When AI Crawlers Behave Like a DDoS: How Content Owners Can Protect Their Websites

In January 2025, TechCrunch reported on an incident in which automated crawling activity associated with an AI model overwhelmed a small company’s website, effectively rendering it unusable for extended periods. While the activity was not a traditional distributed denial-of-service (DDoS) attack, the volume, frequency, and persistence of requests had a similar operational impact.

The incident highlights a growing issue for content owners and licensors: AI scraping at scale can create real technical and legal risk, even when the intent is data collection rather than disruption.

AI Crawlers and DDoS-Like Behavior

Modern AI crawlers are designed to collect large volumes of data efficiently. When improperly throttled or insufficiently constrained, that activity can resemble malicious traffic patterns:

• sustained high request rates

• repeated access to content-heavy pages

• strain on infrastructure not designed for constant automated access

For small or mid-sized websites, especially those hosting proprietary or licensed content, this can lead to downtime, degraded performance, or service outages.

Why Robots.txt Alone Is Not Sufficient

Many site operators assume that configuring a robots.txt file is enough to control scraping. While robots.txt directives are an important first step, they rely on voluntary compliance.

Some AI providers publicly state that their crawlers honor robots.txt instructions. Others may not, or may operate through multiple user agents or infrastructure layers that complicate enforcement.

As a result, content owners should treat robots.txt as one layer in a broader defense strategy, not a complete solution.

Practical Steps to Limit AI Scraping Risk

Based on common patterns seen across recent incidents, content owners should consider the following safeguards.

1. Explicitly Block Known AI Crawlers in Robots.txt

Website operators can configure robots.txt to deny access to known AI crawler user agents, including:

• GPTBot

• ChatGPT-User

• OAI-SearchBot

• crawlers associated with other AI services

Providers such as OpenAI, Anthropic, and Perplexity publish documentation describing their crawler behavior and user agents. Those references should be reviewed regularly, as crawler names and practices can change.

2. Deploy Firewall and Traffic-Filtering Services

Infrastructure tools such as Cloudflare or similar web application firewalls can help:

• identify known scraping IP ranges

• detect abnormal request patterns

• block traffic from data centers commonly used for large-scale scraping

This layer is particularly important when crawler behavior exceeds what robots.txt was designed to manage.

3. Enforce Request Rate Limits

Rate limiting helps prevent excessive automated access by restricting how frequently a single client or IP can request resources.v Without rate limits, even “legitimate” crawlers can unintentionally overwhelm systems designed for human traffic patterns.

4. Use CAPTCHAs and Bot Detection on High-Value Pages

CAPTCHAs and bot-detection mechanisms can help distinguish human users from automated requests, particularly for:

• content-heavy pages

• licensed or proprietary materials

• endpoints frequently targeted by scrapers

While not appropriate for every page, selective deployment can materially reduce risk.

The Broader Issue: AI Training vs. Content Ownership

The TechCrunch report underscores a broader tension emerging across the technology ecosystem. AI developers require large data sets. Content owners rely on controlled access, licensing, and infrastructure stability.

As AI scraping becomes more aggressive and automated, technical controls, contractual protections, and operational safeguards are increasingly intertwined. Companies that host valuable content can no longer assume that “passive” publication is risk-free.

Key Takeaway for Content Owners

AI scraping is not inherently malicious, but at scale, it can create real operational harm.

Companies that host proprietary, licensed, or high-value content should proactively evaluate:

• how AI crawlers interact with their websites

• whether existing controls are sufficient

• how scraping activity could affect uptime, performance, and contractual obligations

Waiting until an incident occurs often means discovering vulnerabilities only after damage is done.

The information provided is for educational purposes only and does not constitute legal advice. Reading this article does not establish an attorney-client relationship.