MLSecScan Development
Otsmane Ahmed
MLSecScan
MLSecScan is an advanced web application vulnerability scanner that combines machine learning with traditional security testing techniques. It provides real-time scanning capabilities, intelligent vulnerability detection, and a modern web dashboard for monitoring scan progress and results.
Table of Contents
Features
Core Capabilities
Intelligent Crawling
Advanced URL discovery
Smart filtering and prioritization
Depth-controlled crawling
Resource-aware scanning
ML-Based Detection
Anomaly detection models
Pattern recognition
Adaptive learning
False positive reduction
Real-Time Dashboard
Live progress monitoring
Interactive statistics
Dynamic vulnerability updates
Performance metrics
Security Testing
Comprehensive Testing
SQL Injection detection
Error-based detection
Time-based detection
Boolean/Union-based detection
Cross-Site Scripting (XSS) detection
Custom vulnerability signature support
Path traversal detection
File inclusion vulnerabilities
Security Features
Tor proxy support for anonymous scanning
Rate limiting and request throttling
SSL verification options
Cookie handling and session management
Request randomization
User-agent rotation
Analytics and Reporting
Advanced Analytics
Vulnerability distribution visualization
Response time analysis
Error rate tracking
Custom signature matching
Parameter-based vulnerability grouping
Sorted vulnerability reporting
Enhanced Reporting
Parameter-based vulnerability organization
Sorted vulnerability counts by parameter
Detailed vulnerability grouping
Interactive vulnerability charts
Exportable HTML reports
Customizable report formats
Configuration Options
Flexible Configuration
Customizable scan depth
Adjustable thread count
Configurable timeouts
Custom payload support
Memory usage optimization
Batch processing options
Installation
Prerequisites
Python 3.8 or higher
Tor service (optional, for anonymous scanning)
Git
pip (Python package manager)
System Requirements
Linux/Unix-based system (recommended)
Minimum 4GB RAM
2GB free disk space
Network connectivity
Installation Steps
Clone the repository:
Install dependencies:
Start Tor service (optional):
Quick Start
Run a basic scan:
Access the dashboard at
http://localhost:5000 to monitor the scan progress.Usage
Basic Usage
Command Line Options
Essential Options
--url: Target URL to scan--file: File containing URLs to scan--depth: Maximum crawl depth (default: 2)--threads: Number of concurrent threads (default: 3)Security Options
--no-tor: Disable Tor proxy--verify-ssl: Enable SSL verification--max-errors: Maximum errors per URL before skipping (default: 5)Output Options
--output-dir: Directory for output files--custom-config: Path to custom configuration fileML Options
--ml-model: Path to custom ML model file--no-ml: Disable ML-based detectionAdvanced Options
--add-signature: Add custom vulnerability signature--list-signatures: List all custom signaturesUsage Examples
Basic scan with default settings:
Deep scan with multiple threads:
Scan with custom ML model:
Scan multiple URLs from file:
Web Dashboard
The web dashboard provides real-time monitoring of the scan progress and results. Access it at:
Dashboard Features
Live progress tracking
Vulnerability statistics
Response time analysis
Error rate monitoring
Interactive charts
Export capabilities
Parameter-based vulnerability grouping
Sorted vulnerability counts
Detailed vulnerability reports
Enhanced Reporting Features
The scanner provides comprehensive reporting capabilities:
Parameter-Based Grouping
Vulnerabilities grouped by parameters
Hierarchical organization
Quick identification of critical issues
Detailed Vulnerability Information
Parameter name
Vulnerability type
Affected URL
Detailed description
Severity level
Remediation suggestions
Interactive Visualization
Vulnerability distribution charts
Response time graphs
Error rate analysis
Custom chart generation
Export Options
HTML report generation
Custom report formats
Data export capabilities
Report customization
Configuration
Default Configuration
The default configuration is stored in
config.json. You can modify:Scan parameters
ML model settings
Dashboard options
Proxy settings
Rate limiting rules
Custom Signatures
Add custom vulnerability signatures:
Security Considerations
Always obtain permission before scanning websites
Use responsibly and ethically
Consider rate limiting and resource usage
Follow security best practices
Keep the tool and dependencies updated
Monitor system resource usage
Implement proper error handling
Use secure configurations
License
This project is licensed under the MIT License - see the LICENSE file for details.
Developed by Otsmane Ahmed
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Posted Jun 11, 2025
Developed MLSecScan, a web app vulnerability scanner with ML.
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Timeline
Feb 2, 2025 - Mar 31, 2025
