Visualize Complex
Malware Spreading
in Custom Networks
MSpread empowers researchers and analysts to visualize, simulate, and analyze spread dynamics across complex networks of 10,000+ nodes with unprecedented speed and clarity.
Powerful Capabilities
Everything you need for network analysis
From visualization to deep analytics, MSpread provides a comprehensive suite of tools designed for modern network science.
Real-time Visualization
Watch spread dynamics unfold across networks instantly with our high-performance rendering engine.
Advanced Analytics
Deep dive into node centrality, clustering coefficients, and path lengths with comprehensive tools.
Simulation Engine
Run thousands of Monte Carlo simulations in parallel to predict spread outcomes with high confidence.
AI Integration
Architect and refine complex simulation scenarios using an intuitive AI assistant to create precise network configurations.
Malware Profiling
Define unique propagation behaviors, infection rates, and latency for specific malware strains.
MIT Open Source
The core engine for building networks and simulating malware spreading is fully open source.
Open Source Core
Powered by MSpreadEngine
MSpreadEngine is the core simulation engine component of the MSpread platform. It provides a powerful framework for modeling and simulating malware propagation across networks ranging from small corporate environments to country-wide infrastructures.
Realistic Modeling
Built with Python and NetworkX for precise topology analysis.
High Performance
Optimized simulation engine for massive infrastructure models.
Engine Support
Main Libraries
from network_model import NetworkGraph
from malware_engine.malware_base import Malware
from simulation import Simulator
# Create network
network = NetworkGraph(network_type="scale_free")
network.generate_topology(num_nodes=500, use_parallel=True)
# Create malware
malware = Malware("malware_1", infection_rate=0.5)
# Run simulation
simulator = Simulator(network, malware)
simulator.initialize(["device_0"])
results = simulator.run(max_steps=100)
# Get statistics
stats = simulator.get_statistics()
print(f"Infected: {stats['total_infected']}")
Powerful API for Automated Workflows
Integrate MSpread's simulation engine directly into your security stack. Our robust REST API allows you to automate malware spread simulations, retrieve network configurations, and generate reports programmatically.
import requests
import json
# Authenticate with API Key
headers = {
"X-API-Key": "msp_prod_8273...",
"Content-Type": "application/json"
}
# Start simulation
response = requests.post(
"https://api.mspread.com/v1/simulate",
json={"nodes": 100, "type": "worm"},
headers=headers
)