CVE-2025-49132 Standalone Vulnerability Scanner

Non-Docker Implementation

This scanner operates directly on Python without Docker dependencies, suitable for environments where Docker is not available or preferred.

Installation

pip install -r requirements-standalone.txt

Manual installation:

pip install requests urllib3

Usage

1. Single Target Scanning

python standalone_scanner.py scan http://localhost/

2. Batch Scanning from File

Create targets.txt:

http://localhost/
http://localhost:8080
http://localhost:3000

Execute batch scan:

python standalone_scanner.py batch --file targets.txt

3. Output Persistence

python standalone_scanner.py batch --file targets.txt --output results.json

4. Interactive Mode

python standalone_scanner.py interactive

Output Examples

Vulnerable Target:

🔍 Scanning: http://localhost/
⏰ Time: 2025-01-27 15:30:45
------------------------------------------------------------
✅ VULNERABLE - Database credentials found!
📊 Database Info:
   Host: localhost
   Port: 3306
   Database: root
   Username: root
   Password: secret123
🔗 Connection String: root:secret123@localhost:3306/root

✅ VULNERABLE - App configuration found!
📊 App Config:
   App Key: base64:your_secret_key_here
   Cipher: AES-256-CBC
   Debug: false
   Environment: production
   App Name: Pterodactyl
   App URL: http://localhost
   Timezone: UTC
   Locale: en

🔔 SECURITY WARNING: APP_KEY exposed!
   This key is used for encryption/decryption
   Can be used to decrypt sensitive data

Safe Target:

🔍 Scanning: http://localhost/
⏰ Time: 2025-01-27 15:30:45
------------------------------------------------------------
❌ NOT VULNERABLE (Status: 404)

Technical Features

• ✅ Docker-free Operation: Direct Python execution
• ✅ Cross-platform Compatibility: Windows, Linux, macOS
• ✅ Multiple Execution Modes: Single target, batch processing, interactive
• ✅ Structured Output: JSON format for data persistence
• ✅ Robust Error Handling: Comprehensive exception management
• ✅ Progress Monitoring: Real-time scanning progress
• ✅ Analytical Reports: Statistical summary generation
• ✅ Cryptographic Detection: APP_KEY and cipher identification
• ✅ Security Alerts: Automated vulnerability notifications

Comparative Analysis

Feature	Standalone	Container
Setup Complexity	Minimal	Docker-dependent
Dependencies	Python packages	Docker + Python
Performance	Optimized	Comparable
Process Isolation	None	Full isolation
Deployment Portability	High	Medium

Technical Specifications

Network Configuration

• Timeout: 10 seconds (configurable)
• SSL Verification: Disabled for compatibility
• User-Agent: Standard browser simulation
• Request Method: GET only (non-intrusive)

Vulnerability Detection

• Database Configuration Exposure: MySQL/PostgreSQL credentials
• Application Configuration: Laravel/PHP settings
• Cryptographic Keys: APP_KEY identification
• Environment Variables: Production/development settings

Troubleshooting

Module Import Errors:

pip install requests

SSL Certificate Issues:

SSL warnings are automatically suppressed. No additional configuration required.

Connection Timeout:

Default timeout is 10 seconds. Modify timeout parameter in source code if needed.

Security Considerations

Scanner Behavior

• Non-intrusive: Only performs GET requests
• Data Handling: No sensitive data persistence
• Detection Scope: Configuration file exposure
• Exploitation: No active exploitation performed

Risk Assessment

• Database Credentials: Direct database access potential
• Application Keys: Encryption/decryption capability exposure
• Environment Variables: Configuration disclosure
• Attack Surface: Increased vulnerability footprint

Quick Start Guide

# Install dependencies
pip install requests urllib3

# Perform test scan
python standalone_scanner.py scan http://localhost/

# Execute batch analysis
python standalone_scanner.py batch --file targets.txt --output results.json

Technical Architecture

Core Components

1. Scanner Engine: HTTP request processing
2. Parser Module: Response analysis and extraction
3. Vulnerability Detector: Pattern matching and validation
4. Output Formatter: Structured data presentation
5. Error Handler: Exception management and recovery

Data Flow

Target Input → HTTP Request → Response Analysis → Vulnerability Detection → Output Generation

Performance Metrics

• Scan Speed: ~1-3 seconds per target
• Memory Usage: Minimal footprint
• Network Overhead: Single GET request per target
• CPU Utilization: Low computational requirements

Compliance and Ethics

This tool is designed for:

• Security Research: Vulnerability assessment
• Penetration Testing: Authorized security testing
• Educational Purposes: Security awareness training
• Compliance Auditing: Security posture evaluation

Note: Always obtain proper authorization before scanning any target systems.