The Tool Desk
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How to tell whether AI bot traffic is excessive
There is no universal request-rate threshold that makes a crawler excessive. Define the problem in terms of its effect on your site: origin load, bandwidth, error rates, service costs, or repeated access to expensive pages and endpoints.
Use your web-server logs or CDN/WAF analytics to group requests over a consistent time window by path, response status, claimed user agent, source address or network, and burst or concurrency pattern. Look for repeated retrievals of search pages, APIs, large assets, or other resource-intensive URLs. A high count alone does not establish harm; compare it with your capacity and the value of the access.
For visibility, Cloudflare AI Crawl Control reports crawler request counts and trends, including robots.txt violations (Cloudflare: Manage AI crawlers). AWS WAF Bot Control can label detected requests by bot category and name, with labels available for metrics and logs (AWS WAF Bot Control).
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Identify the crawler without trusting its name alone
A user-agent string is supplied in an HTTP request and can be spoofed. AWS specifically warns that bots may misrepresent this header (AWS: How to manage AI Bots with AWS WAF and enhance security). Treat a crawler name as a starting point for investigation, not proof of who made the request.
Cloudflare’s bot reference distinguishes several identities that are easy to collapse into one broad “AI bot” category: OpenAI’s GPTBot, OAI-SearchBot, and ChatGPT-User, and Anthropic’s ClaudeBot, Claude-SearchBot, and Claude-User. It also lists names such as PerplexityBot, Bytespider, CCBot, and Google-CloudVertexBot. Names and classifications can change, so check the live reference when writing or updating rules (Cloudflare: Bot reference).
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Where your CDN or WAF supports it, combine user-agent matching with stronger signals such as managed bot labels, verified-bot status, detection IDs, bot scores, fingerprints, or request behavior. Availability varies by provider and plan. Cloudflare says Bot Management customers can use detection IDs in custom WAF rules; AWS Bot Control’s common inspection level labels self-identifying bots, while its targeted level adds browser interrogation, fingerprinting, behavioral heuristics, and optional machine-learning traffic analysis (AWS WAF Bot Control).
Decide what access you want to allow
Choose the policy before writing a rule. Training crawlers, search or indexing crawlers, and user-initiated assistant fetches can have different purposes, and some providers identify them separately. Decide whether you want to block a specific crawler class, restrict particular paths, or manage all automated access. Keep ordinary search-engine access if you want it, and test the actual edge behavior rather than assuming a robots.txt directive enforces the policy.
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Use robots.txt to communicate with cooperative crawlers
A robots.txt file can ask crawlers that follow the Robots Exclusion Protocol to avoid the whole site or selected paths. Directives can be scoped by user-agent, so a site might allow an AI search crawler to access /public/ while disallowing /private/. AWS also documents Google-Extended and Applebot-Extended directives for expressing model-training preferences in those specific cases while retaining search indexing (AWS guidance on managing AI bots).
These directives are requests, not access controls. Some operators may not honor them, and a scraper can claim a different user agent. Use a WAF or other access-control layer when requests must be stopped rather than merely discouraged.
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Enforce limits at the CDN or WAF
A CDN or web application firewall can evaluate requests before they reach your origin. Depending on the service, you can allow, block, rate-limit, or challenge traffic. AWS WAF Bot Control labels detected requests by bot category and name so custom rules can act on those labels; AWS also recommends rate-based rules for high-volume sources and challenges for evasive scrapers (AWS WAF Bot Control; AWS implementation guidance).
Cloudflare provides managed AI-crawler controls and managed robots.txt. More specific custom rules can combine a URL path with fields such as country, ASN, fingerprint, and user agent. Cloudflare notes that custom rules run before Super Bot Fight Mode rules; a terminating custom action can therefore stop later bot settings from being evaluated. Review the current feature availability for your plan before relying on a particular action (Cloudflare: Custom rules; Cloudflare: Manage AI crawlers).
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Choose the least disruptive action that addresses the impact
- Allow traffic you have verified and want to retain, with exceptions kept narrow.
- Rate-limit an identity or source that is making too many requests, especially when some access remains useful.
- Challenge uncertain or evasive traffic when an outright block could affect legitimate visitors.
- Block a confirmed unwanted crawler or access pattern when a softer control is insufficient.
Roll out the rule carefully and monitor its effects
Start with observation rather than a broad block. Review analytics, logs, detected labels, and likely false positives before enforcing a rule. Cloudflare recommends checking Bot Analytics first and adjusting thresholds gradually; AWS guidance similarly recommends reviewing Bot Control labels and logs to understand detections before switching to blocking (Cloudflare: Challenge bad bots; AWS implementation guidance).
- Observe: identify the paths, request patterns, and sources contributing to the problem.
- Scope: create a rule for the affected path or a well-supported crawler identity instead of blocking all automated traffic.
- Enforce: apply the narrowest suitable action—rate limit, challenge, or block—and preserve exceptions for verified desirable crawlers or authenticated clients where appropriate.
- Review: compare request volume and site impact with the previous baseline, and check whether legitimate users or crawlers are being caught.
- Adjust or roll back: expand the rule only if the scoped policy works; loosen or remove it if collateral effects outweigh the benefit.
Set rate limits using your own request patterns, capacity, and cost data. The cited provider guidance does not establish a universally safe requests-per-minute threshold.
Compare options against your infrastructure
| What to compare | Questions to ask |
|---|---|
| Existing infrastructure | Does the site already use the provider’s CDN, WAF, or cloud services? |
| Identification depth | Are rules based only on user agents, or can they use managed labels, verification, fingerprints, behavior, or bot scores? |
| Enforcement | Can the service allow, block, rate-limit, or challenge requests? |
| Scope and exceptions | Can a rule target specific paths and combine request fields, or does it apply across the domain? |
| Visibility | Can you inspect request counts, labels, logs, trends, and robots.txt violations? |
| False-positive controls | Are verified-bot exceptions, observation workflows, and straightforward rollback available? |
| Plan and cost | Is the feature included in your plan, plan-limited, or subject to additional usage fees? |
AWS states that Bot Control carries additional fees. Cloudflare documents plan or subscription requirements for some bot scores, verified-bot features, and custom bot-management fields, while some managed AI-crawler features are listed for all plans. Confirm current terms and availability with each provider before implementation (AWS WAF Bot Control; Cloudflare: Custom rules).
When signed identity can help with legitimate assistant traffic
OpenAI documents Web Bot Auth for requests from the ChatGPT Work Cloud browser. Those requests include HTTP Message Signatures and a Signature-Agent value; site operators can validate them using published public keys. OpenAI provides recognition or allowlisting guidance for Cloudflare, Akamai, and HUMAN (OpenAI: ChatGPT Work’s Cloud browser allowlisting).
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This verification applies to the documented ChatGPT Work Cloud browser requests; it is not a general method for authenticating every AI crawler or assistant request.
Quick Recap
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