AI Bots Are Visiting Your Website: How to Identify GPTBot, PerplexityBot, and Claude-SearchBot

AI Bots Are Already On Your Site—You Just Can’t See Them

AI bot traffic grew 1,300% in the first half of 2025 according to Human Security, and over 50% of all internet traffic is now non-human according to Barracuda research. Yet most website owners have no visibility into which AI bots visit their sites, how often they crawl, or what content they consume. Your Google Analytics doesn’t show it. Your server logs bury it. And your marketing metrics are contaminated by it.

This technical guide identifies every major AI bot currently crawling the web, shows you exactly how to detect each one, and provides actionable controls for managing AI bot access to your content. Whether you’re a developer implementing detection, a marketer trying to clean your analytics, or a business leader preparing for the agentic commerce era, identifying AI bots is the essential first step.

The Major AI Bots: Complete Reference

OpenAI: GPTBot and ChatGPT-User

OpenAI operates two primary crawlers with distinct purposes:

Key distinction: blocking GPTBot prevents your content from being used in model training. Blocking ChatGPT-User prevents ChatGPT’s browsing feature from accessing your pages when users ask about your content. Most businesses want to allow ChatGPT-User (visibility) while considering whether to allow GPTBot (training).

Anthropic: ClaudeBot and Claude-SearchBot

Anthropic operates separate bots for different functions:

Perplexity: PerplexityBot

Google: Google-Extended and Googlebot

Google’s AI crawling is complicated by its dual-purpose infrastructure:

This is a critical nuance: Google’s AI Overviews feature uses Googlebot-indexed content, not Google-Extended. Blocking Google-Extended only prevents your content from being used in Gemini model training—it does not prevent Google from summarizing your content in AI-generated search results.

Other Notable AI Bots

How to Detect AI Bots: Three Methods

Method 1: User Agent String Detection

The simplest detection method—check the user agent string against known AI bot signatures. This works for bots that properly identify themselves, which includes all major AI company crawlers:

# Nginx: Log AI bot visits separately
map $http_user_agent $is_ai_bot {
    default 0;
    ~*GPTBot 1;
    ~*ChatGPT-User 1;
    ~*ClaudeBot 1;
    ~*Claude-SearchBot 1;
    ~*PerplexityBot 1;
    ~*Google-Extended 1;
    ~*Bytespider 1;
    ~*CCBot 1;
    ~*Meta-ExternalAgent 1;
    ~*cohere-ai 1;
    ~*Diffbot 1;
    ~*Amazonbot 1;
}

Limitation: User agents can be spoofed. Malicious bots routinely impersonate legitimate crawlers. User agent detection is a first-pass filter, not a definitive verification method.

Method 2: IP Range Verification

Cross-reference visitor IPs against the published IP ranges of known AI services. This is more reliable than user agent detection because IP ranges are harder to spoof (though not impossible with proxies).

Major AI companies publish their crawler IP ranges:

• OpenAI — Published JSON feed of GPTBot and ChatGPT-User IP ranges
• Anthropic — Published IP ranges for ClaudeBot and Claude-SearchBot
• Google — Published via googlebot.json and special-crawlers.json
• Perplexity — Published IP range list

Best practice: combine user agent detection with IP verification. A request claiming to be GPTBot but originating from outside OpenAI’s published IP ranges is likely a spoofed bot and should be treated as suspicious.

Method 3: Behavioral Analysis

Some AI agents don’t identify themselves honestly—or are new enough that their signatures aren’t in your detection lists. Behavioral analysis catches these by examining interaction patterns:

• Request timing — AI bots typically maintain consistent intervals between requests, unlike humans who show irregular browsing patterns
• Navigation paths — Systematic page traversal (alphabetical, sitemap-ordered, or breadth-first) vs. human navigation which follows interest and context
• Session characteristics — No cookie persistence, no JavaScript execution (for simple crawlers), missing browser APIs
• Content consumption — Full page downloads without asset loading (CSS, images, fonts) indicate non-browser HTTP clients
• TLS fingerprint — JA3/JA4 fingerprints from automated HTTP libraries (Python requests, Go net/http, Node.js fetch) differ from genuine browser TLS handshakes

QAIL AI’s AI bot traffic detection combines all three methods—user agent matching, IP verification, and behavioral analysis—to identify both known and unknown AI visitors with high accuracy.

Controlling AI Bot Access: robots.txt Configuration

The primary mechanism for controlling AI bot crawling is your robots.txt file. Here are common configurations:

Allow All AI Bots (Maximum Visibility)

# Allow all AI bots to crawl everything
User-agent: GPTBot
Allow: /

User-agent: ChatGPT-User
Allow: /

User-agent: ClaudeBot
Allow: /

User-agent: Claude-SearchBot
Allow: /

User-agent: PerplexityBot
Allow: /

User-agent: Google-Extended
Allow: /

Block Training, Allow Search (Balanced)

# Block training crawlers
User-agent: GPTBot
Disallow: /

User-agent: ClaudeBot
Disallow: /

User-agent: Google-Extended
Disallow: /

User-agent: CCBot
Disallow: /

User-agent: Bytespider
Disallow: /

# Allow search/retrieval bots (visibility in AI answers)
User-agent: ChatGPT-User
Allow: /

User-agent: Claude-SearchBot
Allow: /

User-agent: PerplexityBot
Allow: /

Selective Access (Protect Premium Content)

# Allow AI bots on public content
User-agent: GPTBot
Allow: /blog/
Allow: /solutions/
Disallow: /members/
Disallow: /api/
Disallow: /pricing/

User-agent: PerplexityBot
Allow: /blog/
Allow: /solutions/
Disallow: /members/
Disallow: /api/
Disallow: /pricing/

Important limitation: robots.txt is advisory, not enforceable. Well-behaved bots respect it; malicious bots ignore it. For enforcement, you need server-side blocking via IP ranges and user agent filtering in your web server configuration or WAF rules.

Beyond Detection: The Strategic Decision

Identifying AI bots is step one. The strategic question is what to do with them. Most businesses default to blocking—but that’s increasingly the wrong answer.

The Case for Engaging AI Bots

GEO (Generative Engine Optimization) research shows that websites with authoritative, well-structured content achieve 89.1% higher visibility in AI-generated responses and 65.5% more citations when they include verifiable statistics. Blocking AI crawlers means opting out of this visibility entirely.

As AI-powered search (Perplexity, ChatGPT with browsing, Google AI Overviews, Claude with web search) captures a growing share of information queries, being visible to AI systems is becoming as important as ranking in traditional search. The Know Your Agent framework provides a more nuanced approach: identify each bot, classify its intent, and serve appropriate content accordingly.

What to Serve AI Bots

Rather than a binary allow/block decision, consider what content different AI bots should see:

• Search/retrieval bots (ChatGPT-User, Claude-SearchBot, PerplexityBot) — Serve full content with rich structured data. These bots drive visibility in AI-powered answers.
• Training crawlers (GPTBot, ClaudeBot, Google-Extended) — Business decision. Allowing training contributes to AI model quality and may improve how AI systems understand your brand. Blocking protects content exclusivity.
• AI purchasing agents — Serve structured product data, pricing, and availability via MCP endpoints. These are the agents driving the $3-5 trillion agentic commerce opportunity.
• Unknown/suspicious bots — Serve limited content or challenge with verification. Don’t block outright—they might be legitimate agents you haven’t identified yet.

Implementation Checklist

1. Audit current AI bot traffic — Check server logs for known AI bot user agents. Estimate what percentage of your traffic is AI-driven.
2. Configure robots.txt — Set explicit rules for each major AI bot based on your content strategy.
3. Implement server-side detection — Add user agent and IP range checking to your web server or application layer.
4. Set up AI traffic analytics — Segment AI bot visits in your analytics to measure volume, frequency, and content consumption patterns.
5. Publish an AI crawler policy — Establish and communicate your rules for AI agent access. See our AI crawler policy template.
6. Deploy comprehensive detection — QAIL AI’s bot detection combines user agent, IP, behavioral, and fingerprint analysis for complete AI visitor identification.
7. Plan for agent engagement — As AI purchasing agents become more common, prepare structured data and MCP endpoints to serve them.

Frequently Asked Questions

Can AI bots bypass robots.txt?

Technically yes—robots.txt is a voluntary standard. All major AI company bots (GPTBot, ClaudeBot, PerplexityBot) respect robots.txt, but smaller or malicious bots may not. For enforcement, use server-side IP blocking and user agent filtering in addition to robots.txt.

Will blocking AI bots affect my Google search rankings?

Blocking Google-Extended does not affect your search rankings—it only prevents use in Gemini model training. However, blocking Googlebot will remove you from Google search entirely. The two are separate systems with separate robots.txt tokens.

How often do AI bots crawl my site?

Crawl frequency varies by bot and site authority. High-traffic sites may see GPTBot daily, while smaller sites might see weekly visits. Real-time retrieval bots (ChatGPT-User, PerplexityBot) visit on-demand when users query about your content. QAIL AI’s traffic analytics show exact crawl frequencies for each AI bot.

Do AI bots consume significant bandwidth?

For most sites, AI bot bandwidth is manageable. However, aggressive crawlers (especially Bytespider and some lesser-known bots) can generate significant load. If you notice performance impacts, implement rate limiting per bot rather than outright blocking. Set crawl-delay in robots.txt as a starting measure.

Should I serve different content to AI bots?

Serving completely different content (cloaking) violates Google’s guidelines and is not recommended. However, serving supplementary structured data, schema markup, and machine-readable formats alongside your human-readable content is good practice and improves how AI systems understand your business.

How do I detect AI bots that don’t identify themselves?

Use behavioral analysis and browser fingerprinting. Bots that spoof their user agent still leave fingerprints: TLS handshake characteristics, missing browser APIs, automated navigation patterns, and data center IP origins. QAIL AI’s detection catches these through multi-signal analysis.

Want to see exactly which AI bots visit your website? Get a free AI traffic audit from QAIL AI, or explore the platform to see real-time AI visitor identification in action.