Enforcement Automation

Why Enforcement Automation Matters

The math is simple: brand threats appear at internet speed and scale. Manual enforcement cannot keep up.

Consider the numbers:

• Approximately 60 domains are registered every second
• The APWG observed over 1 million phishing attacks in Q1 2025
• A single brand may face hundreds or thousands of active threats simultaneously

A human analyst handling enforcement manually can process perhaps 5-15 cases per day — each requiring evidence collection, form completion, submission, and follow-up. At that rate, the backlog grows faster than it can be cleared.

Enforcement automation changes the equation by handling the repetitive, time-consuming steps — while keeping humans in control of the decisions that matter.

How Enforcement Automation Works

1. Evidence Collection

When a threat is detected, the system automatically gathers:

• Screenshots of the infringing content (timestamped)
• WHOIS/RDAP data for the domain registration
• DNS records (A, MX, NS records showing hosting infrastructure)
• Content analysis documenting specific trademark use or brand impersonation

This evidence package is compiled in seconds — a process that takes a human analyst 15-30 minutes per case.

2. Channel Selection

The system determines which enforcement channels are appropriate based on the threat type:

3. Filing

Enforcement requests are submitted through the appropriate channels — often multiple channels simultaneously for maximum speed. This includes:

• Registrar abuse complaint forms
• Hosting provider abuse reporting systems
• Search engine content removal requests
• Payment processor fraud reports

4. Tracking

Each enforcement action is tracked through to resolution:

• Pending — Request submitted, awaiting action
• Actioned — Registrar/host has taken action
• Resolved — Threat is offline or removed
• Escalated — Initial request not actioned, escalating to upstream provider or alternative channel

5. Escalation

If an enforcement request isn't actioned within expected timeframes, the system escalates:

• Resubmitting with additional evidence
• Escalating to other upstream intermediaries
• Flagging for manual review and potential legal action

Manual vs. Semi-Automated vs. Automated Enforcement

The Human-in-the-Loop Principle

Enforcement automation does not mean fully autonomous enforcement. The critical distinction:

Automated: Evidence collection, form filling, filing, tracking, escalation Human-controlled: The decision to enforce

This matters for several reasons:

• Accuracy — Automated detection can produce false positives. A human reviewer confirms the content is actually infringing before enforcement is initiated.
• Proportionality — Not every detected use of a trademark requires enforcement. Legitimate uses (news, review, comparative advertising) should not be targeted.
• Accountability — Wrongful enforcement can have legal consequences. Human review provides a checkpoint.
• Strategic judgment — Some threats warrant legal escalation rather than standard enforcement. Human reviewers can make this call.

The goal is to automate everything that doesn't require judgment, so that human expertise is applied where it matters most — the decision to act.