence
- LLaMA 3.2 Integration: Advanced AI model for intelligent vulnerability analysis
- Smart Payload Generation: Context-aware exploit payloads
- Chain Attack Detection: Identifies multi-step exploitation paths
- Risk Assessment: AI-driven vulnerability prioritization
- Executive Summaries: Business impact analysis and recommendations
Comprehensive Testing
- OWASP Top 10 2021 Coverage: Complete testing of all categories
- A01:2021 - Broken Access Control
- A02:2021 - Cryptographic Failures
- A03:2021 - Injection
- A04:2021 - Insecure Design
- A05:2021 - Security Misconfiguration
- A06:2021 - Vulnerable and Outdated Components
- A07:2021 - Identification and Authentication Failures
- A08:2021 - Software and Data Integrity Failures
- A09:2021 - Security Logging and Monitoring Failures
- A10:2021 - Server-Side Request Forgery (SSRF)
DevSecOps Integration
- CI/CD Pipeline Integration: Ready-to-use configurations for GitHub Actions, GitLab CI, and Jenkins
- Security Gates: Automated pipeline failures based on vulnerability thresholds
- Shift-Left Security: Catch vulnerabilities early in development cycle
- Artifact Archiving: Compliance reporting and review capabilities
- Environment Configuration: Easy setup through environment variables
Professional Interface
- Modern GUI: Burp Suite-inspired blue-gray theme
- Real-time Monitoring: Live vulnerability detection
- Color-coded Severity: Critical (Red), High (Orange), Medium (Yellow), Low (Blue)
- Multiple Views: Console, Vulnerabilities, Summary, AI Analysis
- Export Options: HTML and JSON reports
Scan Modes
1. Basic Scan
- Speed: Fast scan for quick assessment
- Features: Common security issues, minimal AI overhead
- Best For: Quick initial assessment, time-sensitive scans
2. Medium Scan (Default)
- Speed: Standard scan with comprehensive coverage
- Features: OWASP Top 10 testing, AI-powered vulnerability analysis
- Best For: Standard security assessment, regular testing
3. Aggressive Scan
- Speed: Thorough and comprehensive scanning
- Features: Deep penetration testing, chain attack detection
- Best For: Thorough security audit, pre-production testing
Technical Specifications
System Requirements
- Operating Systems: Windows 10/11, Linux (Ubuntu 20.04+, Kali Linux, Parrot OS, Debian, Fedora, Arch), macOS 11+
- Python: 3.8 or higher
- RAM: Minimum 4GB (8GB+ recommended)
- Storage: 5GB free space (10GB+ recommended)
- Internet: Required for initial setup and AI model access
Supported Platforms
- Kali Linux: Fully tested and optimized
- Parrot Security OS: Complete compatibility
- Ubuntu: 20.04, 22.04, 24.04 versions
- Debian: Versions 11, 12
- Windows: 10 and 11
- macOS: Versions 11 and later
Target Users
- Security Professionals: Comprehensive penetration testing
- Developers: Pre-deployment security checks and CI/CD integration
- Organizations: Regular security assessments and compliance
- Students: Learning security testing concepts and tools
Development Roadmap
Phase 1 Completed Features
- DevSecOps Pipeline Integration: Seamless integration with GitHub Actions, GitLab CI, Jenkins
- Microservices Architecture: Modular service components
- Advanced AI Integration: Multiple AI model support
- Performance Optimization: Improved speed and efficiency
Future Enhancements
- Cloud Security Assessment: AWS, Azure, GCP security testing
- Mobile Application Security: Static and dynamic mobile app analysis
- Container & Serverless Security: Docker and Kubernetes assessment
- Secure Code Checking: Static code analysis (SAST) integration
- Quantum-Resistant Assessment: Post-quantum cryptography evaluation
- IoT and Industrial Security: IoT device security modules
Developer Information
- Developer: Cahyo Darujati
- Email: cahyod@yahoo.co.id
- Support: Cybersecurity Indonesia (https://www.cybersecurity.or.id/)
Licensing & Legal
- License: MIT License
- Usage: Authorized security testing only
- Compliance: Designed for educational and authorized penetration testing
- Legal Notice: Only scan systems you own or have explicit permission to test
Value Proposition
"Precision Testing for Modern Cyber Risks"
VYOMA combines the vast analytical capabilities of AI with comprehensive security testing methodologies to deliver precision vulnerability detection. The platform's philosophy of "boundless space" represents its comprehensive, deep, and extensive analysis capabilities that go far beyond conventional security tools.
The platform maps risks with precision, prioritizes mitigation efforts, and provides strategic, measurable recommendations to help organizations achieve a strong, adaptive security posture ready to face modern threats.
Follow this link to view our catalog on WhatsApp: https://wa.me/c/6287726594969
Vyoma-2.0 - RAG Enhanced
Versi ini sudah dilengkapi dengan RAG Enhanced
> apa itu RAG-Enhanced?
✦ RAG-Enhanced mengacu pada sistem AI yang menggunakan Retrieval-Augmented Generation (RAG), yang merupakan teknik lanjutan dalam kecerdasan buatan yang menggabungkan kemampuan model bahasa besar (LLM) dengan akses ke informasi eksternal dan kontekstual secara real-time.
Dalam konteks Vyoma AI Security Scanner 2.0, RAG-Enhanced memiliki arti spesifik berikut:
I. Definisi RAG (Retrieval-Augmented Generation)
RAG adalah pendekatan yang menggabungkan:
- Retrieval (Pengambilan): Mencari dan mengambil informasi relevan dari sumber eksternal
- Augmentation (Peningkatan): Menambahkan konteks tambahan ke permintaan AI
- Generation (Pembuatan): Menghasilkan jawaban atau analisis berdasarkan informasi yang ditingkatkan
II. Komponen RAG-Enhanced dalam Vyoma 2.0
1. Vector Database (ChromaDB)
- Menyimpan informasi keamanan dalam format yang memungkinkan pencarian semantik
- Menggunakan teknik embedding untuk menyimpan dan mengambil informasi keamanan
2. Security Knowledge Base
- Basis pengetahuan keamanan dinamis yang menyimpan data CVE (Common Vulnerabilities and Exposures) terbaru
- Mengintegrasikan informasi dari API NIST NVD untuk CVE terkini
- Mencakup pengetahuan tentang tipe kerentanan, solusi, dan praktik terbaik keamanan
3. Kemampuan Spesifik RAG-Enhanced
3.1. Pengambilan Kontekstual
- Saat menganalisis kerentanan, sistem mencari informasi terkait dari basis pengetahuan keamanan
- Mengambil informasi tentang CVE serupa, teknik eksploitasi terbaru, dan solusi terbaik
3.2. Analisis Bergaya Kontekstual
- Bukannya hanya menggunakan pengetahuan statis dalam model AI, sistem menggabungkan informasi terbaru dari basis pengetahuan.
- Ini membuat analisis lebih akurat dan relevan dengan ancaman saat ini.
3.3. Pembaruan CVE Otomatis
- Sistem secara otomatis mengambil CVE terbaru dari database publik (seperti NVD)
- Hal ini memastikan bahwa informasi keamanan selalu diperbarui
- Fungsi update_cve_from_external_sources() secara otomatis mengambil CVE terbaru setiap 30 hari
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