How to Build a Dynamic Zero-Trust Network Simulation with Graph-Based Micro-Segmentation, Adaptive Policy Engine, and Insider Threat Detection

!pip -q install networkx flask

import math
import json
import time
import random
import hashlib
from dataclasses import dataclass, field
from typing import Dict, Any, List, Tuple, Optional

import networkx as nx
from flask import Flask, request, jsonify

import matplotlib.pyplot as plt

def _sigmoid(x: float) -> float:
return 1.0 / (1.0 + math.exp(-x))

def _clamp(x: float, lo: float = 0.0, hi: float = 1.0) -> float:
return max(lo, min(hi, x))

def _now_ts() -> float:
return time.time()

def _stable_hash(s: str) -> int:
h = hashlib.sha256(s.encode(“utf-8”)).hexdigest()
return int(h[:10], 16)

def _rand_choice_weighted(items: List[Any], weights: List[float]) -> Any:
return random.choices(items, weights=weights, k=1)[0]

def _pretty(obj: Any) -> str:
return json.dumps(obj, indent=2, sort_keys=False)

ZONES = [“public”, “dmz”, “app”, “data”, “admin”]
SENSITIVITY = {“public”: 0.15, “dmz”: 0.35, “app”: 0.6, “data”: 0.85, “admin”: 0.95}

ASSETS = {
“public”: [“cdn”, “landing”, “status”],
“dmz”: [“api_gateway”, “waf”, “vpn”],
“app”: [“orders_svc”, “billing_svc”, “ml_inference”, “inventory_svc”],
“data”: [“customer_db”, “ledger_db”, “feature_store”],
“admin”: [“iam”, “siem”, “backup_vault”]
}

ACTIONS = [“read”, “write”, “deploy”, “admin”, “exfiltrate”]

ROLES = [“customer”, “employee”, “analyst”, “engineer”, “admin”, “secops”]

DEVICE_TYPES = [“managed_laptop”, “managed_server”, “byod_phone”, “unknown_iot”]
NETWORK_CONTEXT = [“corp_lan”, “corp_vpn”, “public_wifi”, “tor_exit”]

@dataclass
class RequestContext:
user: str
role: str
device_id: str
device_type: str
device_posture: float
mfa: bool
source: str
src_node: str
dst_node: str
action: str
time_bucket: str
geo_risk: float
behavior_anomaly: float
data_volume: float
reason: str = “”

@dataclass
class Decision:
allowed: bool
trust_score: float
rule_hits: List[str] = field(default_factory=list)
controls: Dict[str, Any] = field(default_factory=dict)
explanation: str = “”
ts: float = field(default_factory=_now_ts)

@dataclass
class PrincipalState:
user: str
role: str
base_risk: float
last_seen_ts: float
rolling_denies: int = 0
rolling_allows: int = 0
quarantined: bool = False
compromise_score: float = 0.0

@dataclass
class DeviceState:
device_id: str
device_type: str
owner: str
posture: float
attested: bool
quarantined: bool = False

@dataclass
class FlowRecord:
ts: float
ctx: Dict[str, Any]
decision: Dict[str, Any]

def build_microsegmented_graph(seed: int = 7) -> nx.DiGraph:
random.seed(seed)
G = nx.DiGraph()

for z in ZONES:
G.add_node(f”zone:{z}”, kind=”zone”, zone=z, sensitivity=SENSITIVITY[z])

for z, assets in ASSETS.items():
for a in assets:
node = f”{z}:{a}”
G.add_node(node, kind=”asset”, zone=z, sensitivity=SENSITIVITY[z] + random.uniform(-0.05, 0.05))
G.add_edge(f”zone:{z}”, node, kind=”contains”)

allowed_paths = [
(“public”, “dmz”),
(“dmz”, “app”),
(“app”, “data”),
(“admin”, “app”),
(“admin”, “data”),
(“admin”, “dmz”),
(“dmz”, “admin”)
]

for src_z, dst_z in allowed_paths:
G.add_edge(f”zone:{src_z}”, f”zone:{dst_z}”, kind=”zone_route”, base_allowed=True)

for src_z, dst_z in allowed_paths:
for src_a in ASSETS[src_z]:
for dst_a in ASSETS[dst_z]:
if random.random() < 0.45:
G.add_edge(f”{src_z}:{src_a}”, f”{dst_z}:{dst_a}”, kind=”service_call”, base_allowed=True)

for z in ZONES:
for a in ASSETS[z]:
if random.random() < 0.35:
G.add_edge(f”{z}:{a}”, f”{z}:{a}”, kind=”self”, base_allowed=True)

return G

def draw_graph(G: nx.DiGraph, title: str = “Zero-Trust Microsegmented Network Graph”) -> None:
plt.figure(figsize=(14, 9))
pos = nx.spring_layout(G, seed=42, k=0.35)
kinds = nx.get_node_attributes(G, “kind”)
node_colors = []
for n in G.nodes():
if kinds.get(n) == “zone”:
node_colors.append(0.85)
else:
node_colors.append(G.nodes[n].get(“sensitivity”, 0.5))
nx.draw_networkx_nodes(G, pos, node_size=350, node_color=node_colors)
nx.draw_networkx_edges(G, pos, arrows=True, alpha=0.25)
nx.draw_networkx_labels(G, pos, font_size=8)
plt.title(title)
plt.axis(“off”)
plt.show()

class ZeroTrustPolicyEngine:
def __init__(self, G: nx.DiGraph):
self.G = G
self.principals: Dict[str, PrincipalState] = {}
self.devices: Dict[str, DeviceState] = {}
self.flow_log: List[FlowRecord] = []
self.blocked_edges: set = set()
self.policy_version = “ztpe-v1.3”

self.role_perms = {
“customer”: {“public”: {“read”}, “dmz”: {“read”}},
“employee”: {“public”: {“read”}, “dmz”: {“read”}, “app”: {“read”, “write”}},
“analyst”: {“public”: {“read”}, “dmz”: {“read”}, “app”: {“read”}, “data”: {“read”}},
“engineer”: {“public”: {“read”}, “dmz”: {“read”}, “app”: {“read”, “write”, “deploy”}, “data”: {“read”}},
“admin”: {“public”: {“read”}, “dmz”: {“read”, “write”}, “app”: {“read”, “write”, “deploy”, “admin”}, “data”: {“read”, “write”, “admin”}, “admin”: {“read”, “write”, “admin”}},
“secops”: {“public”: {“read”}, “dmz”: {“read”, “write”}, “app”: {“read”, “admin”}, “data”: {“read”, “admin”}, “admin”: {“read”, “admin”}},
}

self.w = {
“role_fit”: 1.4,
“device_posture”: 1.8,
“mfa”: 1.0,
“network_context”: 1.2,
“time”: 0.6,
“geo_risk”: 1.2,
“behavior_anomaly”: 2.2,
“data_volume”: 1.4,
“principal_base_risk”: 1.3,
“principal_compromise”: 2.0,
“asset_sensitivity”: 1.6,
“path_validity”: 1.5,
“quarantine”: 4.0,
}

self.thresholds = {
“allow”: 0.72,
“step_up”: 0.62,
“rate_limit”: 0.55,
“deny”: 0.0
}

def register_principal(self, user: str, role: str, base_risk: float) -> None:
self.principals[user] = PrincipalState(
user=user,
role=role,
base_risk=_clamp(base_risk),
last_seen_ts=_now_ts()
)

def register_device(self, device_id: str, device_type: str, owner: str, posture: float, attested: bool) -> None:
self.devices[device_id] = DeviceState(
device_id=device_id,
device_type=device_type,
owner=owner,
posture=_clamp(posture),
attested=bool(attested)
)

def _asset_zone_and_sensitivity(self, node: str) -> Tuple[str, float]:
if node.startswith(“zone:”):
z = node.split(“:”, 1)[1]
return z, SENSITIVITY.get(z, 0.5)
z = self.G.nodes[node].get(“zone”, “public”)
sens = float(self.G.nodes[node].get(“sensitivity”, SENSITIVITY.get(z, 0.5)))
return z, _clamp(sens)

def _base_abac_check(self, role: str, dst_zone: str, action: str) -> bool:
return action in self.role_perms.get(role, {}).get(dst_zone, set())

def _path_is_valid(self, src: str, dst: str) -> bool:
if (src, dst) in self.blocked_edges:
return False
try:
return nx.has_path(self.G, src, dst)
except nx.NetworkXError:
return False

def _network_context_risk(self, source: str) -> float:
table = {“corp_lan”: 0.1, “corp_vpn”: 0.25, “public_wifi”: 0.65, “tor_exit”: 0.9}
return table.get(source, 0.6)

def _time_risk(self, time_bucket: str) -> float:
return 0.15 if time_bucket == “business_hours” else 0.55

def _compute_trust_score(self, ctx: RequestContext) -> Tuple[float, List[str], Dict[str, Any]]:
rule_hits = []
controls: Dict[str, Any] = {}

principal = self.principals.get(ctx.user)
device = self.devices.get(ctx.device_id)

if principal is None:
rule_hits.append(“unknown_principal”)
principal = PrincipalState(ctx.user, ctx.role, base_risk=0.85, last_seen_ts=_now_ts())

if device is None:
rule_hits.append(“unknown_device”)
device = DeviceState(ctx.device_id, ctx.device_type, owner=ctx.user, posture=0.25, attested=False)

src_zone, src_sens = self._asset_zone_and_sensitivity(ctx.src_node)
dst_zone, dst_sens = self._asset_zone_and_sensitivity(ctx.dst_node)

abac_ok = self._base_abac_check(ctx.role, dst_zone, ctx.action)
if not abac_ok:
rule_hits.append(“abac_denied”)

path_ok = self._path_is_valid(ctx.src_node, ctx.dst_node)
if not path_ok:
rule_hits.append(“invalid_path_or_blocked”)

if principal.quarantined or device.quarantined:
rule_hits.append(“quarantined”)
controls[“auto_response”] = “deny_quarantine”

if ctx.action == “exfiltrate”:
rule_hits.append(“exfil_attempt”)

if dst_zone in [“admin”, “data”] and not ctx.mfa:
rule_hits.append(“mfa_required_for_sensitive_zone”)
controls[“step_up_mfa”] = True

if device.owner != ctx.user:
rule_hits.append(“device_owner_mismatch”)

net_r = self._network_context_risk(ctx.source)
t_r = self._time_risk(ctx.time_bucket)

role_fit = 1.0 if abac_ok else 0.0
posture = _clamp(device.posture if device.attested else device.posture * 0.75)
mfa = 1.0 if ctx.mfa else 0.0
path_valid = 1.0 if path_ok else 0.0
sens = _clamp(dst_sens)

principal_risk = _clamp(principal.base_risk)
compromise = _clamp(principal.compromise_score)
anomaly = _clamp(ctx.behavior_anomaly)
geo = _clamp(ctx.geo_risk)
data_vol = _clamp(ctx.data_volume)

quarantine_penalty = 1.0 if (principal.quarantined or device.quarantined) else 0.0
owner_mismatch_penalty = 1.0 if (device.owner != ctx.user) else 0.0
exfil_penalty = 1.0 if (ctx.action == “exfiltrate”) else 0.0

z = 0.0
z += self.w[“role_fit”] * (role_fit – 0.5)
z += self.w[“device_posture”] * (posture – 0.5)
z += self.w[“mfa”] * (mfa – 0.5)
z += self.w[“path_validity”] * (path_valid – 0.5)

z -= self.w[“asset_sensitivity”] * (sens – 0.35)

z -= self.w[“network_context”] * (net_r – 0.25)
z -= self.w[“time”] * (t_r – 0.15)
z -= self.w[“geo_risk”] * (geo – 0.2)

z -= self.w[“behavior_anomaly”] * (anomaly – 0.1)
z -= self.w[“data_volume”] * (data_vol – 0.15)

z -= self.w[“principal_base_risk”] * (principal_risk – 0.2)
z -= self.w[“principal_compromise”] * (compromise – 0.0)

z -= 2.0 * owner_mismatch_penalty
z -= 2.5 * exfil_penalty
z -= self.w[“quarantine”] * quarantine_penalty

trust = _sigmoid(z)

if trust < self.thresholds[“rate_limit”]:
controls[“rate_limit”] = True
if trust < self.thresholds[“step_up”]:
controls[“step_up”] = bool(controls.get(“step_up_mfa”, False) or dst_zone in [“admin”, “data”])
if trust < self.thresholds[“allow”]:
controls[“continuous_auth”] = True

if “abac_denied” in rule_hits or “invalid_path_or_blocked” in rule_hits or “exfil_attempt” in rule_hits:
controls[“risk_signal”] = “policy_violation”

if anomaly > 0.75 and sens > 0.75:
controls[“auto_response”] = “quarantine_candidate”

return _clamp(trust), rule_hits, controls

def evaluate(self, ctx: RequestContext) -> Decision:
trust, rule_hits, controls = self._compute_trust_score(ctx)
allowed = trust >= self.thresholds[“allow”]

if controls.get(“step_up”):
if not ctx.mfa:
allowed = False
rule_hits.append(“step_up_failed_no_mfa”)
else:
allowed = allowed or (trust >= self.thresholds[“step_up”])

if controls.get(“rate_limit”) and trust < 0.5:
allowed = False
rule_hits.append(“rate_limited_denied”)

explanation = self._explain(ctx, trust, allowed, rule_hits, controls)
dec = Decision(allowed=allowed, trust_score=trust, rule_hits=rule_hits, controls=controls, explanation=explanation)

self._post_decision_updates(ctx, dec)

self.flow_log.append(
FlowRecord(
ts=dec.ts,
ctx=ctx.__dict__.copy(),
decision={
“allowed”: dec.allowed,
“trust_score”: dec.trust_score,
“rule_hits”: dec.rule_hits,
“controls”: dec.controls,
“explanation”: dec.explanation
}
)
)
return dec

def _explain(self, ctx: RequestContext, trust: float, allowed: bool, hits: List[str], controls: Dict[str, Any]) -> str:
src_z, _ = self._asset_zone_and_sensitivity(ctx.src_node)
dst_z, dst_s = self._asset_zone_and_sensitivity(ctx.dst_node)
bits = []
bits.append(f”Decision={‘ALLOW’ if allowed else ‘DENY’} | trust={trust:.3f} | {ctx.user}({ctx.role}) {ctx.action} {ctx.src_node}->{ctx.dst_node}”)
bits.append(f”Context: source={ctx.source}, time={ctx.time_bucket}, geo_risk={ctx.geo_risk:.2f}, anomaly={ctx.behavior_anomaly:.2f}, data_vol={ctx.data_volume:.2f}”)
bits.append(f”Zones: {src_z} -> {dst_z} (dst_sensitivity={dst_s:.2f}) | MFA={‘yes’ if ctx.mfa else ‘no’} | posture={ctx.device_posture:.2f}”)
if hits:
bits.append(f”Rule hits: {‘, ‘.join(hits)}”)
if controls:
bits.append(f”Controls: {controls}”)
return ” | “.join(bits)

def _post_decision_updates(self, ctx: RequestContext, dec: Decision) -> None:
p = self.principals.get(ctx.user)
d = self.devices.get(ctx.device_id)

if p is None:
self.register_principal(ctx.user, ctx.role, base_risk=0.65)
p = self.principals[ctx.user]
if d is None:
self.register_device(ctx.device_id, ctx.device_type, ctx.user, ctx.device_posture, attested=(ctx.device_type.startswith(“managed”)))
d = self.devices[ctx.device_id]

p.last_seen_ts = dec.ts

if dec.allowed:
p.rolling_allows += 1
p.rolling_denies = max(0, p.rolling_denies – 1)
p.compromise_score = _clamp(p.compromise_score – 0.02)
else:
p.rolling_denies += 1
p.compromise_score = _clamp(p.compromise_score + 0.06 + 0.10 * (1.0 if “exfil_attempt” in dec.rule_hits else 0.0))

if dec.controls.get(“auto_response”) == “quarantine_candidate” or p.rolling_denies >= 4 or p.compromise_score > 0.78:
p.quarantined = True
if d:
d.quarantined = True

if (“invalid_path_or_blocked” in dec.rule_hits) or (“exfil_attempt” in dec.rule_hits) or (“abac_denied” in dec.rule_hits):
self.blocked_edges.add((ctx.src_node, ctx.dst_node))

def stats(self) -> Dict[str, Any]:
total = len(self.flow_log)
allows = sum(1 for r in self.flow_log if r.decision[“allowed”])
denies = total – allows
top_denies = {}
for r in self.flow_log:
if not r.decision[“allowed”]:
for h in r.decision[“rule_hits”]:
top_denies[h] = top_denies.get(h, 0) + 1
principals = {
u: {
“role”: p.role,
“base_risk”: round(p.base_risk, 3),
“compromise_score”: round(p.compromise_score, 3),
“rolling_denies”: p.rolling_denies,
“rolling_allows”: p.rolling_allows,
“quarantined”: p.quarantined
}
for u, p in self.principals.items()
}
devices = {
did: {
“owner”: d.owner,
“type”: d.device_type,
“posture”: round(d.posture, 3),
“attested”: d.attested,
“quarantined”: d.quarantined
}
for did, d in self.devices.items()
}
return {
“policy_version”: self.policy_version,
“flows_total”: total,
“flows_allow”: allows,
“flows_deny”: denies,
“deny_reasons_top”: dict(sorted(top_denies.items(), key=lambda kv: kv[1], reverse=True)[:10]),
“blocked_edges_count”: len(self.blocked_edges),
“principals”: principals,
“devices”: devices
}

def make_world(engine: ZeroTrustPolicyEngine, seed: int = 13) -> Dict[str, Any]:
random.seed(seed)

users = [
(“alice”, “employee”, 0.18),
(“bob”, “engineer”, 0.22),
(“cathy”, “analyst”, 0.25),
(“dan”, “admin”, 0.15),
(“eve”, “secops”, 0.10),
(“mallory”, “employee”, 0.55)
]
for u, r, br in users:
engine.register_principal(u, r, br)

devices = [
(“dev-alice-lt”, “managed_laptop”, “alice”, 0.82, True),
(“dev-bob-lt”, “managed_laptop”, “bob”, 0.77, True),
(“dev-cathy-lt”, “managed_laptop”, “cathy”, 0.74, True),
(“dev-dan-lt”, “managed_laptop”, “dan”, 0.88, True),
(“dev-eve-lt”, “managed_laptop”, “eve”, 0.90, True),
(“dev-mallory-byod”, “byod_phone”, “mallory”, 0.42, False),
(“unknown-iot-7”, “unknown_iot”, “unknown”, 0.20, False),
]
for did, dt, owner, posture, attested in devices:
engine.register_device(did, dt, owner, posture, attested)

all_assets = [n for n in engine.G.nodes() if engine.G.nodes[n].get(“kind”) == “asset”]
by_zone = {z: [a for a in all_assets if engine.G.nodes[a].get(“zone”) == z] for z in ZONES}

return {“users”: users, “devices”: devices, “assets”: all_assets, “by_zone”: by_zone}

def gen_request(engine: ZeroTrustPolicyEngine, world: Dict[str, Any], kind: str = “normal”, seed_salt: str = “”) -> RequestContext:
rnd = random.Random(_stable_hash(kind + seed_salt + str(_now_ts())[:6]))

users = world[“users”]
by_zone = world[“by_zone”]

def pick_user(role_bias: Optional[str] = None) -> Tuple[str, str]:
if role_bias:
filtered = [u for u in users if u[1] == role_bias]
if filtered:
u, r, _ = rnd.choice(filtered)
return u, r
u, r, _ = rnd.choice(users)
return u, r

def user_device(u: str) -> Tuple[str, str, float]:
candidates = [d for d in engine.devices.values() if d.owner == u]
if candidates:
d = rnd.choice(candidates)
else:
d = rnd.choice(list(engine.devices.values()))
return d.device_id, d.device_type, d.posture

def time_bucket():
return “business_hours” if rnd.random() < 0.75 else “after_hours”

source = _rand_choice_weighted(NETWORK_CONTEXT, [0.45, 0.25, 0.22, 0.08])
geo_risk = _clamp(rnd.uniform(0.05, 0.35) + (0.25 if source in [“public_wifi”, “tor_exit”] else 0.0))
behavior_anomaly = _clamp(rnd.uniform(0.02, 0.25))
data_volume = _clamp(rnd.uniform(0.02, 0.25))

if kind == “normal”:
u, r = pick_user()
did, dt, posture = user_device(u)

src_zone = _rand_choice_weighted([“public”, “dmz”, “app”], [0.15, 0.55, 0.30])
dst_zone = _rand_choice_weighted([“dmz”, “app”, “data”], [0.35, 0.45, 0.20])
action = _rand_choice_weighted(ACTIONS, [0.55, 0.28, 0.07, 0.08, 0.02])

src = rnd.choice(by_zone[src_zone])
dst = rnd.choice(by_zone[dst_zone])

mfa = True if dst_zone in [“data”, “admin”] else (rnd.random() < 0.55)

return RequestContext(
user=u, role=r,
device_id=did, device_type=dt, device_posture=posture,
mfa=mfa, source=source,
src_node=src, dst_node=dst,
action=action,
time_bucket=time_bucket(),
geo_risk=geo_risk,
behavior_anomaly=behavior_anomaly,
data_volume=data_volume,
reason=”routine_access”
)

if kind == “malicious_flow”:
u, r = (“unknown_actor”, “customer”)
did, dt, posture = (“unknown-dev”, “unknown_iot”, 0.18)

source = _rand_choice_weighted([“tor_exit”, “public_wifi”], [0.65, 0.35])
geo_risk = _clamp(rnd.uniform(0.6, 0.95))
behavior_anomaly = _clamp(rnd.uniform(0.75, 0.98))
data_volume = _clamp(rnd.uniform(0.75, 0.98))

src = rnd.choice(by_zone[“public”] + by_zone[“dmz”])
dst = rnd.choice(by_zone[“data”] + by_zone[“admin”])
action = _rand_choice_weighted([“write”, “admin”, “exfiltrate”], [0.25, 0.25, 0.50])
mfa = False

return RequestContext(
user=u, role=r,
device_id=did, device_type=dt, device_posture=posture,
mfa=mfa, source=source,
src_node=src, dst_node=dst,
action=action,
time_bucket=”after_hours”,
geo_risk=geo_risk,
behavior_anomaly=behavior_anomaly,
data_volume=data_volume,
reason=”external_malicious_attempt”
)

if kind == “insider_threat”:
u, r = (“mallory”, “employee”)
did, dt, posture = user_device(u)

source = _rand_choice_weighted([“corp_vpn”, “public_wifi”], [0.55, 0.45])
geo_risk = _clamp(rnd.uniform(0.25, 0.65))
behavior_anomaly = _clamp(rnd.uniform(0.55, 0.95))
data_volume = _clamp(rnd.uniform(0.55, 0.95))

src = rnd.choice(by_zone[“app”] + by_zone[“dmz”])
dst = rnd.choice(by_zone[“data”] + by_zone[“admin”])
action = _rand_choice_weighted([“read”, “write”, “exfiltrate”, “admin”], [0.18, 0.22, 0.45, 0.15])

mfa = rnd.random() < 0.25

return RequestContext(
user=u, role=r,
device_id=did, device_type=dt, device_posture=posture,
mfa=mfa, source=source,
src_node=src, dst_node=dst,
action=action,
time_bucket=”after_hours”,
geo_risk=geo_risk,
behavior_anomaly=behavior_anomaly,
data_volume=data_volume,
reason=”insider_lateral_and_exfil”
)

raise ValueError(f”Unknown kind={kind}”)

def run_simulation(engine: ZeroTrustPolicyEngine, world: Dict[str, Any], steps: int = 60, seed: int = 99) -> Dict[str, Any]:
random.seed(seed)
results = {“allowed”: 0, “denied”: 0, “samples”: []}

for i in range(steps):
if i in [12, 13, 14, 28, 29]:
ctx = gen_request(engine, world, kind=”malicious_flow”, seed_salt=str(i))
elif i in [18, 19, 20, 34, 35, 36, 50, 51]:
ctx = gen_request(engine, world, kind=”insider_threat”, seed_salt=str(i))
else:
ctx = gen_request(engine, world, kind=”normal”, seed_salt=str(i))

dec = engine.evaluate(ctx)
if dec.allowed:
results[“allowed”] += 1
else:
results[“denied”] += 1

if i < 10 or (not dec.allowed and len(results[“samples”]) < 18):
results[“samples”].append({“ctx”: ctx.__dict__, “decision”: dec.__dict__})

return results

def make_app(engine: ZeroTrustPolicyEngine, world: Dict[str, Any]) -> Flask:
app = Flask(__name__)

@app.get(“/health”)
def health():
return jsonify({“ok”: True, “policy_version”: engine.policy_version})

@app.get(“/graph”)
def graph():
nodes = [{“id”: n, **engine.G.nodes[n]} for n in engine.G.nodes()]
edges = [{“src”: u, “dst”: v, **engine.G.edges[u, v]} for u, v in engine.G.edges()]
return jsonify({“nodes”: nodes, “edges”: edges, “blocked_edges”: list(map(list, engine.blocked_edges))})

@app.post(“/request”)
def evaluate_request():
payload = request.get_json(force=True)
ctx = RequestContext(**payload)
dec = engine.evaluate(ctx)
return jsonify({“allowed”: dec.allowed, “trust_score”: dec.trust_score, “rule_hits”: dec.rule_hits, “controls”: dec.controls, “explanation”: dec.explanation})

@app.post(“/simulate”)
def simulate():
payload = request.get_json(force=True) if request.data else {}
steps = int(payload.get(“steps”, 50))
res = run_simulation(engine, world, steps=steps, seed=int(payload.get(“seed”, 123)))
return jsonify({“steps”: steps, “allowed”: res[“allowed”], “denied”: res[“denied”], “stats”: engine.stats()})

@app.get(“/stats”)
def stats():
return jsonify(engine.stats())

return app

G = build_microsegmented_graph(seed=7)
engine = ZeroTrustPolicyEngine(G)
world = make_world(engine, seed=13)

draw_graph(G, title=”Zero-Trust Microsegmented Network (Zones + Assets + Directed Flows)”)

app = make_app(engine, world)
client = app.test_client()

print(“== Health ==”)
print(client.get(“/health”).json)

print(“n== Run simulation (mixture: normal + malicious flows + insider threat) ==”)
sim_out = client.post(“/simulate”, json={“steps”: 70, “seed”: 2026}).json
print(_pretty({“allowed”: sim_out[“allowed”], “denied”: sim_out[“denied”], “blocked_edges_count”: sim_out[“stats”][“blocked_edges_count”]}))

print(“n== Top deny reasons ==”)
print(_pretty(sim_out[“stats”][“deny_reasons_top”]))

print(“n== Principal risk snapshot (watch mallory) ==”)
principals = sim_out[“stats”][“principals”]
focus = {k: principals[k] for k in sorted(principals.keys()) if k in [“alice”,”bob”,”cathy”,”dan”,”eve”,”mallory”,”unknown_actor”]}
print(_pretty(focus))

print(“n== Example: send a direct insider exfil request via the policy API ==”)
insider_ctx = gen_request(engine, world, kind=”insider_threat”, seed_salt=”manual-1″)
insider_ctx.action = “exfiltrate”
insider_ctx.mfa = False
insider_ctx.behavior_anomaly = 0.92
insider_ctx.data_volume = 0.88
insider_ctx.geo_risk = 0.62

resp = client.post(“/request”, json=insider_ctx.__dict__).json
print(_pretty(resp))

print(“n== Example: a legitimate admin read with MFA from corp_lan ==”)
admin_ctx = RequestContext(
user=”dan”, role=”admin”,
device_id=”dev-dan-lt”, device_type=”managed_laptop”, device_posture=engine.devices[“dev-dan-lt”].posture,
mfa=True, source=”corp_lan”,
src_node=random.choice(world[“by_zone”][“admin”]),
dst_node=random.choice(world[“by_zone”][“data”]),
action=”read”,
time_bucket=”business_hours”,
geo_risk=0.08,
behavior_anomaly=0.06,
data_volume=0.10,
reason=”admin_operational_access”
)
resp2 = client.post(“/request”, json=admin_ctx.__dict__).json
print(_pretty(resp2))

print(“n== Final stats ==”)
final_stats = client.get(“/stats”).json
print(_pretty({
“flows_total”: final_stats[“flows_total”],
“flows_allow”: final_stats[“flows_allow”],
“flows_deny”: final_stats[“flows_deny”],
“blocked_edges_count”: final_stats[“blocked_edges_count”],
“deny_reasons_top”: final_stats[“deny_reasons_top”]
}))

scores = [r.decision[“trust_score”] for r in engine.flow_log]
plt.figure(figsize=(9, 4))
plt.hist(scores, bins=18)
plt.title(“Trust Score Distribution Across Simulated Flows”)
plt.xlabel(“trust_score”)
plt.ylabel(“count”)
plt.show()

denied = [r for r in engine.flow_log if not r.decision[“allowed”]]
print(“n== Recent denied explanations (last 6) ==”)
for r in denied[-6:]:
print(“-“, r.decision[“explanation”])