Employees are sending proprietary data to AI tools your security team has never evaluated. Our feed of 17,410+ classified AI domains gives you organization-wide access control — deployed once, enforced everywhere, updated daily.
New AI tools launch weekly — requiring no installation, no procurement, and no IT involvement. Over 60% of knowledge workers already use AI tools their IT departments have never sanctioned or discovered.
An employee pastes a contract into a translation tool or routes source code through an AI debugger. No alert fires — your existing security stack doesn't see it.
Blocking a dozen well-known domains was sufficient two years ago. Today, tens of thousands of specialized AI tools span every business function — and three more launch before your list is updated.
Multi-region offices, multiple firewall vendors, decentralized IT governance, and differing departmental needs make blanket blocks untenable. Category-aware, centrally managed policy is essential.
GDPR, CCPA, and sector-specific frameworks hold you accountable for cross-border data transfers. IP disclosed to an AI tool for training cannot be recalled.
Organizations that deploy all three pillars achieve defense-in-depth coverage. Each addresses a different aspect of the AI access control problem.
Deploy the classified domain feed at the firewall, secure web gateway, and DNS resolver, so every AI access attempt is intercepted at the perimeter — on every device, managed or not.
Correlate DNS, proxy, and SIEM logs against the classified feed to run a shadow AI audit. You cannot build a defensible policy without knowing which tools employees already depend on.
The 18-category taxonomy lets you block code assistants while allowing design tools. Policy maps to organizational need — not a binary allow/deny for every AI tool.
For organizations with 5,000+ endpoints across multiple offices, the recommended deployment follows a hub-and-spoke model. The central SOC maintains the master policy and publishes it to every enforcement point.
Catches traffic that bypasses the perimeter, including VPN split-tunnel and guest network segments.
Blocks AI domains in managed browsers even when devices are completely off-network.
Consistent enforcement whether the user is at HQ, on a VPN, or working remotely.
Enterprise AI blocking fails most often due to organizational resistance, not technical limitations. The rollout must balance security urgency with change management discipline across defined phases.
Deploy in audit-only mode at a single representative site. Correlate DNS/proxy logs against the feed to produce a shadow AI usage report — no traffic is blocked yet.
Move from audit to selective enforcement at the pilot site. Block high-risk categories (Chatbots, Code Assistants, Data Analytics) while monitoring lower-risk ones.
Roll the tested configuration to additional sites in the same region. The employee communication plan and exception workflow should be fully operational.
Extend enforcement to all remaining sites worldwide. Apply regional variations — stricter blocking for EU sites, engineering exceptions for R&D locations.
Clear, empathetic communication reduces pushback during rollout. Adapt this template to match your organization's culture and the specific categories being restricted.
Subject: Changes to AI Tool Access — What You Need to Know From: Chief Information Security Officer To: All Employees Date: [Deployment Date] Team, Starting [date], [Company] is implementing controls on access to external AI tools from the corporate network. This change is part of our broader data protection program and is designed to prevent accidental exposure of confidential information. What is changing: - Access to unapproved AI chatbots, code assistants, and data analysis tools will be restricted on the corporate network. - Approved AI tools (listed at [internal wiki URL]) remain fully available. - If you need access to a tool that is currently blocked, submit a request through [exception portal URL]. Why we are doing this: - Many AI tools process submitted data through external servers and may retain it for model training. - Unapproved tools have not been evaluated for compliance with our data protection policies or regulatory obligations. - We want to enable productive AI use through approved, evaluated tools — not eliminate AI usage entirely. What you should do: 1. Review the approved AI tools list at [internal wiki URL]. 2. If you currently use an AI tool not on the list, check whether an approved alternative is available. 3. If no alternative exists, submit an exception request. 4. Questions? Contact the IT Help Desk or attend the Q&A session on [date] at [time]. We are committed to enabling AI-powered productivity while protecting our data, our customers, and our company. — [CISO Name]
Track these five key metrics throughout the rollout to gauge effectiveness and organizational health.
The REST API integrates directly into firewalls, proxies, SOAR playbooks, and custom workflows. Below are the two most common integration patterns for security operations teams.
#!/usr/bin/env python3 """Enterprise AI tool lookup — download once, classify locally.""" import requests import csv import io API_BASE = "https://www.aitoolsblocklist.com/api/database/" API_KEY = "your-enterprise-api-key" def load_database() -> dict: """Download the full database CSV (domain,category,subcategory) and index it by domain for O(1) lookups.""" resp = requests.get( API_BASE, params={"action": "download_database"}, headers={"X-API-Key": API_KEY}, timeout=120 ) resp.raise_for_status() return {row["domain"]: row for row in csv.DictReader(io.StringIO(resp.text))} DB = load_database() # refresh daily; database updates daily def check_domain(domain: str) -> dict: """Check a single domain against the local copy.""" return DB.get(domain) def bulk_check(domains: list) -> list: """Check any number of domains with no additional API calls. Use for daily proxy log analysis or SOAR enrichment.""" return [DB[d] for d in domains if d in DB] # Single domain lookup result = check_domain("chatgpt.com") if result: print(f"MATCH: {result['domain']}") print(f" Category: {result['category']}") print(f" Subcategory: {result['subcategory']}") # Bulk check — feed proxy log domains for classification proxy_domains = ["claude.ai", "midjourney.com", "github.com", "deepseek.com", "perplexity.ai", "notion.so"] ai_tools = bulk_check(proxy_domains) print(f"\n{len(ai_tools)} of {len(proxy_domains)} domains are AI tools") for tool in ai_tools: print(f" {tool['domain']:25s} {tool['category']:25s} {tool['subcategory']}")
For firewall-native EDL integration, download the pre-formatted EDL export from your account downloads page, or use a scheduled job like the one below to extract a plain-text domain list from the API CSV and host it internally for your firewall to poll.
#!/bin/bash # /etc/cron.daily/update-ai-blocklist.sh # Download and validate the AI tools blocklist for local firewall consumption API_KEY="your-enterprise-api-key" FEED_URL="https://www.aitoolsblocklist.com/api/database/?action=download_database" DEST="/etc/blocklists/ai-tools-all.txt" TMP="/etc/blocklists/.ai-tools-tmp.txt" LOG="/var/log/ai-blocklist-update.log" # Full blocklist — all 18 categories; extract the domain column from the CSV curl -sf -H "X-API-Key: $API_KEY" "$FEED_URL" \ | tail -n +2 | cut -d, -f1 > "$TMP" LINES=$(wc -l < "$TMP" 2>/dev/null || echo 0) if [ "$LINES" -gt 1000 ]; then mv "$TMP" "$DEST" echo "$(date -Is) OK: updated $DEST ($LINES domains)" >> "$LOG" # Reload the firewall/proxy so it picks up the new list systemctl reload your-proxy-service 2>/dev/null || true else rm -f "$TMP" echo "$(date -Is) FAIL: download too small ($LINES lines), kept previous" >> "$LOG" fi # Optional: category-filtered list — filter the CSV client-side curl -sf -H "X-API-Key: $API_KEY" "$FEED_URL" \ | awk -F, 'NR>1 && ($2=="Conversational & Chatbots" || $2=="Code & Development") {print $1}' \ > "/etc/blocklists/ai-tools-high-risk.txt"
Firewalls, DNS resolvers, proxies, and SIEM correlation all lean on the same continuously refreshed domain intelligence.
Winning executive sponsorship requires framing this as a risk reduction program, not a technology purchase. The business case rests on three pillars: cost of inaction, operational savings, and strategic value.
AI breaches with cross-border fines can exceed $10M. IP incorporated into model training cannot be deleted.
The feed replaces the analyst time otherwise spent manually curating and maintaining AI tool lists.
Transform a blanket prohibition into a governed capability with controlled AI adoption.
Average breach: $4.88M. AI-related breaches with regulatory exposure can exceed $10M. One prevented incident justifies years of subscription.
Manual tracking: 20-40 hours/month. Automated feed: zero curation effort. Redeploy analyst capacity to threat hunting and incident response.
Demonstrate to auditors that AI usage is inventoried, assessed, and controlled. GDPR, CCPA, HIPAA, and SOX audit readiness built in.
A blocking policy without an exception process creates shadow workarounds. A well-designed exception workflow channels legitimate demand through a governed process that maintains visibility.
Self-service portal request with tool domain, business justification, data classification, and expected duration.
Tool is looked up for category, risk level, and vendor metadata. Security analyst reviews and assigns a risk tier via risk assessment.
Approved: 90-day conditional access with DLP monitoring. Denied: documented rationale and alternative tool recommendation.
Bring security, legal/compliance, and business unit representatives together quarterly to evaluate program effectiveness. Review these key indicators:
A blanket block is rarely the right policy. The 18-category taxonomy lets security teams create policies that align with organizational risk tolerance.
Tell us about your environment — number of endpoints, firewall vendor, compliance requirements — and we will set up a trial feed tailored to your organization.
Describe your security infrastructure and we will configure a trial feed for your firewall or proxy.