zero trust architecture

Implementing Device Posture Assessment in Zero Trust

Implementing device posture assessment as a zero trust access control by integrating endpoint health signals from CrowdStrike ZTA, Microsoft Intune, and Jamf into conditional access policies that enforce compliance before granting resource access.

conditional-accesscrowdstrike-ztadevice-postureendpoint-complianceintunejamfzero-trust
Install this skill
npx skills add mukul975/Anthropic-Cybersecurity-Skills
Framework mappings

When to Use

  • When enforcing device health as a prerequisite for accessing corporate applications
  • When integrating CrowdStrike ZTA scores, Intune compliance, or Jamf device status into access decisions
  • When implementing CISA Zero Trust Maturity Model device pillar requirements
  • When building conditional access policies that adapt based on real-time endpoint security posture
  • When detecting and blocking access from compromised, unmanaged, or non-compliant devices

Do not use for IoT or headless devices that cannot run posture agents, as a standalone security control without identity verification, or when real-time posture data is unavailable and stale compliance data would create false trust.

Prerequisites

  • Endpoint Detection and Response (EDR): CrowdStrike Falcon with ZTA module, or Microsoft Defender for Endpoint
  • Mobile Device Management (MDM): Microsoft Intune, Jamf Pro, or VMware Workspace ONE
  • Identity Provider: Microsoft Entra ID, Okta, or Ping Identity with conditional access capability
  • ZTNA Platform: Zscaler ZPA, Cloudflare Access, Palo Alto Prisma Access, or cloud-native IAP
  • API access to EDR/MDM platforms for posture signal ingestion

Workflow

Step 1: Define Device Compliance Baselines

Establish minimum security requirements for each device category.

# Microsoft Intune: Create device compliance policy via Graph API
Connect-MgGraph -Scopes "DeviceManagementConfiguration.ReadWrite.All"
 
# Windows 10/11 Compliance Policy
$compliancePolicy = @{
    "@odata.type" = "#microsoft.graph.windows10CompliancePolicy"
    displayName = "Zero Trust - Windows Compliance"
    description = "Minimum device requirements for zero trust access"
    osMinimumVersion = "10.0.19045"
    bitLockerEnabled = $true
    secureBootEnabled = $true
    codeIntegrityEnabled = $true
    tpmRequired = $true
    antivirusRequired = $true
    antiSpywareRequired = $true
    defenderEnabled = $true
    firewallEnabled = $true
    passwordRequired = $true
    passwordMinimumLength = 12
    passwordRequiredType = "alphanumeric"
    storageRequireEncryption = $true
    scheduledActionsForRule = @(
        @{
            ruleName = "PasswordRequired"
            scheduledActionConfigurations = @(
                @{
                    actionType = "block"
                    gracePeriodHours = 24
                    notificationTemplateId = ""
                    notificationMessageCCList = @()
                }
            )
        }
    )
}
 
New-MgDeviceManagementDeviceCompliancePolicy -BodyParameter $compliancePolicy
 
# macOS Compliance Policy via Jamf Pro API
curl -X POST "https://jamf.company.com/api/v1/compliance-policies" \
  -H "Authorization: Bearer ${JAMF_TOKEN}" \
  -H "Content-Type: application/json" \
  --data '{
    "name": "Zero Trust - macOS Compliance",
    "rules": [
      {"type": "os_version", "operator": ">=", "value": "14.0"},
      {"type": "filevault_enabled", "value": true},
      {"type": "firewall_enabled", "value": true},
      {"type": "gatekeeper_enabled", "value": true},
      {"type": "sip_enabled", "value": true},
      {"type": "auto_update_enabled", "value": true},
      {"type": "screen_lock_timeout", "operator": "<=", "value": 300},
      {"type": "falcon_sensor_running", "value": true}
    ]
  }'

Step 2: Configure CrowdStrike Zero Trust Assessment

Enable ZTA scoring and configure score thresholds for access tiers.

# CrowdStrike Falcon API: Query ZTA scores for all endpoints
curl -X GET "https://api.crowdstrike.com/zero-trust-assessment/entities/assessments/v1?ids=${DEVICE_AID}" \
  -H "Authorization: Bearer ${CS_TOKEN}" \
  -H "Content-Type: application/json"
 
# Response includes:
# {
#   "aid": "device-agent-id",
#   "assessment": {
#     "overall": 82,
#     "os": 90,
#     "sensor_config": 85,
#     "version": "7.14.16703"
#   },
#   "assessment_items": {
#     "os_signals": [
#       {"signal_id": "firmware_protection", "meets_criteria": "yes"},
#       {"signal_id": "disk_encryption", "meets_criteria": "yes"},
#       {"signal_id": "kernel_protection", "meets_criteria": "yes"}
#     ],
#     "sensor_signals": [
#       {"signal_id": "sensor_version", "meets_criteria": "yes"},
#       {"signal_id": "prevention_policies", "meets_criteria": "yes"}
#     ]
#   }
# }
 
# Define ZTA score thresholds for access tiers
# Tier 1 (Basic Access):      ZTA >= 50
# Tier 2 (Standard Access):   ZTA >= 65
# Tier 3 (Sensitive Access):  ZTA >= 80
# Tier 4 (Critical Access):   ZTA >= 90
 
# Query devices below minimum threshold
curl -X GET "https://api.crowdstrike.com/zero-trust-assessment/queries/assessments/v1?filter=assessment.overall:<50" \
  -H "Authorization: Bearer ${CS_TOKEN}"
 
# CrowdStrike ZTA signals evaluated:
# - OS patch level and version
# - Disk encryption (BitLocker/FileVault)
# - Sensor version and configuration
# - Prevention policy enforcement
# - Firmware protection (Secure Boot)
# - Kernel protection (SIP, Code Integrity)
# - Firewall status

Step 3: Integrate Device Posture with Entra ID Conditional Access

Create conditional access policies that require compliant devices.

# Create Conditional Access policy requiring compliant device
Connect-MgGraph -Scopes "Policy.ReadWrite.ConditionalAccess"
 
$caPolicy = @{
    displayName = "Zero Trust - Require Compliant Device"
    state = "enabled"
    conditions = @{
        applications = @{
            includeApplications = @("All")
        }
        users = @{
            includeUsers = @("All")
            excludeGroups = @("BreakGlass-Admins-Group-ID")
        }
        platforms = @{
            includePlatforms = @("all")
        }
        clientAppTypes = @("browser", "mobileAppsAndDesktopClients")
    }
    grantControls = @{
        operator = "AND"
        builtInControls = @("mfa", "compliantDevice")
    }
    sessionControls = @{
        signInFrequency = @{
            value = 4
            type = "hours"
            isEnabled = $true
            authenticationType = "primaryAndSecondaryAuthentication"
            frequencyInterval = "timeBased"
        }
        persistentBrowser = @{
            mode = "never"
            isEnabled = $true
        }
    }
}
 
New-MgIdentityConditionalAccessPolicy -BodyParameter $caPolicy
 
# Create risk-based policy using device compliance + sign-in risk
$riskPolicy = @{
    displayName = "Zero Trust - Block High Risk Sign-Ins on Non-Compliant Devices"
    state = "enabled"
    conditions = @{
        applications = @{ includeApplications = @("All") }
        users = @{ includeUsers = @("All") }
        signInRiskLevels = @("high", "medium")
        devices = @{
            deviceFilter = @{
                mode = "include"
                rule = "device.isCompliant -ne True"
            }
        }
    }
    grantControls = @{
        operator = "OR"
        builtInControls = @("block")
    }
}
 
New-MgIdentityConditionalAccessPolicy -BodyParameter $riskPolicy

Step 4: Configure Okta Device Trust with CrowdStrike Integration

Set up Okta device trust policies using CrowdStrike posture signals.

# Okta: Configure CrowdStrike device trust integration
# Admin Console > Security > Device Integrations > Add Integration
 
# Okta API: Create device assurance policy
curl -X POST "https://company.okta.com/api/v1/device-assurances" \
  -H "Authorization: SSWS ${OKTA_API_TOKEN}" \
  -H "Content-Type: application/json" \
  --data '{
    "name": "Corporate Device Assurance",
    "platform": "WINDOWS",
    "osVersion": {
      "minimum": "10.0.19045"
    },
    "diskEncryptionType": {
      "include": ["ALL_INTERNAL_VOLUMES"]
    },
    "screenLockType": {
      "include": ["BIOMETRIC", "PASSCODE"]
    },
    "secureHardwarePresent": true,
    "thirdPartySignalProviders": {
      "dtc": {
        "browserVersion": {
          "minimum": "120.0"
        },
        "builtInDnsClientEnabled": true,
        "chromeRemoteDesktopAppBlocked": true,
        "crowdStrikeCustomerId": "CS_CUSTOMER_ID",
        "crowdStrikeAgentId": "REQUIRED",
        "crowdStrikeVerifiedState": {
          "include": ["RUNNING"]
        }
      }
    }
  }'
 
# Create Okta authentication policy with device assurance
curl -X POST "https://company.okta.com/api/v1/policies" \
  -H "Authorization: SSWS ${OKTA_API_TOKEN}" \
  -H "Content-Type: application/json" \
  --data '{
    "name": "Zero Trust Application Policy",
    "type": "ACCESS_POLICY",
    "conditions": null,
    "rules": [
      {
        "name": "Managed Device Access",
        "conditions": {
          "device": {
            "assurance": {
              "include": ["DEVICE_ASSURANCE_POLICY_ID"]
            },
            "managed": true,
            "registered": true
          },
          "people": {
            "groups": {"include": ["EMPLOYEES_GROUP_ID"]}
          }
        },
        "actions": {
          "appSignOn": {
            "access": "ALLOW",
            "verificationMethod": {
              "factorMode": "1FA",
              "type": "ASSURANCE"
            }
          }
        }
      },
      {
        "name": "Unmanaged Device - Block",
        "conditions": {
          "device": { "managed": false }
        },
        "actions": {
          "appSignOn": { "access": "DENY" }
        }
      }
    ]
  }'

Step 5: Implement Continuous Posture Monitoring

Set up real-time monitoring of device compliance state changes.

#!/usr/bin/env python3
"""Monitor device posture compliance drift in real-time."""
 
import requests
import time
import json
from datetime import datetime, timezone
 
CROWDSTRIKE_BASE = "https://api.crowdstrike.com"
INTUNE_BASE = "https://graph.microsoft.com/v1.0"
 
def get_cs_token(client_id: str, client_secret: str) -> str:
    resp = requests.post(f"{CROWDSTRIKE_BASE}/oauth2/token", data={
        "client_id": client_id,
        "client_secret": client_secret
    })
    return resp.json()["access_token"]
 
def get_low_zta_devices(token: str, threshold: int = 50) -> list:
    resp = requests.get(
        f"{CROWDSTRIKE_BASE}/zero-trust-assessment/queries/assessments/v1",
        headers={"Authorization": f"Bearer {token}"},
        params={"filter": f"assessment.overall:<{threshold}", "limit": 100}
    )
    return resp.json().get("resources", [])
 
def get_intune_noncompliant(token: str) -> list:
    resp = requests.get(
        f"{INTUNE_BASE}/deviceManagement/managedDevices",
        headers={"Authorization": f"Bearer {token}"},
        params={
            "$filter": "complianceState eq 'noncompliant'",
            "$select": "id,deviceName,userPrincipalName,complianceState,lastSyncDateTime,operatingSystem"
        }
    )
    return resp.json().get("value", [])
 
def check_posture_drift(cs_token: str, intune_token: str):
    print(f"\n[{datetime.now(timezone.utc).isoformat()}] Device Posture Check")
    print("=" * 60)
 
    low_zta = get_low_zta_devices(cs_token, threshold=50)
    print(f"CrowdStrike ZTA < 50: {len(low_zta)} devices")
 
    noncompliant = get_intune_noncompliant(intune_token)
    print(f"Intune Non-Compliant: {len(noncompliant)} devices")
 
    for device in noncompliant[:10]:
        print(f"  - {device['deviceName']} ({device['userPrincipalName']}): "
              f"{device['complianceState']} | Last sync: {device['lastSyncDateTime']}")
 
    return {"low_zta_count": len(low_zta), "noncompliant_count": len(noncompliant)}

Key Concepts

Term Definition
Device Posture Collection of endpoint security attributes (OS version, encryption, EDR status, patch level) evaluated before granting access
CrowdStrike ZTA Score Numerical score (1-100) calculated by CrowdStrike Falcon assessing endpoint security posture based on OS signals and sensor configuration
Device Compliance Policy MDM-defined rules specifying minimum security requirements (encryption, PIN, OS version) that devices must meet
Conditional Access Policy engine (Entra ID, Okta) that evaluates user identity, device compliance, location, and risk before allowing access
Device Trust Verification that an endpoint is managed, enrolled, and meets security baselines before treating it as trusted
Posture Drift Degradation of device security posture over time (expired patches, disabled encryption) that should trigger access revocation

Tools & Systems

  • CrowdStrike Falcon ZTA: Real-time endpoint posture scoring based on OS and sensor security signals
  • Microsoft Intune: MDM platform enforcing device compliance policies and reporting to Entra ID Conditional Access
  • Jamf Pro: Apple device management with compliance rules for macOS and iOS endpoints
  • Microsoft Entra ID Conditional Access: Policy engine consuming Intune compliance and risk signals for access decisions
  • Okta Device Trust: Device assurance policies integrating with CrowdStrike, Chrome Enterprise, and MDM platforms
  • Cloudflare Device Posture: WARP client-based posture checks for disk encryption, OS version, and third-party EDR

Common Scenarios

Scenario: Enforcing Device Compliance for 2,000 Endpoints Across Windows and macOS

Context: A healthcare company with 2,000 endpoints (70% Windows, 30% macOS) must enforce HIPAA-compliant device posture before allowing access to patient data systems. Devices are managed by Intune (Windows) and Jamf (macOS) with CrowdStrike Falcon deployed on all endpoints.

Approach:

  1. Define Windows compliance policy in Intune: BitLocker, Secure Boot, TPM, Defender enabled, OS >= 10.0.19045
  2. Define macOS compliance policy in Jamf: FileVault, Gatekeeper, SIP, Firewall, OS >= 14.0
  3. Configure CrowdStrike ZTA thresholds: >= 70 for general apps, >= 85 for patient data systems
  4. Create Entra ID Conditional Access policies requiring compliant device + MFA for all cloud apps
  5. Configure 24-hour grace period for newly non-compliant devices before blocking
  6. Set up weekly compliance report for IT showing non-compliant devices and remediation actions
  7. Implement automated remediation via Intune: push BitLocker enablement, deploy pending patches

Pitfalls: Grace periods must be long enough for IT to remediate but short enough to limit risk exposure. CrowdStrike ZTA scores can fluctuate with sensor updates; avoid setting thresholds too aggressively initially. BYOD devices may lack MDM enrollment; provide a separate Browser Access path with reduced functionality for unmanaged devices.

Output Format

Device Posture Assessment Report
==================================================
Organization: HealthCorp
Report Date: 2026-02-23
Total Managed Devices: 2,000
 
COMPLIANCE BY PLATFORM:
  Windows (1,400 devices):
    Compliant:              1,302 (93.0%)
    Non-compliant:            98 (7.0%)
    Top Issue: Missing patches (45), BitLocker disabled (23)
 
  macOS (600 devices):
    Compliant:                567 (94.5%)
    Non-compliant:             33 (5.5%)
    Top Issue: OS outdated (18), FileVault disabled (8)
 
CROWDSTRIKE ZTA SCORES:
  Average Score:              78.4
  Devices >= 85 (Critical):  1,456 (72.8%)
  Devices >= 70 (Standard):  1,812 (90.6%)
  Devices < 50 (Blocked):       34 (1.7%)
 
CONDITIONAL ACCESS IMPACT (last 7 days):
  Total sign-in attempts:    45,678
  Blocked by posture:           312 (0.7%)
  Remediated within 24h:        289 (92.6%)
  Still non-compliant:           23
 
POSTURE DRIFT ALERTS:
  Encryption disabled:            5
  EDR sensor stopped:             3
  OS downgraded:                  1
Source materials

References and resources

Everything below is rendered for inspection. Script files are read-only and never run.

References 3

api-reference.md1.5 KB

API Reference: Device Posture Assessment Agent

Dependencies

Library Version Purpose
(stdlib only) Python 3.8+ Platform detection, subprocess for OS security checks

CLI Usage

python scripts/agent.py --output-dir /reports/ --output device_posture.json

Functions

check_os_version() -> dict

Uses platform.system(), platform.version() for OS identification.

check_disk_encryption() -> dict

Windows: manage-bde -status C: (BitLocker). macOS: fdesetup status (FileVault). Linux: lsblk for LUKS.

check_firewall_status() -> dict

Windows: netsh advfirewall show allprofiles state. Linux: ufw status.

check_antivirus() -> dict

Windows: PowerShell Get-MpComputerStatus for Defender real-time protection.

check_screen_lock() -> dict

Windows: Registry InactivityTimeoutSecs check.

compute_posture_score(checks) -> dict

Weighted scoring: encryption (25), firewall (20), AV (25), screen lock (15), OS (15). Returns COMPLIANT/PARTIAL/NON_COMPLIANT.

Posture Checks

Check Weight Tool
Disk Encryption 25 BitLocker/FileVault/LUKS
Firewall 20 Windows Firewall/UFW
Antivirus/EDR 25 Defender/endpoint agent
Screen Lock 15 OS policy
OS Supported 15 Platform detection

Output Schema

{
  "hostname": "WORKSTATION-01",
  "posture": {"score": 85, "compliance": "COMPLIANT"},
  "recommendations": ["Enable disk encryption"]
}
standards.md2.2 KB

Device Posture Assessment - Standards & References

NIST SP 800-207: Zero Trust Architecture

CISA Zero Trust Maturity Model v2.0 - Device Pillar

  • Traditional: Limited visibility into device health
  • Initial: Compliance enforcement via MDM
  • Advanced: Continuous monitoring with automated remediation
  • Optimal: Real-time posture integrated into every access decision
  • URL: https://www.cisa.gov/zero-trust-maturity-model

NIST SP 800-124r2: Guidelines for Managing Mobile Device Security

CrowdStrike ZTA Documentation

Microsoft Intune Compliance

Jamf Pro Compliance

HIPAA Security Rule (45 CFR 164.312)

  • (a)(1): Access control - device posture as access control mechanism
  • (d): Device and media controls - encryption and integrity requirements
workflows.md3.2 KB

Device Posture Assessment Implementation Workflow

Phase 1: Baseline Assessment (Week 1)

1.1 Inventory Current State

  1. Export all managed devices from Intune/Jamf/SCCM
  2. Identify unmanaged devices accessing corporate resources
  3. Document OS distribution, patch levels, and encryption status
  4. Measure current compliance rate before enforcement

1.2 Define Posture Requirements

  1. Establish minimum requirements per device tier:
    • Tier 1 (Basic): OS updated within 90 days, screen lock enabled
    • Tier 2 (Standard): Disk encryption, firewall, antivirus, OS within 60 days
    • Tier 3 (Enhanced): EDR running, ZTA score >= 70, OS within 30 days, TPM/Secure Boot
    • Tier 4 (Critical): ZTA score >= 90, fully managed, patched within 7 days
  2. Map application sensitivity to required posture tier
  3. Define grace periods for remediation (24h standard, 4h for critical)

Phase 2: MDM Policy Configuration (Week 2-3)

2.1 Intune Compliance Policies

  1. Create Windows compliance policy: BitLocker, Secure Boot, TPM, Defender, OS version
  2. Create macOS compliance policy: FileVault, Gatekeeper, SIP, Firewall
  3. Create iOS/Android compliance policy: Encryption, PIN, jailbreak detection
  4. Configure non-compliance actions: email notification, mark non-compliant, block after grace
  5. Assign policies to device groups

2.2 Jamf Pro Configuration

  1. Create smart groups for compliant/non-compliant macOS devices
  2. Configure compliance criteria: FileVault, SIP, Gatekeeper, OS version
  3. Set up automated remediation scripts for common issues
  4. Configure compliance reporting to Jamf Protect or SIEM

Phase 3: EDR Integration (Week 3-4)

3.1 CrowdStrike ZTA Setup

  1. Enable Zero Trust Assessment module in Falcon console
  2. Configure ZTA score thresholds per access tier
  3. Set up API integration for ZTNA platform (Zscaler, Cloudflare, Okta)
  4. Create host groups for ZTA monitoring
  5. Build dashboard for ZTA score distribution

3.2 Microsoft Defender for Endpoint

  1. Enable device risk assessment in Defender Security Center
  2. Configure risk levels: Low, Medium, High, Critical
  3. Integrate with Intune compliance via Defender connector
  4. Set up conditional access policy consuming device risk signal

Phase 4: Conditional Access Configuration (Week 4-5)

4.1 Entra ID Conditional Access

  1. Create policy: Require compliant device for all cloud apps
  2. Create policy: Block high-risk devices from sensitive apps
  3. Create policy: Require MFA + compliant device for admin portals
  4. Configure break-glass exclusions for emergency access
  5. Start in report-only mode, then switch to enforcement

4.2 Okta Device Trust

  1. Configure device trust integration with MDM platforms
  2. Create device assurance policies with CrowdStrike integration
  3. Set up authentication policies requiring device trust
  4. Test with enrolled and non-enrolled devices

Phase 5: Monitoring and Remediation (Ongoing)

  1. Build compliance dashboard showing real-time posture across fleet
  2. Configure alerts for posture drift (encryption disabled, EDR stopped)
  3. Automate remediation: push encryption enablement, deploy patches
  4. Generate weekly compliance reports for security leadership
  5. Conduct monthly review of posture requirements vs. threat landscape

Scripts 2

agent.py6.7 KB
Display-only source. This catalog never executes bundled scripts.
#!/usr/bin/env python3
"""Device posture assessment agent for zero trust endpoint compliance evaluation."""

import argparse
import json
import logging
import os
import platform
import subprocess
from datetime import datetime

logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] %(message)s")
logger = logging.getLogger(__name__)


def check_os_version() -> dict:
    """Check OS version and patch level."""
    return {
        "os": platform.system(),
        "version": platform.version(),
        "release": platform.release(),
        "machine": platform.machine(),
    }


def check_disk_encryption() -> dict:
    """Check if disk encryption is enabled."""
    system = platform.system()
    if system == "Windows":
        try:
            result = subprocess.run(
                ["manage-bde", "-status", "C:"], capture_output=True, text=True, timeout=10)
            encrypted = "Fully Encrypted" in result.stdout or "100%" in result.stdout
            return {"enabled": encrypted, "tool": "BitLocker", "output": result.stdout[:200]}
        except FileNotFoundError:
            return {"enabled": False, "tool": "BitLocker", "error": "manage-bde not found"}
    elif system == "Darwin":
        try:
            result = subprocess.run(
                ["fdesetup", "status"], capture_output=True, text=True, timeout=10)
            return {"enabled": "On" in result.stdout, "tool": "FileVault"}
        except FileNotFoundError:
            return {"enabled": False, "error": "fdesetup not found"}
    elif system == "Linux":
        try:
            result = subprocess.run(
                ["lsblk", "-o", "NAME,TYPE,FSTYPE"], capture_output=True, text=True, timeout=10)
            encrypted = "crypto_LUKS" in result.stdout or "crypt" in result.stdout
            return {"enabled": encrypted, "tool": "LUKS"}
        except FileNotFoundError:
            return {"enabled": False, "error": "lsblk not found"}
    return {"enabled": False, "error": "Unsupported OS"}


def check_firewall_status() -> dict:
    """Check if host firewall is enabled."""
    system = platform.system()
    if system == "Windows":
        try:
            result = subprocess.run(
                ["netsh", "advfirewall", "show", "allprofiles", "state"],
                capture_output=True, text=True, timeout=10)
            enabled = "ON" in result.stdout.upper()
            return {"enabled": enabled, "tool": "Windows Firewall"}
        except FileNotFoundError:
            return {"enabled": False, "error": "netsh not found"}
    elif system == "Linux":
        try:
            result = subprocess.run(
                ["ufw", "status"], capture_output=True, text=True, timeout=10)
            return {"enabled": "active" in result.stdout.lower(), "tool": "UFW"}
        except FileNotFoundError:
            return {"enabled": False, "error": "ufw not found"}
    return {"enabled": False, "error": "Unsupported OS"}


def check_antivirus() -> dict:
    """Check if antivirus/EDR is running."""
    system = platform.system()
    if system == "Windows":
        try:
            result = subprocess.run(
                ["powershell", "-Command", "Get-MpComputerStatus | Select-Object RealTimeProtectionEnabled | ConvertTo-Json"],
                capture_output=True, text=True, timeout=15)
            if result.stdout:
                data = json.loads(result.stdout)
                return {"enabled": data.get("RealTimeProtectionEnabled", False),
                        "tool": "Windows Defender"}
        except (FileNotFoundError, json.JSONDecodeError):
            pass
    return {"enabled": False, "tool": "unknown"}


def check_screen_lock() -> dict:
    """Check if screen lock is configured with timeout."""
    system = platform.system()
    if system == "Windows":
        try:
            result = subprocess.run(
                ["powershell", "-Command",
                 "(Get-ItemProperty 'HKLM:\\SOFTWARE\\Microsoft\\Windows\\CurrentVersion\\Policies\\System').InactivityTimeoutSecs"],
                capture_output=True, text=True, timeout=10)
            timeout = int(result.stdout.strip()) if result.stdout.strip() else 0
            return {"configured": timeout > 0, "timeout_seconds": timeout}
        except (FileNotFoundError, ValueError):
            pass
    return {"configured": False, "timeout_seconds": 0}


def compute_posture_score(checks: dict) -> dict:
    """Compute device posture compliance score."""
    weights = {"disk_encryption": 25, "firewall": 20, "antivirus": 25,
               "screen_lock": 15, "os_supported": 15}
    score = 0
    if checks.get("disk_encryption", {}).get("enabled"):
        score += weights["disk_encryption"]
    if checks.get("firewall", {}).get("enabled"):
        score += weights["firewall"]
    if checks.get("antivirus", {}).get("enabled"):
        score += weights["antivirus"]
    if checks.get("screen_lock", {}).get("configured"):
        score += weights["screen_lock"]
    score += weights["os_supported"]
    if score >= 80:
        compliance = "COMPLIANT"
    elif score >= 50:
        compliance = "PARTIAL"
    else:
        compliance = "NON_COMPLIANT"
    return {"score": score, "max_score": 100, "compliance": compliance}


def generate_report() -> dict:
    """Generate device posture assessment report."""
    checks = {
        "os_info": check_os_version(),
        "disk_encryption": check_disk_encryption(),
        "firewall": check_firewall_status(),
        "antivirus": check_antivirus(),
        "screen_lock": check_screen_lock(),
    }
    posture = compute_posture_score(checks)
    recommendations = []
    if not checks["disk_encryption"].get("enabled"):
        recommendations.append("Enable disk encryption (BitLocker/FileVault/LUKS)")
    if not checks["firewall"].get("enabled"):
        recommendations.append("Enable host firewall")
    if not checks["antivirus"].get("enabled"):
        recommendations.append("Enable antivirus/EDR with real-time protection")
    return {
        "analysis_date": datetime.utcnow().isoformat(),
        "hostname": platform.node(),
        "checks": checks,
        "posture": posture,
        "recommendations": recommendations,
    }


def main():
    parser = argparse.ArgumentParser(description="Device Posture Assessment Agent")
    parser.add_argument("--output-dir", default=".")
    parser.add_argument("--output", default="device_posture_report.json")
    args = parser.parse_args()

    os.makedirs(args.output_dir, exist_ok=True)
    report = generate_report()
    out_path = os.path.join(args.output_dir, args.output)
    with open(out_path, "w") as f:
        json.dump(report, f, indent=2)
    logger.info("Report saved to %s", out_path)
    print(json.dumps(report["posture"], indent=2))


if __name__ == "__main__":
    main()
process.py12.0 KB
Display-only source. This catalog never executes bundled scripts.
#!/usr/bin/env python3
"""
Device Posture Assessment - Compliance Audit Tool

Queries CrowdStrike ZTA scores, Microsoft Intune compliance status,
and generates a consolidated device posture compliance report.

Requirements:
    pip install requests msal pandas
"""

import json
import sys
from datetime import datetime, timezone
from typing import Any

import requests


class DevicePostureAuditor:
    """Audit device posture compliance across EDR and MDM platforms."""

    def __init__(self, cs_client_id: str, cs_client_secret: str,
                 azure_tenant_id: str, azure_client_id: str, azure_client_secret: str):
        self.cs_client_id = cs_client_id
        self.cs_client_secret = cs_client_secret
        self.azure_tenant_id = azure_tenant_id
        self.azure_client_id = azure_client_id
        self.azure_client_secret = azure_client_secret
        self.cs_token = None
        self.azure_token = None

    def authenticate_crowdstrike(self):
        """Get CrowdStrike API bearer token."""
        resp = requests.post(
            "https://api.crowdstrike.com/oauth2/token",
            data={
                "client_id": self.cs_client_id,
                "client_secret": self.cs_client_secret
            },
            timeout=30
        )
        resp.raise_for_status()
        self.cs_token = resp.json()["access_token"]
        print("[AUTH] CrowdStrike authenticated")

    def authenticate_azure(self):
        """Get Microsoft Graph API token."""
        resp = requests.post(
            f"https://login.microsoftonline.com/{self.azure_tenant_id}/oauth2/v2.0/token",
            data={
                "client_id": self.azure_client_id,
                "client_secret": self.azure_client_secret,
                "scope": "https://graph.microsoft.com/.default",
                "grant_type": "client_credentials"
            },
            timeout=30
        )
        resp.raise_for_status()
        self.azure_token = resp.json()["access_token"]
        print("[AUTH] Microsoft Graph authenticated")

    def get_zta_scores(self) -> dict[str, Any]:
        """Get CrowdStrike ZTA score distribution."""
        print("\n[1/4] Querying CrowdStrike ZTA scores...")
        headers = {"Authorization": f"Bearer {self.cs_token}"}

        # Get all device AIDs with ZTA assessments
        resp = requests.get(
            "https://api.crowdstrike.com/zero-trust-assessment/queries/assessments/v1",
            headers=headers,
            params={"limit": 5000},
            timeout=60
        )
        resp.raise_for_status()
        device_ids = resp.json().get("resources", [])

        if not device_ids:
            print("  No ZTA assessments found")
            return {"total": 0, "distribution": {}}

        # Get detailed assessments in batches of 100
        scores = []
        for i in range(0, len(device_ids), 100):
            batch = device_ids[i:i+100]
            resp = requests.get(
                "https://api.crowdstrike.com/zero-trust-assessment/entities/assessments/v1",
                headers=headers,
                params={"ids": batch},
                timeout=60
            )
            if resp.status_code == 200:
                for resource in resp.json().get("resources", []):
                    assessment = resource.get("assessment", {})
                    scores.append({
                        "aid": resource.get("aid"),
                        "overall": assessment.get("overall", 0),
                        "os_score": assessment.get("os", 0),
                        "sensor_score": assessment.get("sensor_config", 0)
                    })

        # Calculate distribution
        distribution = {
            "critical_90_100": sum(1 for s in scores if s["overall"] >= 90),
            "high_80_89": sum(1 for s in scores if 80 <= s["overall"] < 90),
            "medium_65_79": sum(1 for s in scores if 65 <= s["overall"] < 80),
            "low_50_64": sum(1 for s in scores if 50 <= s["overall"] < 65),
            "blocked_below_50": sum(1 for s in scores if s["overall"] < 50),
        }
        avg_score = sum(s["overall"] for s in scores) / len(scores) if scores else 0

        print(f"  Total devices: {len(scores)}")
        print(f"  Average ZTA score: {avg_score:.1f}")
        print(f"  Distribution: {distribution}")

        return {
            "total": len(scores),
            "average_score": round(avg_score, 1),
            "distribution": distribution,
            "below_threshold_50": distribution["blocked_below_50"]
        }

    def get_intune_compliance(self) -> dict[str, Any]:
        """Get Microsoft Intune device compliance status."""
        print("\n[2/4] Querying Intune compliance status...")
        headers = {"Authorization": f"Bearer {self.azure_token}"}

        resp = requests.get(
            "https://graph.microsoft.com/v1.0/deviceManagement/managedDevices",
            headers=headers,
            params={
                "$select": "id,deviceName,userPrincipalName,complianceState,"
                           "operatingSystem,osVersion,isEncrypted,lastSyncDateTime,"
                           "managementAgent",
                "$top": 999
            },
            timeout=60
        )
        resp.raise_for_status()
        devices = resp.json().get("value", [])

        stats = {
            "total": len(devices),
            "compliant": 0,
            "noncompliant": 0,
            "in_grace_period": 0,
            "unknown": 0,
            "os_distribution": {},
            "encryption_status": {"encrypted": 0, "not_encrypted": 0},
            "stale_devices": 0,
            "noncompliant_details": []
        }

        now = datetime.now(timezone.utc)
        for device in devices:
            compliance = device.get("complianceState", "unknown")
            os_name = device.get("operatingSystem", "unknown")
            encrypted = device.get("isEncrypted", False)

            stats["os_distribution"][os_name] = stats["os_distribution"].get(os_name, 0) + 1

            if encrypted:
                stats["encryption_status"]["encrypted"] += 1
            else:
                stats["encryption_status"]["not_encrypted"] += 1

            if compliance == "compliant":
                stats["compliant"] += 1
            elif compliance == "noncompliant":
                stats["noncompliant"] += 1
                stats["noncompliant_details"].append({
                    "device": device.get("deviceName"),
                    "user": device.get("userPrincipalName"),
                    "os": f"{os_name} {device.get('osVersion', '')}",
                    "encrypted": encrypted
                })
            elif compliance == "inGracePeriod":
                stats["in_grace_period"] += 1
            else:
                stats["unknown"] += 1

            # Check for stale devices (no sync in 30 days)
            last_sync = device.get("lastSyncDateTime")
            if last_sync:
                try:
                    sync_dt = datetime.fromisoformat(last_sync.replace("Z", "+00:00"))
                    if (now - sync_dt).days > 30:
                        stats["stale_devices"] += 1
                except (ValueError, TypeError):
                    pass

        compliance_rate = (stats["compliant"] / stats["total"] * 100) if stats["total"] else 0
        print(f"  Total: {stats['total']}, Compliant: {stats['compliant']} ({compliance_rate:.1f}%)")
        print(f"  Non-compliant: {stats['noncompliant']}, Grace period: {stats['in_grace_period']}")
        print(f"  Encryption: {stats['encryption_status']}")
        print(f"  Stale devices (>30d no sync): {stats['stale_devices']}")

        return stats

    def correlate_posture(self, zta: dict, intune: dict) -> dict[str, Any]:
        """Correlate ZTA and MDM compliance for overall posture score."""
        print("\n[3/4] Correlating posture signals...")

        total_devices = max(zta["total"], intune["total"])
        zta_passing = zta["total"] - zta.get("below_threshold_50", 0)
        intune_passing = intune["compliant"] + intune["in_grace_period"]

        overall_compliance = min(
            (zta_passing / zta["total"] * 100) if zta["total"] else 0,
            (intune_passing / intune["total"] * 100) if intune["total"] else 0
        )

        summary = {
            "estimated_total_devices": total_devices,
            "zta_passing_rate": round((zta_passing / zta["total"] * 100) if zta["total"] else 0, 1),
            "intune_passing_rate": round((intune_passing / intune["total"] * 100) if intune["total"] else 0, 1),
            "overall_compliance_rate": round(overall_compliance, 1),
            "risk_level": "LOW" if overall_compliance >= 90 else "MEDIUM" if overall_compliance >= 75 else "HIGH"
        }

        print(f"  ZTA passing: {summary['zta_passing_rate']}%")
        print(f"  Intune passing: {summary['intune_passing_rate']}%")
        print(f"  Overall compliance: {summary['overall_compliance_rate']}%")
        print(f"  Risk level: {summary['risk_level']}")

        return summary

    def generate_report(self, zta: dict, intune: dict, correlated: dict) -> str:
        """Generate consolidated posture report."""
        print("\n[4/4] Generating report...")
        now = datetime.now(timezone.utc).strftime("%Y-%m-%d %H:%M UTC")

        report = f"""
Device Posture Compliance Report
{'=' * 55}
Generated: {now}

1. CROWDSTRIKE ZTA SCORES
   Total devices assessed:      {zta['total']}
   Average ZTA score:           {zta['average_score']}
   Score >= 90 (Critical OK):   {zta['distribution'].get('critical_90_100', 0)}
   Score 80-89 (High OK):       {zta['distribution'].get('high_80_89', 0)}
   Score 65-79 (Medium OK):     {zta['distribution'].get('medium_65_79', 0)}
   Score 50-64 (Low):           {zta['distribution'].get('low_50_64', 0)}
   Score < 50 (BLOCKED):        {zta['distribution'].get('blocked_below_50', 0)}

2. INTUNE COMPLIANCE
   Total managed devices:       {intune['total']}
   Compliant:                   {intune['compliant']}
   Non-compliant:               {intune['noncompliant']}
   In grace period:             {intune['in_grace_period']}
   Stale (>30d no sync):        {intune['stale_devices']}
   Encrypted:                   {intune['encryption_status']['encrypted']}
   Not encrypted:               {intune['encryption_status']['not_encrypted']}

3. OVERALL POSTURE
   ZTA passing rate:            {correlated['zta_passing_rate']}%
   Intune passing rate:         {correlated['intune_passing_rate']}%
   Combined compliance:         {correlated['overall_compliance_rate']}%
   Risk level:                  {correlated['risk_level']}

4. RECOMMENDATIONS
"""
        recs = []
        if zta["distribution"].get("blocked_below_50", 0) > 0:
            recs.append(f"   - {zta['distribution']['blocked_below_50']} devices below ZTA 50 - investigate immediately")
        if intune["encryption_status"]["not_encrypted"] > 0:
            recs.append(f"   - {intune['encryption_status']['not_encrypted']} devices lack encryption - enforce BitLocker/FileVault")
        if intune["stale_devices"] > 0:
            recs.append(f"   - {intune['stale_devices']} stale devices - verify active use or remove")
        if correlated["overall_compliance_rate"] < 95:
            recs.append(f"   - Overall compliance {correlated['overall_compliance_rate']}% below 95% target")
        if not recs:
            recs.append("   - All devices meet compliance requirements")
        report += "\n".join(recs)
        return report


def main():
    if len(sys.argv) < 6:
        print("Usage: python process.py <cs_client_id> <cs_client_secret> "
              "<azure_tenant_id> <azure_client_id> <azure_client_secret>")
        sys.exit(1)

    auditor = DevicePostureAuditor(*sys.argv[1:6])
    auditor.authenticate_crowdstrike()
    auditor.authenticate_azure()

    zta = auditor.get_zta_scores()
    intune = auditor.get_intune_compliance()
    correlated = auditor.correlate_posture(zta, intune)
    report = auditor.generate_report(zta, intune, correlated)
    print(report)

    filename = f"device_posture_report_{datetime.now().strftime('%Y%m%d')}.txt"
    with open(filename, "w") as f:
        f.write(report)
    print(f"\nReport saved to: {filename}")


if __name__ == "__main__":
    main()

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