MetaShield - Advanced Forensic Analysis Tool

🛡️ Overview

MetaShield is a comprehensive digital forensics tool designed for advanced steganography detection, metadata analysis, and malware identification. This application provides forensic investigators to analyze suspicious files and detect hidden threats.

✨ Key Features

🔍 Advanced Steganography Detection

• LSB (Least Significant Bit) Analysis: Detects hidden data in image files using statistical entropy analysis
• Steghide Integration: Automated password-based extraction with support for multiple file formats
• Frequency Analysis: Identifies suspicious patterns in file structure
• Multi-layer Detection: Combines multiple detection algorithms for comprehensive analysis

🧬 Comprehensive Metadata Analysis

• EXIF Data Extraction: Complete metadata analysis for image files
• Suspicious Pattern Detection: Identifies keywords and anomalies in metadata
• File Signature Analysis: Validates file integrity and detects format inconsistencies
• Advanced Binary Analysis: Deep inspection of file structures

🦠 Malware Detection & Analysis

• VirusTotal Integration: Real-time scanning using VirusTotal API
• Behavioral Analysis: Identifies suspicious file behaviors and patterns
• Risk Assessment: Calculates comprehensive threat scores
• Multi-engine Scanning: Leverages multiple detection engines

📊 Professional Reporting

• PDF Reports: Detailed forensic reports with charts and analysis
• CSV Data Export: Raw data for further analysis
• Real-time Dashboard: Interactive GUI with risk visualization
• Evidence Export: Secure extraction and documentation of findings

🚀 Installation

Prerequisites

# Python 3.7 or higher
python --version

# Required system tools
# For Windows: Download steghide from http://steghide.sourceforge.net/
# For Linux: sudo apt-get install steghide
# For macOS: brew install steghide

Install Dependencies

# Install required Python packages
pip install -r requirements.txt

Required packages:

numpy
pillow
tkinter
exifread
requests
reportlab
stegano

VirusTotal API Setup

1. Register at VirusTotal
2. Obtain your API key
3. Replace XXXXXXXXXXX in the code with your actual API key

📖 Usage

Quick Start

1. Launch the Application

   python MetaShield.ipynb  # or run in Jupyter

2. Select Target File

   • Click "Browse File" to select the file for analysis
   • Supports: Images (JPG, PNG, GIF, BMP), Audio (WAV), Executables

3. Configure Analysis Options

   • ✅ Metadata Analysis
   • ✅ LSB Steganography Detection
   • ✅ Steghide Detection
   • ✅ Frequency Analysis
   • ✅ VirusTotal Scanning
   • ✅ Advanced Binary Analysis

4. Run Analysis

   • Click "🔍 Start Analysis"
   • Monitor progress in real-time
   • View results in organized tabs

Advanced Configuration

Steghide Setup

1. Download steghide executable
2. Click "Browse Steghide" to locate the executable
3. Test configuration with "Test" button

Custom Password Lists

Modify the common_passwords list in the code to include domain-specific passwords:

self.common_passwords = [
    '', 'password', '123456', 'secret', 'hidden',
    'custom_password1', 'custom_password2'  # Add your passwords
]

🔧 Technical Specifications

Supported File Formats

Category	Formats	Detection Methods
Images	JPG, PNG, GIF, BMP	LSB, Steghide, Metadata

Detection Algorithms

1. Shannon Entropy Analysis: Measures data randomness to detect hidden content
2. Statistical LSB Detection: Analyzes bit plane patterns in images
3. Signature-based Detection: Identifies file format anomalies
4. Password Dictionary Attack: Tests common passwords for steghide extraction
5. Behavioral Pattern Analysis: Detects suspicious file behaviors

Risk Assessment Matrix

Score Range	Risk Level	Description
0-25	🟢 Low	File appears clean with no significant threats
26-50	🟡 Medium	Some suspicious indicators detected
51-75	🟠 High	Multiple threat indicators present
76-100	🔴 Critical	Confirmed malicious content detected

📊 Output Examples

Console Output

[MetaShield] Analyzing: suspicious_image.jpg
[STEGANOGRAPHY] LSB detection: POSITIVE (Confidence: 87%)
[METADATA] Suspicious keywords found in EXIF data
[VIRUSTOTAL] 3/70 engines detected malware
[RISK ASSESSMENT] Overall Score: 72/100 (HIGH RISK)

Report Structure

📄 MetaShield Forensic Report
├── 📋 Executive Summary
├── 🔍 Detection Results
│   ├── Steganography Analysis
│   ├── Metadata Examination
│   ├── Malware Scanning
│   └── Binary Analysis
├── 📊 Risk Assessment
├── 🎯 Recommendations
└── 📎 Evidence Files

⚠️ Important Notes

Legal Compliance

• Educational Use Only: This tool is designed for educational and research purposes
• Authorization Required: Only analyze files you own or have explicit permission to examine
• Compliance: Ensure usage complies with local laws and regulations

Performance Considerations

• Large Files: Analysis time increases with file size
• Memory Usage: Complex images may require significant RAM
• Network Dependency: VirusTotal scanning requires internet connection

Security Warnings

• Extracted Content: Be cautious when handling extracted hidden files
• Malware Risk: Quarantine systems when analyzing suspected malware
• Data Privacy: Avoid uploading sensitive files to VirusTotal

🛠️ Development

Architecture

MetaShield/
├── Core Engine/
│   ├── AdvancedSteganographyDetector
│   ├── MetadataAnalyzer
│   └── RiskAssessment
├── GUI Interface/
│   ├── Control Panel
│   ├── Results Display
│   └── Report Generator
└── Integration/
    ├── VirusTotal API
    ├── Steghide Interface
    └── Export Functions

Extending Functionality

Adding New Detection Methods

def custom_detection_method(self, file_path):
    """Custom detection implementation"""
    results = {'method': 'Custom', 'found': False}
    # Your detection logic here
    return results

Custom Risk Scoring

def calculate_custom_risk(self, analysis_result):
    """Custom risk calculation"""
    risk_score = 0
    # Your scoring logic here
    return risk_score

🤝 Contributing

We welcome contributions from the cybersecurity community:

1. Bug Reports: Submit detailed issue reports
2. Feature Requests: Propose new detection methods
3. Code Contributions: Follow coding standards and include tests
4. Documentation: Improve guides and examples

📜 License

This project is released under an Educational License. See LICENSE file for details.

🙏 Acknowledgments

• Steghide Project: For steganography detection capabilities
• VirusTotal: For malware detection API
• Python Community: For excellent libraries and tools
• Cybersecurity Researchers: For sharing knowledge and techniques

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⚠️ Disclaimer: MetaShield is provided for educational and research purposes only. Users are responsible for ensuring compliance with applicable laws and regulations. The developers assume no liability for misuse of this tool.

🔒 Security Notice: Always run suspicious file analysis in isolated environments to prevent potential system compromise.