Vision

🚨 Tensorprox by Shugo.io is building the future of decentralized cybersecurity.
Our journey is shaped by 4 powerful phases:
1️⃣ Foundation Forge – Core architecture, synthetic attack simulation, performance-based competition ✅
2️⃣ Maturity – Smarter detection, faster scaling, cooperative defense 🧠
3️⃣ Integration – One-click, plug-and-play protection for any user or subnet node 🔌
4️⃣ Expansion – Enterprise-grade, globally redundant, threat-intelligent defense 🌍
We’re done laying the foundation—soon, anyone can deploy powerful DDoS protection in seconds.
From sandbox to safeguard, Tensorprox is making protection automatic, scalable, and decentralized.

Introduction

Tensorprox introduces a novel approach to DDoS protection with a distributed architecture and an innovative incentive mechanism powered by the Bittensor Network. The validation process leverages synthetic traffic generation, alternating between normal and malicious network behaviors to simulate realistic attack scenarios. This project aims to evolve into a global cybersecurity solution, tackling the most complex security challenges.

Core Conceptual Design

Tensorprox redefines distributed DDoS mitigation by simulating complex network environments and evaluating miner performance in high-stress scenarios. The subnet operates on a unique distributed network architecture where:

Validators challenge miners by simulating real-world DDoS scenarios
Miners provide DDoS protection services
Performance is evaluated through comprehensive traffic analysis

It employs a novel architectural design to build a robust and adaptable mitigation system. This design strategically positions key components to ensure comprehensive protection of the target server, referred to as the "King".

King: It represents the target server requiring protection.

Traffic generators: These machines (tgens) generate a blend of traffic, dynamically configured per round to simulate varying network conditions, including DDoS spikes and legitimate traffic flows.

Moat: It is run by miners and acts as a routing firewall. The Moat leverages Advanced Forwarding eXpress Data Path (AF_XDP) for high-performance packet processing.

The system works by positioning the Moat strategically between the traffic generators and the King. All traffic must pass through the Moat, which analyzes and filters it based on pre-defined rules and dynamically learned patterns.

Note: For scalability reasons, access to the traffic generator and King machines must be provided by the miner to the validator via SSH connections.

Scalable and Balanced Network Growth

Tensorprox enables progressive scalability through competitive bandwidth handling, allowing miners to gradually increase the number of tgen machines over time. This design incentivizes miners to process higher volumes of network traffic (see Reward Mechanism), promoting scale and performance. To prevent abuse and ensure quality, the multi-factor reward function balances throughput with traffic filtering accuracy and latency efficiency. Miners must maintain a high mitigation ratio and low response times to benefit from additional tgen deployments, fostering a natural equilibrium between scale and effectiveness.