In this tutorial, we build a realistic Zero-Trust network simulation by modeling a micro-segmented environment as a directed graph and forcing every request to earn access through continuous verification. We implement a dynamic policy engine that blends ABAC-style permissions with device posture, MFA, path reachability, zone sensitivity, and live risk signals such as anomaly and data-volume indicators. We then operationalize the model through a Flask API and run mixed traffic, including insider-lateral movement and exfiltration attempts, to show how trust scoring, adaptive controls, and automated quarantines block malicious flows in real time.

!pip -q install networkx flask

import math

import json

import time