Your malware’s favorite sandbox – where red teamers come to bury their payloads.
A sandbox environment designed specifically for malware development and payload testing.
This Web Application enables red teamers to validate evasion techniques, assess detection signatures, and test implant behavior before deployment in the field.
Think of it as your personal LitterBox for perfecting your tradecraft without leaving traces on production detection systems.
The platform provides automated analysis through an intuitive web interface, monitoring process behavior and generating comprehensive runtime analysis reports.
This ensures your payloads work as intended before execution in target environments.
Features
Initial Analysis
- File identification with multiple hashing algorithms (MD5, SHA256)
- Shannon entropy calculation for encryption detection
- Advanced file type detection and MIME analysis
- Original filename preservation
- Upload timestamp tracking
PE File Analysis
For Windows executables (.exe, .dll, .sys):
- PE file type detection (PE32/PE32+)
- Machine architecture identification
- Compilation timestamp analysis
- Subsystem classification
- Entry point detection
- Section enumeration and analysis
- Import DLL dependency mapping
Office Document Analysis
For Microsoft Office files (.docx, .xlsx, .doc, .xls, .xlsm, .docm):
- Macro detection and extraction
- VBA code analysis
- Hidden content identification
Analysis Capabilities
Static Analysis Engine
- Signature-based detection using industry-standard rulesets
- Binary entropy analysis
- String extraction and analysis
- Pattern matching for suspicious indicators
Dynamic Analysis Engine
Available in two modes:
- File Analysis Mode
- Process ID (PID) Analysis Mode
Features include:
- Behavioral monitoring
- Memory region inspection
- Process hollowing detection
- Injection technique analysis
- Sleep pattern monitoring
- PE integrity verification
Integrated Tools
Static Analysis Suite
Dynamic Analysis Suite
- YARA (memory scanning) – Runtime pattern detection
- PE-Sieve – Process and memory inspection
- Moneta – Sleep pattern analysis
- Patriot – Runtime monitoring
- Hunt-Sleeping-Beacons – Beacon behavior analysis
API Reference
File Operations
POST /upload # Upload files for analysis
GET /analyze/static/<hash> # Static file analysis
POST /analyze/dynamic/<hash> # Dynamic file analysis
POST /analyze/dynamic/<pid> # Process analysis
GET /files # Get list of processed files
GET /file/<hash>/info # Get file info
GET /file/<hash>/static # Get results for file static analysis
GET /file/<hash>/dynamic # Get results for file dynamic analysis
DELETE /file/<hash> # Delete single analysis
System Management
GET /health # System health and tool status check
POST /cleanup # Clean analysis artifacts and uploads
POST /validate/<pid> # Validate process accessibility
Installation
Prerequisites
- Python 3.11 or higher
- Administrator privileges (required for certain features)
- Windows operating system (required for specific analyzers)
Setup Steps
Clone the repository:
git clone https://github.com/BlackSnufkin/LitterBox.git<br>cd LitterBox
Install required dependencies:
pip install -r requirements.txt
Running LitterBox
python litterbox.py
The web interface will be available at: http://127.0.0.1:1337
Configuration
The config.yml
file controls:
- Upload directory and allowed extensions
- Analysis tool paths and Command options
- YARA rule locations
- Analysis timeouts and limits
SECURITY WARNINGS
- DO NOT USE IN PRODUCTION: This tool is designed for development and testing environments only. Running it in production could expose your systems to serious security risks.
- ISOLATED ENVIRONMENT: Only run LitterBox in an isolated, disposable virtual machine or dedicated testing environment.
- NO WARRANTY: This software is provided “as is” without any guarantees. Use at your own risk.
- LEGAL DISCLAIMER: Only use this tool for authorized testing purposes. Users are responsible for complying with all applicable laws and regulations.
Acknowledgments
This project incorporates the following open-source components and acknowledges their authors:
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