Core Architecture
The core of Lynort runs fully on the device, offline. It utilizes a sophisticated stack of local AI models to detect and neutralize threats without relying on cloud signatures.
2.1 Local AI Security Engine
Our engine is designed to be lightweight yet powerful, leveraging the Neural Processing Units (NPUs) in modern processors when available, or falling back to optimized CPU/GPU instructions.
Components
Behavioral AI Monitor
Instead of looking for known "bad" file hashes (signatures), our Behavioral AI Monitor observes what a process is doing.
- Unexpected encryption of multiple files (Ransomware behavior).
- Processes attempting to inject code into system services.
- Scripts launching hidden shells or network connections.
Zero-Day Detection Engine
Because we don't rely on signatures, Lynort can spot new, never-before-seen threats (Zero-Days). The AI analyzes the structure and intent of executables before they run.
Memory & Injection Shield
Advanced malware often operates solely in memory to avoid file scanners. Our Shield monitors memory space to block:
AI Threat Correlator
A single event might look innocent, but a sequence of events reveals an attack. The Threat Correlator connects the dots:
Individually, these might be allowed. Together, they trigger a high-severity alert.
Isolation Sandbox
When Lynort encounters a suspicious but not definitively malicious application, it can seamlessly launch it in a lightweight Isolation Sandbox. The app runs normally, but has no permanent access to your file system or network until it proves it is safe.