Active Kinetic Defense: The Synzcuor Ecosystem
We bridge the gap between low-level kernel software and physical active-defense hardware, providing real-time protection for enterprise and consumer systems.
Synz Intercept
Hardware FailsafeAn inline hardware appliance that sits physically between the network and critical equipment (like power grids, medical devices, or assembly line PLCs).
Built on custom carrier boards housing System-on-Modules with dual Gigabit Ethernet ports. Inside is a physical Normally Closed (NC) Solid-State Relay wired directly to a CPU GPIO pin. If a threat is detected, the software pulls the GPIO pin high, physically snapping the relay open and cutting the copper Ethernet connection in under 50 microseconds to air-gap the system.
Technical Specifications
Synz Prism
CDR SoftwareA lightweight, software-only Content Disarm and Reconstruction (CDR) agent for laptops and home offices.
Automatically intercepts file downloads locally. If a file is flagged as suspicious, Prism strips active threats—such as macros in Office documents (vbaProject.bin) or Javascript triggers in PDFs (/Launch, /JS)—and reconstructs a clean, threat-free copy in-place. All processing is 100% local, preserving absolute data privacy.
Technical Specifications
Synz Phantom
Core Service EngineThe core local background service and orchestrator governing both appliances and software endpoints.
Acts as the background daemon that controls Synz Intercept appliances and Synz Prism software agents. It securely loads the encrypted ONNX model (.onnx.enc) in memory, parses incoming raw packets, decrypts session tokens, and manages real-time telemetry flows to the control plane.
Technical Specifications
Synz Core
Control ConsoleThe air-gapped management console and central registry for enterprise security teams.
Built in ASP.NET Core (API and Portal), Synz Core runs as a localized or air-gapped server. It aggregates fleet telemetry logs, routes event metrics to Splunk/SIEM systems, logs NERC CIP / IEC 62443 compliance indices, and manages the training 'Foundry' where QGAN neural models are compressed.
Technical Specifications
The Shared Quantum Threat Engine
Our proprietary Split-Head Quantum Generative Adversarial Network (QGAN) powers active anomaly detection across the entire platform.
Massive Training Dataset
The neural threat engine is trained against a corpus of 22.8 million real cybersecurity samples. By synthesizing zero-day threat patterns, the QGAN detects novel intrusion loops without relying on signature files.
Split-Head Architecture
The model evaluates threats on two vectors simultaneously: Network Head evaluates packet structures and entropy. CPU Head monitors host machine Performance Counters (PMUs) to detect CPU cache-miss anomalies caused by ransomware loops.
TT-SVD Compression
Using Tensor Train SVD Decomposition, we reduce model parameter weight sizes by 91% down to just **0.02 MB**, enabling real-time local execution at sub-50 microsecond latencies.