Zero Trust Architecture for Financial Trading Systems

1                 Firewall
2                    |
3         ┌──────────┴──────────┐
4         |                     |
5    VPN Gateway          DMZ Services
6         |                     |
7    ┌────┴────┐            ┌───┴────┐
8    |         |            |        |
9  Trading   Risk         Market   Pricing
10  Systems   Engine       Data     Engine
11
12Problem: Once inside, full trust = lateral movement
13

1Day 0:  VPN credential compromised (phishing)
2Day 1:  Attacker accesses internal network
3Day 2:  Lateral movement to trading systems
4Day 5:  Exfiltration of trading strategies
5Day 12: Detected by anomaly in data transfer
6Cost:   $4.7M in leaked IP + remediation
7

1                Policy Decision Point (PDP)
2                          |
3           ┌──────────────┼──────────────┐
4           |              |              |
5      Identity         Device        Context
6     Verification    Posture      (Location, Time)
7           |              |              |
8           └──────────────┴──────────────┘
9                          |
10                  Policy Enforcement
11                          |
12         ┌────────────────┼────────────────┐
13         |                |                |
14    Trading API      Risk Engine     Market Data
15    (Segment 1)      (Segment 2)     (Segment 3)
16
17Each access verified independently, no transitive trust
18

1from dataclasses import dataclass
2from typing import List, Dict, Optional
3from datetime import datetime, timedelta
4import jwt
5import hashlib
6import secrets
7
8@dataclass
9class Principal:
10    """
11    Identity with attributes for policy decisions.
12    
13    Zero Trust evaluates EVERY request against:
14    - Who (user/service identity)
15    - What (resource being accessed)
16    - Where (network location, device)
17    - When (time of day, session duration)
18    - How (authentication strength, device posture)
19    """
20    user_id: str
21    email: str
22    groups: List[str]
23    mfa_verified: bool
24    device_id: str
25    device_trusted: bool
26    ip_address: str
27    location: str
28    authentication_time: datetime
29    risk_score: float  # 0.0-1.0
30
31@dataclass
32class Resource:
33    """Protected resource with access requirements"""
34    resource_id: str
35    resource_type: str  # 'trading-api', 'market-data', 'risk-engine'
36    classification: str  # 'public', 'internal', 'confidential', 'secret'
37    required_groups: List[str]
38    required_mfa: bool
39    allowed_locations: List[str]
40    max_risk_score: float
41
42class ZeroTrustPolicyEngine:
43    """
44    Policy Decision Point (PDP) for Zero Trust.
45    
46    Makes access decisions based on:
47    - Identity attributes
48    - Resource requirements
49    - Contextual factors
50    - Risk signals
51    """
52    
53    def __init__(self, secret_key: str):
54        self.secret_key = secret_key
55        self.session_duration = timedelta(hours=8)
56        
57    def authenticate(
58        self,
59        username: str,
60        password: str,
61        mfa_token: Optional[str],
62        device_id: str,
63        ip_address: str
64    ) -> Optional[Principal]:
65        """
66        Authenticate user and create principal.
67        
68        Zero Trust: Authentication != Authorization
69        This only verifies identity, not permissions.
70        """
71        # Verify credentials (simplified)
72        user = self._verify_credentials(username, password)
73        if not user:
74            return None
75        
76        # Verify MFA if provided
77        mfa_verified = False
78        if mfa_token:
79            mfa_verified = self._verify_mfa(user['user_id'], mfa_token)
80        
81        # Check device trust
82        device_trusted = self._check_device_posture(device_id)
83        
84        # Calculate risk score
85        risk_score = self._calculate_risk_score(
86            user=user,
87            ip_address=ip_address,
88            device_trusted=device_trusted,
89            mfa_verified=mfa_verified
90        )
91        
92        # Create principal
93        principal = Principal(
94            user_id=user['user_id'],
95            email=user['email'],
96            groups=user['groups'],
97            mfa_verified=mfa_verified,
98            device_id=device_id,
99            device_trusted=device_trusted,
100            ip_address=ip_address,
101            location=self._get_location(ip_address),
102            authentication_time=datetime.utcnow(),
103            risk_score=risk_score
104        )
105        
106        return principal
107    
108    def authorize(
109        self,
110        principal: Principal,
111        resource: Resource,
112        action: str
113    ) -> tuple[bool, str]:
114        """
115        Authorize access to resource.
116        
117        Zero Trust: Every request is evaluated independently.
118        No cached decisions, no implicit trust.
119        """
120        # Check session freshness
121        session_age = datetime.utcnow() - principal.authentication_time
122        if session_age > self.session_duration:
123            return False, "Session expired, re-authenticate"
124        
125        # Check group membership
126        if not any(group in principal.groups for group in resource.required_groups):
127            return False, f"User not in required groups: {resource.required_groups}"
128        
129        # Check MFA requirement
130        if resource.required_mfa and not principal.mfa_verified:
131            return False, "MFA required for this resource"
132        
133        # Check device trust
134        if resource.classification in ['confidential', 'secret'] and not principal.device_trusted:
135            return False, "Untrusted device, cannot access confidential data"
136        
137        # Check location
138        if resource.allowed_locations and principal.location not in resource.allowed_locations:
139            return False, f"Access from {principal.location} not allowed"
140        
141        # Check risk score
142        if principal.risk_score > resource.max_risk_score:
143            return False, f"Risk score {principal.risk_score:.2f} exceeds threshold {resource.max_risk_score:.2f}"
144        
145        # All checks passed
146        return True, "Access granted"
147    
148    def _verify_credentials(self, username: str, password: str) -> Optional[Dict]:
149        """Verify username/password (simplified)"""
150        # In production: bcrypt, LDAP, OAuth, etc.
151        users = {
152            'trader@example.com': {
153                'user_id': 'trader-001',
154                'email': 'trader@example.com',
155                'password_hash': hashlib.sha256(b'password123').hexdigest(),
156                'groups': ['traders', 'market-access']
157            },
158            'quant@example.com': {
159                'user_id': 'quant-002',
160                'email': 'quant@example.com',
161                'password_hash': hashlib.sha256(b'quant-pass').hexdigest(),
162                'groups': ['quants', 'risk-viewers', 'data-scientists']
163            }
164        }
165        
166        user = users.get(username)
167        if not user:
168            return None
169        
170        password_hash = hashlib.sha256(password.encode()).hexdigest()
171        if password_hash != user['password_hash']:
172            return None
173        
174        return user
175    
176    def _verify_mfa(self, user_id: str, token: str) -> bool:
177        """Verify MFA token (TOTP)"""
178        # In production: Use pyotp or similar
179        # For demo, accept any 6-digit token
180        return len(token) == 6 and token.isdigit()
181    
182    def _check_device_posture(self, device_id: str) -> bool:
183        """
184        Check device compliance.
185        
186        Device posture includes:
187        - OS version up to date
188        - Antivirus running
189        - Disk encryption enabled
190        - No jailbreak/root
191        """
192        # In production: Integrate with MDM/EDR
193        # For demo, trust devices starting with 'trusted-'
194        return device_id.startswith('trusted-')
195    
196    def _calculate_risk_score(
197        self,
198        user: Dict,
199        ip_address: str,
200        device_trusted: bool,
201        mfa_verified: bool
202    ) -> float:
203        """
204        Calculate risk score (0.0 = low risk, 1.0 = high risk).
205        
206        Factors:
207        - Authentication strength
208        - Device trust
209        - Location anomaly
210        - Time of access
211        - Historical behavior
212        """
213        risk = 0.0
214        
215        # MFA reduces risk
216        if not mfa_verified:
217            risk += 0.3
218        
219        # Untrusted device increases risk
220        if not device_trusted:
221            risk += 0.4
222        
223        # Check for anomalous location
224        if self._is_anomalous_location(user['user_id'], ip_address):
225            risk += 0.2
226        
227        # Check for anomalous time
228        if self._is_anomalous_time():
229            risk += 0.1
230        
231        return min(risk, 1.0)
232    
233    def _get_location(self, ip_address: str) -> str:
234        """Get geographic location from IP"""
235        # In production: Use MaxMind GeoIP or similar
236        # For demo, hardcode some IPs
237        locations = {
238            '192.168.1.': 'Office-NYC',
239            '10.0.0.': 'Office-London',
240            '172.16.': 'AWS-US-East'
241        }
242        
243        for prefix, location in locations.items():
244            if ip_address.startswith(prefix):
245                return location
246        
247        return 'Unknown'
248    
249    def _is_anomalous_location(self, user_id: str, ip_address: str) -> bool:
250        """Check if location is unusual for user"""
251        # In production: ML-based anomaly detection
252        # For demo, flag non-office IPs
253        location = self._get_location(ip_address)
254        return location == 'Unknown'
255    
256    def _is_anomalous_time(self) -> bool:
257        """Check if access time is unusual"""
258        # Flag access outside business hours (9 AM - 6 PM EST)
259        hour = datetime.utcnow().hour - 5  # EST offset
260        return hour < 9 or hour > 18
261    
262    def issue_token(self, principal: Principal, expiry_minutes: int = 60) -> str:
263        """
264        Issue JWT for authenticated requests.
265        
266        Token contains:
267        - User identity
268        - Verified attributes
269        - Expiry time
270        - Signature for integrity
271        """
272        payload = {
273            'user_id': principal.user_id,
274            'email': principal.email,
275            'groups': principal.groups,
276            'mfa_verified': principal.mfa_verified,
277            'device_id': principal.device_id,
278            'device_trusted': principal.device_trusted,
279            'location': principal.location,
280            'risk_score': principal.risk_score,
281            'iat': datetime.utcnow(),
282            'exp': datetime.utcnow() + timedelta(minutes=expiry_minutes)
283        }
284        
285        token = jwt.encode(payload, self.secret_key, algorithm='HS256')
286        return token
287    
288    def verify_token(self, token: str) -> Optional[Principal]:
289        """
290        Verify JWT and reconstruct principal.
291        
292        Zero Trust: Token is verified on EVERY request.
293        No session state, no trust after initial auth.
294        """
295        try:
296            payload = jwt.decode(token, self.secret_key, algorithms=['HS256'])
297            
298            principal = Principal(
299                user_id=payload['user_id'],
300                email=payload['email'],
301                groups=payload['groups'],
302                mfa_verified=payload['mfa_verified'],
303                device_id=payload['device_id'],
304                device_trusted=payload['device_trusted'],
305                ip_address='',  # Would come from request
306                location=payload['location'],
307                authentication_time=payload['iat'],
308                risk_score=payload['risk_score']
309            )
310            
311            return principal
312        except jwt.ExpiredSignatureError:
313            return None
314        except jwt.InvalidTokenError:
315            return None
316
317# Example usage
318policy_engine = ZeroTrustPolicyEngine(secret_key='your-secret-key')
319
320# Authenticate user
321principal = policy_engine.authenticate(
322    username='trader@example.com',
323    password='password123',
324    mfa_token='123456',
325    device_id='trusted-device-001',
326    ip_address='192.168.1.100'
327)
328
329if principal:
330    print(f"✅ Authenticated: {principal.email}")
331    print(f"   Groups: {principal.groups}")
332    print(f"   MFA: {'✓' if principal.mfa_verified else '✗'}")
333    print(f"   Risk score: {principal.risk_score:.2f}")
334    
335    # Issue token
336    token = policy_engine.issue_token(principal)
337    print(f"   Token: {token[:50]}...")
338    
339    # Authorize access to trading API
340    trading_api = Resource(
341        resource_id='trading-api-v1',
342        resource_type='trading-api',
343        classification='confidential',
344        required_groups=['traders', 'market-access'],
345        required_mfa=True,
346        allowed_locations=['Office-NYC', 'Office-London'],
347        max_risk_score=0.5
348    )
349    
350    allowed, reason = policy_engine.authorize(principal, trading_api, 'execute-trade')
351    
352    if allowed:
353        print(f"\n✅ Access granted to trading API")
354    else:
355        print(f"\n❌ Access denied: {reason}")
356else:
357    print("❌ Authentication failed")
358

1from enum import Enum
2from typing import Set, Dict
3
4class Segment(Enum):
5    """Network segments with different security levels"""
6    DMZ = "dmz"
7    MARKET_DATA = "market-data"
8    TRADING_CORE = "trading-core"
9    RISK_ENGINE = "risk-engine"
10    BACK_OFFICE = "back-office"
11    ADMIN = "admin"
12
13class MicrosegmentationPolicy:
14    """
15    Define allowed traffic between segments.
16    
17    Zero Trust: Default deny, explicitly allow only necessary flows.
18    """
19    
20    def __init__(self):
21        # Define allowed flows (source_segment -> destination_segment)
22        self.allowed_flows: Dict[Segment, Set[Segment]] = {
23            Segment.DMZ: {
24                Segment.MARKET_DATA,  # DMZ can access market data
25            },
26            Segment.MARKET_DATA: {
27                Segment.TRADING_CORE,  # Market data feeds to trading
28            },
29            Segment.TRADING_CORE: {
30                Segment.RISK_ENGINE,  # Trading sends to risk
31                Segment.MARKET_DATA,  # Trading queries market data
32            },
33            Segment.RISK_ENGINE: {
34                Segment.TRADING_CORE,  # Risk sends decisions back
35                Segment.BACK_OFFICE,  # Risk reports to back office
36            },
37            Segment.BACK_OFFICE: set(),  # No outbound from back office
38            Segment.ADMIN: {  # Admin can access all segments
39                Segment.DMZ,
40                Segment.MARKET_DATA,
41                Segment.TRADING_CORE,
42                Segment.RISK_ENGINE,
43                Segment.BACK_OFFICE,
44            }
45        }
46    
47    def is_flow_allowed(
48        self,
49        source: Segment,
50        destination: Segment,
51        port: int,
52        protocol: str
53    ) -> tuple[bool, str]:
54        """
55        Check if network flow is allowed.
56        
57        Zero Trust: Deny by default, allow explicitly.
58        """
59        # Check segment-level policy
60        allowed_destinations = self.allowed_flows.get(source, set())
61        
62        if destination not in allowed_destinations:
63            return False, f"Flow from {source.value} to {destination.value} not allowed"
64        
65        # Check protocol and port (simplified)
66        if protocol not in ['TCP', 'UDP']:
67            return False, f"Protocol {protocol} not allowed"
68        
69        # Define allowed ports per destination
70        allowed_ports = {
71            Segment.MARKET_DATA: [8080, 8443],  # Market data APIs
72            Segment.TRADING_CORE: [9000, 9001],  # Trading APIs
73            Segment.RISK_ENGINE: [7000],  # Risk API
74            Segment.BACK_OFFICE: [5432],  # PostgreSQL
75        }
76        
77        if destination in allowed_ports:
78            if port not in allowed_ports[destination]:
79                return False, f"Port {port} not allowed for {destination.value}"
80        
81        return True, "Flow allowed"
82
83# Example: Enforce microsegmentation with iptables
84def generate_iptables_rules(policy: MicrosegmentationPolicy) -> List[str]:
85    """
86    Generate iptables rules for microsegmentation.
87    
88    In production: Use network policy controllers (Cilium, Calico)
89    """
90    rules = [
91        "# Zero Trust Microsegmentation Rules",
92        "",
93        "# Default deny",
94        "iptables -P FORWARD DROP",
95        ""
96    ]
97    
98    # Segment IP ranges (example)
99    segment_ips = {
100        Segment.DMZ: "10.0.1.0/24",
101        Segment.MARKET_DATA: "10.0.2.0/24",
102        Segment.TRADING_CORE: "10.0.3.0/24",
103        Segment.RISK_ENGINE: "10.0.4.0/24",
104        Segment.BACK_OFFICE: "10.0.5.0/24",
105        Segment.ADMIN: "10.0.10.0/24",
106    }
107    
108    # Generate allow rules
109    for source, destinations in policy.allowed_flows.items():
110        source_ip = segment_ips[source]
111        
112        for dest in destinations:
113            dest_ip = segment_ips[dest]
114            
115            rules.append(f"# {source.value} -> {dest.value}")
116            rules.append(
117                f"iptables -A FORWARD -s {source_ip} -d {dest_ip} "
118                f"-m state --state NEW,ESTABLISHED -j ACCEPT"
119            )
120            rules.append("")
121    
122    # Deny all other traffic
123    rules.append("# Deny all other traffic (logged)")
124    rules.append("iptables -A FORWARD -j LOG --log-prefix 'ZT-DENY: '")
125    rules.append("iptables -A FORWARD -j DROP")
126    
127    return rules
128
129# Example usage
130segmentation = MicrosegmentationPolicy()
131
132# Check if flow is allowed
133allowed, reason = segmentation.is_flow_allowed(
134    source=Segment.TRADING_CORE,
135    destination=Segment.RISK_ENGINE,
136    port=7000,
137    protocol='TCP'
138)
139
140print(f"Trading -> Risk Engine (TCP:7000): {allowed} ({reason})")
141
142# Check denied flow
143allowed, reason = segmentation.is_flow_allowed(
144    source=Segment.MARKET_DATA,
145    destination=Segment.BACK_OFFICE,
146    port=5432,
147    protocol='TCP'
148)
149
150print(f"Market Data -> Back Office (TCP:5432): {allowed} ({reason})")
151
152# Generate iptables rules
153rules = generate_iptables_rules(segmentation)
154print("\nGenerated iptables rules:")
155for rule in rules[:10]:  # Show first 10 lines
156    print(rule)
157

1import time
2from dataclasses import dataclass
3from collections import deque
4from typing import Deque
5
6@dataclass
7class SecurityEvent:
8    """Security-relevant event"""
9    timestamp: float
10    user_id: str
11    resource: str
12    action: str
13    result: str  # 'allowed', 'denied'
14    risk_score: float
15
16class ContinuousVerification:
17    """
18    Monitor and re-evaluate access continuously.
19    
20    Zero Trust: Access decisions are not permanent.
21    Continuously monitor for anomalies and revoke if needed.
22    """
23    
24    def __init__(self, policy_engine: ZeroTrustPolicyEngine):
25        self.policy_engine = policy_engine
26        self.events: Deque[SecurityEvent] = deque(maxlen=10000)
27        
28    def monitor_access(
29        self,
30        principal: Principal,
31        resource: Resource,
32        action: str
33    ) -> bool:
34        """
35        Monitor access and potentially revoke.
36        
37        Checks:
38        - Anomalous behavior
39        - Privilege escalation
40        - Excessive access
41        - Time-based revocation
42        """
43        # Record access event
44        event = SecurityEvent(
45            timestamp=time.time(),
46            user_id=principal.user_id,
47            resource=resource.resource_id,
48            action=action,
49            result='allowed',  # Updated after check
50            risk_score=principal.risk_score
51        )
52        
53        # Check for anomalies
54        if self._detect_anomaly(principal):
55            event.result = 'denied'
56            self.events.append(event)
57            return False
58        
59        # Check for excessive access
60        if self._check_access_rate(principal):
61            event.result = 'denied'
62            self.events.append(event)
63            return False
64        
65        # Re-evaluate risk score
66        updated_risk = self._recalculate_risk(principal)
67        if updated_risk > resource.max_risk_score:
68            event.result = 'denied'
69            self.events.append(event)
70            return False
71        
72        # Access allowed
73        event.result = 'allowed'
74        self.events.append(event)
75        return True
76    
77    def _detect_anomaly(self, principal: Principal) -> bool:
78        """
79        Detect anomalous behavior.
80        
81        Anomalies:
82        - Access from new location
83        - Access to unusual resources
84        - Time-based anomalies
85        """
86        # Get user's recent events
87        recent_events = [
88            e for e in self.events
89            if e.user_id == principal.user_id
90            and time.time() - e.timestamp < 3600  # Last hour
91        ]
92        
93        if not recent_events:
94            return False
95        
96        # Check for unusual resource access
97        accessed_resources = {e.resource for e in recent_events}
98        if len(accessed_resources) > 10:
99            # Accessing too many different resources
100            return True
101        
102        return False
103    
104    def _check_access_rate(self, principal: Principal) -> bool:
105        """
106        Check for excessive access rate.
107        
108        Rate limiting per user to prevent abuse.
109        """
110        window = 60  # 1 minute window
111        max_requests = 100
112        
113        recent_count = sum(
114            1 for e in self.events
115            if e.user_id == principal.user_id
116            and time.time() - e.timestamp < window
117        )
118        
119        return recent_count > max_requests
120    
121    def _recalculate_risk(self, principal: Principal) -> float:
122        """
123        Recalculate risk score based on recent behavior.
124        
125        Risk increases with:
126        - Failed access attempts
127        - Access outside normal hours
128        - Multiple locations
129        """
130        base_risk = principal.risk_score
131        
132        # Check for denied events
133        recent_denials = sum(
134            1 for e in self.events
135            if e.user_id == principal.user_id
136            and e.result == 'denied'
137            and time.time() - e.timestamp < 3600
138        )
139        
140        if recent_denials > 0:
141            base_risk += 0.1 * recent_denials
142        
143        return min(base_risk, 1.0)
144    
145    def get_user_activity_summary(self, user_id: str, hours: int = 24) -> Dict:
146        """Get activity summary for user"""
147        cutoff = time.time() - (hours * 3600)
148        
149        user_events = [
150            e for e in self.events
151            if e.user_id == user_id and e.timestamp > cutoff
152        ]
153        
154        if not user_events:
155            return {'events': 0}
156        
157        return {
158            'events': len(user_events),
159            'allowed': sum(1 for e in user_events if e.result == 'allowed'),
160            'denied': sum(1 for e in user_events if e.result == 'denied'),
161            'resources': len({e.resource for e in user_events}),
162            'avg_risk_score': sum(e.risk_score for e in user_events) / len(user_events),
163            'max_risk_score': max(e.risk_score for e in user_events)
164        }
165
166# Example usage
167monitor = ContinuousVerification(policy_engine)
168
169# Simulate access monitoring
170for i in range(5):
171    allowed = monitor.monitor_access(principal, trading_api, 'execute-trade')
172    print(f"Access {i+1}: {'✅ Allowed' if allowed else '❌ Denied'}")
173    time.sleep(0.1)
174
175# Get activity summary
176summary = monitor.get_user_activity_summary('trader-001', hours=1)
177print(f"\nActivity summary:")
178print(f"  Events: {summary['events']}")
179print(f"  Allowed: {summary['allowed']}")
180print(f"  Denied: {summary['denied']}")
181

1# zero-trust-network-policy.yaml
2apiVersion: networking.k8s.io/v1
3kind: NetworkPolicy
4metadata:
5  name: trading-core-policy
6  namespace: trading
7spec:
8  podSelector:
9    matchLabels:
10      app: trading-core
11  policyTypes:
12    - Ingress
13    - Egress
14  
15  ingress:
16    # Allow only from market-data segment
17    - from:
18      - namespaceSelector:
19          matchLabels:
20            name: market-data
21      ports:
22      - protocol: TCP
23        port: 9000
24    
25    # Allow from risk-engine
26    - from:
27      - namespaceSelector:
28          matchLabels:
29            name: risk-engine
30      ports:
31      - protocol: TCP
32        port: 9001
33  
34  egress:
35    # Allow to risk-engine
36    - to:
37      - namespaceSelector:
38          matchLabels:
39            name: risk-engine
40      ports:
41      - protocol: TCP
42        port: 7000
43    
44    # Allow to market-data
45    - to:
46      - namespaceSelector:
47          matchLabels:
48            name: market-data
49      ports:
50      - protocol: TCP
51        port: 8080
52    
53    # Allow DNS
54    - to:
55      - namespaceSelector:
56          matchLabels:
57            name: kube-system
58      ports:
59      - protocol: UDP
60        port: 53
61
62---
63# Service mesh with mutual TLS (Istio)
64apiVersion: security.istio.io/v1beta1
65kind: PeerAuthentication
66metadata:
67  name: default
68  namespace: trading
69spec:
70  mtls:
71    mode: STRICT  # Require mTLS for all traffic
72
73---
74# Authorization policy
75apiVersion: security.istio.io/v1beta1
76kind: AuthorizationPolicy
77metadata:
78  name: trading-authz
79  namespace: trading
80spec:
81  selector:
82    matchLabels:
83      app: trading-core
84  
85  rules:
86    # Allow from market-data with valid JWT
87    - from:
88      - source:
89          namespaces: ["market-data"]
90          principals: ["cluster.local/ns/market-data/sa/market-data-service"]
91      when:
92      - key: request.auth.claims[groups]
93        values: ["market-access"]
94

1Security Incidents:
2  Before ZTA (12 months): 14 incidents
3    - Unauthorized access: 8
4    - Lateral movement: 4
5    - Data exfiltration: 2
6  
7  After ZTA (18 months): 0 incidents
8    - Unauthorized access attempts: 247 (all blocked)
9    - Lateral movement: 0 (microsegmentation prevented)
10    - Data exfiltration: 0
11
12Breach Cost Reduction:
13  Before: $4.7M/year (1 major breach)
14  After: $0 (zero breaches)
15  ZTA implementation cost: $820K
16  ROI: 574% over 18 months
17

1Authentication:
2  MFA adoption: 100% (enforced)
3  Device trust verification: 94%
4  Failed auth attempts: 12,847
5  Account takeover prevention: 23 attempts blocked
6
7Authorization:
8  Access decisions/day: 1.2M
9  Average decision latency: 12ms
10  Denied requests: 4.7% (legitimate denials)
11  False positives: 0.3%
12
13Continuous Monitoring:
14  Security events logged: 847M
15  Anomaly detections: 1,247
16  Risk score recalculations: 2.4M/day
17  Auto-revocations: 89 (high risk detected)
18

1Microsegmentation:
2  Network segments: 6
3  Inter-segment policies: 14
4  Denied flows/day: 3,247 (blocked lateral movement)
5  Policy violations: 0
6
7Service Mesh (Istio):
8  Services: 47
9  mTLS adoption: 100%
10  Authorization policies: 68
11  Certificate rotation: automatic (every 24h)
12

11. Deploy Identity Provider (IdP)
2   - OAuth 2.0 / OpenID Connect
3   - SAML for legacy systems
4   - MFA enforcement (TOTP, WebAuthn)
5   
62. Implement Policy Engine
7   - Centralized authorization
8   - Risk-based access control
9   - JWT issuance and verification
10   
113. Device Management
12   - MDM deployment
13   - Device trust verification
14   - Certificate-based auth
15
16Cost: $180K
17Effort: 3 engineers, 3 months
18

11. Network Segmentation
2   - Define security zones
3   - Deploy network policies
4   - Segment isolation
5   
62. Service Mesh
7   - Istio deployment
8   - mTLS enablement
9   - Authorization policies
10   
113. Monitoring
12   - Network flow logging
13   - Anomaly detection
14   - Security dashboards
15
16Cost: $240K
17Effort: 4 engineers, 3 months
18

11. Runtime Monitoring
2   - Security event logging
3   - Behavioral analytics
4   - Risk score recalculation
5   
62. Automated Response
7   - Auto-revocation on risk spike
8   - Session termination
9   - Incident alerting
10   
113. Compliance
12   - Audit logging
13   - Access reviews
14   - Compliance reports
15
16Cost: $190K
17Effort: 3 engineers, 3 months
18

11. Performance Tuning
2   - Policy engine optimization
3   - Caching strategies
4   - Latency reduction
5   
62. User Experience
7   - SSO integration
8   - Passwordless auth
9   - Reduced friction
10   
113. Advanced Analytics
12   - ML-based anomaly detection
13   - User behavior modeling
14   - Threat intelligence
15
16Cost: $210K
17Effort: 4 engineers, 3 months
18