CCBot

What is CCBot?

CCBot is a Nutch-based web crawler operated by Common Crawl, a non-profit foundation dedicated to democratizing access to web information. The crawler systematically visits websites across the internet to collect and archive web content, making it universally accessible for research, analysis, and AI training purposes. CCBot is classified as an AI data scraper, which means it downloads website content specifically for inclusion in datasets used to train large language models and other machine learning systems. Unlike traditional search engine crawlers that index content for retrieval, CCBot focuses on comprehensive data collection for machine learning applications. The crawler operates transparently with dedicated IP address ranges and reverse DNS verification, allowing webmasters to authenticate legitimate CCBot requests. Common Crawl’s mission is to promote an inclusive knowledge ecosystem where organizations, academia, and non-profits can collaborate using open data to address complex global challenges.

How CCBot Works & Technical Details

CCBot leverages the Apache Hadoop project and Map-Reduce processing to efficiently handle the massive scale of web crawling operations, processing and extracting crawl candidates from billions of web pages. The crawler stores its collected data in three primary formats, each serving distinct purposes in the data pipeline. The WARC format (Web ARChive) contains the raw crawl data with complete HTTP responses, request information, and crawl metadata, providing a direct mapping to the crawl process. The WAT format (Web Archive Transformation) stores computed metadata about the records in WARC files, including HTTP headers and extracted links in JSON format. The WET format (WARC Encapsulated Text) contains extracted plaintext from the crawled content, making it ideal for tasks requiring only textual information. These three formats allow researchers and developers to access Common Crawl data at different levels of granularity, from raw responses to processed metadata to plain text extraction.

CCBot’s Role in AI Training

CCBot plays a critical role in powering modern artificial intelligence systems, as Common Crawl data is extensively used to train large language models (LLMs) including those developed by OpenAI, Google, and other leading AI organizations. The Common Crawl dataset represents a massive, publicly available repository containing billions of web pages, making it one of the most comprehensive training datasets available for machine learning research. According to recent industry data, training crawling now drives nearly 80% of AI bot activity, up from 72% a year ago, demonstrating the explosive growth in AI model development. The dataset is freely accessible to researchers, organizations, and non-profits, democratizing access to the data infrastructure needed for cutting-edge AI research. Common Crawl’s open approach has accelerated progress in natural language processing, machine translation, and other AI domains by enabling collaborative research across institutions. The availability of this data has been instrumental in developing AI systems that power search engines, chatbots, and other intelligent applications used by millions globally.

Blocking CCBot & robots.txt

Website owners who wish to prevent CCBot from crawling their content can implement blocking rules through the robots.txt file, a standard mechanism for communicating crawler directives to web robots. The robots.txt file is placed in the root directory of a website and contains instructions that specify which user agents are allowed or disallowed from accessing specific paths. To block CCBot specifically, webmasters can add a simple rule that disallows the CCBot user agent from crawling any part of their site. Common Crawl has also implemented dedicated IP address ranges with reverse DNS verification, allowing webmasters to authenticate whether a request genuinely originates from CCBot or from a bad actor falsely identifying themselves as CCBot. This verification capability is important because some malicious crawlers attempt to spoof the CCBot user agent string to bypass security measures. Webmasters can verify authentic CCBot requests by performing reverse DNS lookups on the IP address, which should resolve to a domain in the crawl.commoncrawl.org namespace.

User-agent: CCBot
Disallow: /

Advantages & Disadvantages

CCBot and the Common Crawl dataset offer significant advantages for researchers, developers, and organizations working with large-scale web data, but also present considerations regarding content usage and attribution. The open and freely accessible nature of Common Crawl data has democratized AI research, enabling smaller organizations and academic institutions to develop sophisticated machine learning models that would otherwise require prohibitive infrastructure investments. However, content creators and publishers have raised concerns about how their work is used in AI training datasets without explicit consent or compensation.

Advantages:

• Free and open access to billions of web pages for research and AI development
• Enables democratized AI research across organizations of all sizes
• Comprehensive dataset with multiple format options (WARC, WET, WAT)
• Transparent operation with verifiable IP ranges and reverse DNS
• Supports reproducible research and collaborative development

Disadvantages:

• Content creators may not receive attribution or compensation for their work
• Limited transparency about how collected data is used in AI systems
• Potential concerns about copyright and intellectual property rights
• Aggressive crawling patterns may impact website performance
• Difficulty in opting out retroactively from already-collected data

CCBot vs Other AI Crawlers

While CCBot is one of the most prominent AI data scrapers, it operates alongside other notable crawlers including GPTBot (operated by OpenAI) and Perplexity Bot (operated by Perplexity AI), each with distinct purposes and characteristics. GPTBot is specifically designed to collect training data for OpenAI’s language models and can be blocked through robots.txt directives, similar to CCBot. Perplexity Bot crawls the web to gather information for Perplexity’s AI-powered search engine, which provides cited sources alongside AI-generated responses. Unlike search engine crawlers such as Googlebot that focus on indexing for retrieval, all three of these AI data scrapers prioritize comprehensive content collection for model training. The key distinction between CCBot and proprietary crawlers like GPTBot is that Common Crawl operates as a non-profit foundation providing open data, while OpenAI and Perplexity operate proprietary systems. Website owners can block any of these crawlers individually through robots.txt, though the effectiveness depends on whether the operators respect the directives. The proliferation of AI data scrapers has led to increased interest in tools like Dark Visitors and AmICited.com that help website owners monitor and manage crawler access.

Monitoring & Detection

Website owners can monitor CCBot and other AI crawler activity using specialized tools designed to provide visibility into bot traffic and AI agent access patterns. Dark Visitors is a comprehensive platform that tracks hundreds of AI agents, crawlers, and scrapers, allowing website owners to see which bots are visiting their sites and how frequently. The platform provides real-time analytics on CCBot visits, along with insights into other AI data scrapers and their crawling patterns, helping webmasters make informed decisions about blocking or allowing specific agents. AmICited.com is another resource that helps content creators understand whether their work has been included in AI training datasets and how it might be used in generated outputs. These monitoring tools are particularly valuable because they authenticate bot visits, helping distinguish between legitimate CCBot requests and spoofed requests from bad actors attempting to bypass security measures. By setting up agent analytics through these platforms, website owners gain visibility into their hidden bot traffic and can track trends in AI crawler activity over time. The combination of monitoring tools and robots.txt configuration provides webmasters with comprehensive control over how their content is accessed by AI training systems.

Best Practices & Recommendations

Website owners should implement a comprehensive strategy for managing CCBot and other AI crawler access, balancing the benefits of contributing to open research with concerns about content usage and attribution. First, review your website’s purpose and content to determine whether participation in Common Crawl aligns with your organizational goals and values. Second, if you decide to block CCBot, implement the appropriate robots.txt rules and verify that the directives are being respected by monitoring crawler activity through tools like Dark Visitors. Third, consider implementing Robots.txt Categories that automatically update as new AI agents are discovered, rather than manually maintaining individual rules for each crawler. Fourth, authenticate CCBot requests using reverse DNS verification to ensure that crawlers claiming to be CCBot are actually legitimate, protecting against spoofed user agents. Fifth, monitor your website’s traffic patterns to understand the impact of AI crawlers on your server resources and adjust your blocking strategy accordingly. Sixth, stay informed about developments in AI crawler transparency and attribution standards, as the industry continues to evolve toward better practices for content creator compensation and recognition. Finally, consider engaging with the broader community through Common Crawl’s mailing list and Discord to contribute feedback and participate in discussions about responsible web crawling practices.