Agent skill

implementing-browser-isolation-for-zero-trust

Deploys remote browser isolation (RBI) as a core component of a Zero Trust architecture. Implements isolation policies with URL categorization and risk-based routing, content disarming and reconstruction (CDR) for file sanitization, data loss prevention controls within isolated sessions, and integration with Secure Web Gateway and ZTNA platforms. Based on Cloudflare Browser Isolation, Menlo Security, and Zscaler RBI approaches. Use when hardening web access against zero-day exploits, phishing, credential theft, and browser-based data exfiltration.

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SKILL.md

Implementing Browser Isolation for Zero Trust

When to Use

  • When deploying remote browser isolation as part of a Zero Trust security architecture
  • When protecting users from zero-day browser exploits and drive-by downloads
  • When implementing content disarming and reconstruction for file downloads
  • When enforcing data loss prevention policies for web browsing sessions
  • When securing access to untrusted or uncategorized websites
  • When integrating browser isolation with existing SWG and ZTNA infrastructure
  • When protecting against phishing and credential theft via isolated rendering

Prerequisites

  • Familiarity with Zero Trust architecture principles and network security
  • Understanding of Secure Web Gateway (SWG) and proxy deployment models
  • Access to a test or lab environment for policy validation
  • Python 3.8+ with required dependencies installed
  • DNS and proxy infrastructure for traffic routing

Instructions

Phase 1: URL Categorization and Risk Classification

Build a URL categorization engine that classifies websites by risk level to determine isolation policy. URLs are scored based on threat intelligence feeds, domain reputation, content category, and historical risk indicators.

python
from agent import BrowserIsolationPolicyEngine

engine = BrowserIsolationPolicyEngine(
    organization="Acme Corp",
    default_isolation_mode="isolate_risky",
)

# Classify a URL and determine isolation action
result = engine.classify_url("https://docs.google.com/spreadsheets/d/abc123")
print(f"Category: {result['category']}")
print(f"Risk Level: {result['risk_level']}")
print(f"Isolation Action: {result['action']}")
# Output: Category: cloud_productivity
#         Risk Level: low
#         Action: allow_direct

result = engine.classify_url("https://unknown-sketchy-domain.xyz/download.html")
print(f"Category: {result['category']}")
print(f"Risk Level: {result['risk_level']}")
print(f"Isolation Action: {result['action']}")
# Output: Category: uncategorized
#         Risk Level: high
#         Action: full_isolation

Phase 2: Isolation Policy Configuration

Define isolation policies that map URL categories and risk levels to specific isolation modes and DLP restrictions. Policies support granular controls including clipboard, file download, upload, and printing restrictions.

python
# Configure isolation policies
engine.add_isolation_policy(
    name="Block Uncategorized Sites",
    description="Fully isolate all uncategorized or newly registered domains",
    match_criteria={
        "url_categories": ["uncategorized", "newly_registered"],
        "risk_levels": ["high", "critical"],
    },
    isolation_mode="full_isolation",
    dlp_controls={
        "disable_copy_paste": True,
        "disable_download": True,
        "disable_upload": True,
        "disable_printing": True,
        "disable_keyboard_input": False,
        "watermark_session": True,
    },
)

engine.add_isolation_policy(
    name="Isolate Webmail with DLP",
    description="Isolate personal webmail with download restrictions",
    match_criteria={
        "url_categories": ["webmail"],
        "domains": ["mail.google.com", "outlook.live.com", "mail.yahoo.com"],
    },
    isolation_mode="read_only_isolation",
    dlp_controls={
        "disable_copy_paste": True,
        "disable_download": True,
        "disable_upload": True,
        "disable_printing": True,
        "disable_keyboard_input": False,
        "watermark_session": False,
    },
)

engine.add_isolation_policy(
    name="CDR for File Downloads",
    description="Apply content disarm and reconstruction to all file downloads",
    match_criteria={
        "url_categories": ["*"],
        "file_types": ["pdf", "docx", "xlsx", "pptx", "zip", "exe", "msi"],
    },
    isolation_mode="cdr_passthrough",
    cdr_config={
        "strip_macros": True,
        "strip_embedded_objects": True,
        "strip_javascript": True,
        "strip_active_content": True,
        "flatten_pdf": True,
        "reconstruct_to_safe_format": True,
        "max_file_size_mb": 50,
        "allowed_file_types": ["pdf", "docx", "xlsx", "pptx", "png", "jpg"],
    },
)

engine.add_isolation_policy(
    name="Allow Trusted SaaS Direct",
    description="Allow direct access to sanctioned SaaS applications",
    match_criteria={
        "url_categories": ["cloud_productivity", "business_saas"],
        "domains": [
            "*.office365.com", "*.office.com", "*.microsoft.com",
            "*.salesforce.com", "*.slack.com", "*.github.com",
        ],
        "risk_levels": ["low"],
    },
    isolation_mode="allow_direct",
    dlp_controls={
        "disable_copy_paste": False,
        "disable_download": False,
        "disable_upload": False,
        "log_all_downloads": True,
    },
)

# List all policies
for policy in engine.list_policies():
    print(f"  [{policy['priority']}] {policy['name']} -> {policy['isolation_mode']}")

Phase 3: Content Disarming and Reconstruction (CDR)

Implement CDR processing to sanitize downloaded files by deconstructing them, stripping potentially malicious elements (macros, embedded objects, scripts), and reconstructing clean versions that preserve usability.

python
# Process a file through CDR
cdr_result = engine.process_file_cdr(
    file_path="/tmp/downloads/quarterly_report.docx",
    source_url="https://partner-portal.example.com/reports/q4.docx",
    cdr_profile="strict",
)

print(f"Original file: {cdr_result['original']['filename']}")
print(f"Original size: {cdr_result['original']['size_bytes']} bytes")
print(f"Threats found: {cdr_result['threats_found']}")
for threat in cdr_result['threats_detail']:
    print(f"  - {threat['type']}: {threat['description']} [{threat['action']}]")
print(f"Clean file: {cdr_result['reconstructed']['filename']}")
print(f"Clean size: {cdr_result['reconstructed']['size_bytes']} bytes")
print(f"File integrity preserved: {cdr_result['reconstructed']['usable']}")

# Example output:
# Original file: quarterly_report.docx
# Original size: 245760 bytes
# Threats found: 3
#   - macro: VBA macro with AutoOpen trigger [STRIPPED]
#   - embedded_ole: Embedded OLE object (executable) [STRIPPED]
#   - external_link: External template reference [STRIPPED]
# Clean file: quarterly_report_clean.docx
# Clean size: 198432 bytes
# File integrity preserved: True

Phase 4: Session Control and Monitoring

Implement real-time session monitoring for isolated browsing sessions with keystroke logging policy, clipboard interception, and download tracking. Integrate with SIEM for security event correlation.

python
# Create an isolation session
session = engine.create_isolation_session(
    user_id="jsmith@acme.com",
    user_groups=["engineering", "contractors"],
    device_posture={
        "os": "Windows 11",
        "managed": True,
        "edr_running": True,
        "disk_encrypted": True,
        "os_patched": True,
    },
    target_url="https://external-vendor.example.com/portal",
)

print(f"Session ID: {session['session_id']}")
print(f"Isolation Mode: {session['isolation_mode']}")
print(f"Applied Policy: {session['applied_policy']}")
print(f"DLP Controls: {json.dumps(session['dlp_controls'], indent=2)}")

# Monitor session events
events = engine.get_session_events(session_id=session["session_id"])
for event in events:
    print(f"  [{event['timestamp']}] {event['event_type']}: {event['details']}")

# Generate session audit report
audit = engine.generate_session_audit(
    user_id="jsmith@acme.com",
    date_range=("2026-03-01", "2026-03-19"),
)
print(f"Total sessions: {audit['total_sessions']}")
print(f"Isolated sessions: {audit['isolated_sessions']}")
print(f"Files processed via CDR: {audit['cdr_processed_files']}")
print(f"DLP violations: {audit['dlp_violations']}")

Phase 5: Integration with Zero Trust Platform

Integrate browser isolation with the broader Zero Trust architecture including identity provider, device posture checks, and conditional access policies.

python
# Define Zero Trust conditional access integration
zt_policy = engine.create_zero_trust_integration(
    identity_provider="Azure AD",
    conditional_access_rules=[
        {
            "name": "Unmanaged Device Isolation",
            "condition": {"device_managed": False},
            "action": "full_isolation",
            "dlp_override": {"disable_download": True, "disable_upload": True},
        },
        {
            "name": "High Risk User Isolation",
            "condition": {"user_risk_level": "high"},
            "action": "full_isolation",
            "dlp_override": {"disable_copy_paste": True, "watermark_session": True},
        },
        {
            "name": "Contractor Restricted Access",
            "condition": {"user_group": "contractors"},
            "action": "read_only_isolation",
            "dlp_override": {"disable_download": True, "disable_printing": True},
        },
        {
            "name": "Privileged Admin Isolation",
            "condition": {"user_group": "admins", "target_category": "admin_console"},
            "action": "full_isolation",
            "dlp_override": {"watermark_session": True, "record_session": True},
        },
    ],
    swg_integration={
        "proxy_mode": "explicit",
        "pac_url": "https://pac.acme.com/proxy.pac",
        "ssl_inspection": True,
        "bypass_domains": ["*.acme.internal"],
    },
)

# Evaluate a request against all policies
decision = engine.evaluate_access_request(
    user_id="contractor@vendor.com",
    user_groups=["contractors"],
    device_posture={"managed": False, "edr_running": False},
    target_url="https://sensitive-app.acme.com/dashboard",
    user_risk_level="medium",
)
print(f"Decision: {decision['action']}")
print(f"Matched Rules: {[r['name'] for r in decision['matched_rules']]}")
print(f"DLP Controls: {decision['effective_dlp_controls']}")

Examples

Quick Policy Deployment for Phishing Protection

python
engine = BrowserIsolationPolicyEngine(default_isolation_mode="isolate_risky")

# Isolate all links from email
engine.add_isolation_policy(
    name="Email Link Isolation",
    description="Isolate all URLs clicked from email clients",
    match_criteria={
        "referrer_categories": ["email_client"],
        "url_categories": ["*"],
    },
    isolation_mode="full_isolation",
    dlp_controls={
        "disable_keyboard_input": True,
        "disable_download": True,
        "watermark_session": True,
    },
)

# Test against a phishing URL
result = engine.evaluate_access_request(
    user_id="user@acme.com",
    target_url="https://micr0soft-login.phishing.com/auth",
    referrer="https://mail.google.com",
    user_risk_level="low",
)
print(f"Action: {result['action']}")  # full_isolation

CDR Pipeline for All Downloads

python
engine = BrowserIsolationPolicyEngine()

# Scan a batch of downloaded files through CDR
files = [
    "/tmp/downloads/invoice.pdf",
    "/tmp/downloads/contract.docx",
    "/tmp/downloads/data_export.xlsx",
    "/tmp/downloads/presentation.pptx",
]

batch_result = engine.batch_cdr_process(
    files=files,
    cdr_profile="strict",
    quarantine_on_threat=True,
)

print(f"Processed: {batch_result['total_processed']}")
print(f"Clean: {batch_result['clean_count']}")
print(f"Threats neutralized: {batch_result['threats_neutralized']}")
print(f"Quarantined: {batch_result['quarantined_count']}")
for f in batch_result["results"]:
    status = "CLEAN" if f["clean"] else "SANITIZED"
    print(f"  [{status}] {f['filename']}: {f['threats_found']} threats")

Generating Isolation Policy Compliance Report

python
engine = BrowserIsolationPolicyEngine()

report = engine.generate_compliance_report(
    date_range=("2026-03-01", "2026-03-19"),
    include_metrics=True,
)

print(f"Total web requests: {report['total_requests']}")
print(f"Isolated requests: {report['isolated_requests']} ({report['isolation_rate']}%)")
print(f"CDR processed files: {report['cdr_stats']['total_files']}")
print(f"Threats neutralized: {report['cdr_stats']['threats_neutralized']}")
print(f"DLP violations blocked: {report['dlp_violations_blocked']}")
print(f"Zero-day attacks prevented: {report['zero_day_blocked']}")

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