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LitterBox

single grumpy cat

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.

Python 3.11+ License GitHub Stars

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
  • Collect Windows telemetry via ETW

Doppelganger Analysis

Doppelganger helps you analyze payload in two ways:

Blender

Looks at what's running on your system by:

  • Scanning active processes to collect IOCs
  • Comparing these IOCs with your payload
  • Showing you which processes are the closest matches

FuzzyHash

Helps you find similar code by:

  • Storing known tools in a database
  • Using ssdeep to compare your payload with open-source tools
  • Showing matches in a simple way, with both overall and specific scores

Integrated Tools

Static Analysis Suite

Dynamic Analysis Suite

  • YARA (memory scanning) - Runtime pattern detection
  • PE-Sieve - Detecting and dumping in-memory malware implants and advanced process injection techniques
  • Moneta - Usermode memory analysis tool to detect malware IOCs
  • Patriot - Detecting various kinds of in-memory stealth techniques
  • RedEdr - Collect Windows telemetry via ETW providers
  • Hunt-Sleeping-Beacons - Beacon behavior analysis
  • Hollows-Hunter - Recognizes variety of potentially malicious implants (replaced/implanted PEs, shellcodes, hooks, in-memory patches).

Web Endpoint Reference

File Management

POST   /upload                    # Upload files for analysis
GET    /files                     # Get list of processed files

Analysis Operations

GET    /analyze/static/<hash>     # Static file analysis
POST   /analyze/dynamic/<hash>    # Dynamic file analysis  
POST   /analyze/dynamic/<pid>     # Process analysis

Doppelganger Analyzer

# Blender Analyzer
GET    /doppelganger?type=blender               # Retrieve latest blender scan
GET    /doppelganger?type=blender&hash=<hash>   # Compare processes with payload  
POST   /doppelganger                            # Trigger system scan with {"type": "blender", "operation": "scan"}

#FuzzyHash Analyer
GET    /doppelganger?type=fuzzy                 # Get current fuzzy analysis stats
GET    /doppelganger?type=fuzzy&hash=<hash>     # Analyze file with fuzzy hashing
POST   /doppelganger                            # Create DB with {"type": "fuzzy", "operation": "create_db", "folder_path": "C:\path\to\folder"}

API Results (JSON)

GET    /api/results/<hash>/info      # Get Json file info
GET    /api/results/<hash>/static    # Get Json results for file static analysis
GET    /api/results/<hash>/dynamic   # Get Json results for file dynamic analysis
GET    /api/results/<pid>/dynamic    # Get Json results for pid analysis

Web Results

GET    /results/<hash>/info      # Get file info
GET    /results/<hash>/static    # Get results for file static analysis
GET    /results/<hash>/dynamic   # Get results for file dynamic analysis
GET    /results/<pid>/dynamic    # Get results for pid analysis

System Management

GET  /health                 # System health and tool status check
POST /cleanup                # Clean analysis artifacts and uploads
POST /validate/<pid>         # Validate process accessibility
DELETE /file/<hash>          # Delete single analysis

Installation

Prerequisites

  • Python 3.11 or higher
  • Administrator privileges (required for certain features)
  • Windows operating system (required for specific analyzers)

Setup Steps

  1. Clone the repository:
git clone https://github.com/BlackSnufkin/LitterBox.git
cd LitterBox
  1. Install required dependencies:
pip install -r requirements.txt

Running LitterBox

python litterbox.py

Running LitterBox in debug mode

python litterbox.py --debug

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:

Screenshots

upload

dynamic

static

doppelganger

summary