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Bingbot

Bingbot is the primary operated by for its , responsible for systematically discovering, fetching, and indexing web pages to build and update 's searchable index. Launched on October 1, 2010, it replaced the earlier MSNBot crawler, with no changes to crawling behavior, IP addresses, or rate limits, but introduced a new string: Mozilla/5.0 (compatible; bingbot/2.0; +http://www.bing.com/bingbot.htm), which was updated in 2022 to include Chromium-based identifiers mimicking modern browsers like . This bot adheres to standard web crawling protocols, such as respecting directives, and supports variants for and crawling to ensure comprehensive coverage of . As Bingbot traverses the , it sends discovered back to 's servers, where algorithms analyze and rank the for relevance in search results, powering not only but also integrated services like through the ongoing Microsoft-Yahoo alliance (as of 2025).

History

Origins and Predecessors

's early forays into web search began in the late 1990s with the launch of MSN Search as part of the Microsoft Network () portal, initially relying on human-curated directories and licensed indexing from third-party providers like Inktomi rather than a proprietary crawler. These initial efforts focused on integrating search functionality into the ecosystem, but as the expanded rapidly, recognized the need for independent crawling technology to compete effectively. By the early 2000s, 's search infrastructure evolved from rudimentary link-following bots—simple scripts that traversed hyperlinks to catalog pages—to more sophisticated systems capable of handling larger-scale and basic . This progression reflected broader industry trends toward automated, engines, positioning to transition away from external dependencies. The primary predecessor to Bingbot was MSNBot, introduced in 2004 as the for the beta version of a revamped Search engine and achieving full public release in 2005. MSNBot systematically collected and indexed web documents to power Search, which was rebranded as Search in 2006, continuing its role in constructing 's proprietary search indexes until its phase-out in 2010. It identified itself via user agent strings such as "msnbot/1.0 (+http://search.[msn](/page/MSN).com/msnbot.htm)", signaling its origin to web servers. This foundational work with MSNBot directly informed the development of subsequent crawlers, culminating in Bing's 2009 launch as a comprehensive of Live Search.

Introduction and Evolution

is the primary developed by to discover, collect, and for the . Launched on October 1, 2010, it replaced the predecessor MSNBot to align with the of 's search service as , which had debuted in June 2009. Initially designed to systematically gather documents from across the web to build and maintain 's searchable , incorporated refinements from prior crawlers, including better adherence to directives for more respectful site interactions. Over the years, Bingbot has undergone several key evolutions to adapt to the changing web landscape. In , introduced specialized preview crawlers such as BingPreview, which focused on rendering pages to generate visual snippets and thumbnails for search results, enhancing without overburdening primary crawling resources. By late , Bingbot expanded to include dedicated variants, enabling targeted crawling of mobile-optimized or responsive sites to better support the growing prevalence of mobile search traffic. Further advancements came in 2018 with optimizations to crawl frequency, where algorithms were refined to dynamically adjust visit rates based on site update patterns, reducing unnecessary requests and server load while ensuring timely indexing of fresh content. In the late and into the , Bingbot integrated the rendering engine based on (), significantly improving its ability to process and index JavaScript-heavy dynamic content that earlier versions handled less effectively. As part of this adoption, Microsoft transitioned Bingbot to new user agents matching those of , starting in April 2022 and fully implementing the change by January 2023 to enhance compatibility and simplify identification for site owners. These updates reflect Microsoft's ongoing commitment to efficient, standards-compliant crawling amid evolving web technologies.

Technical Specifications

User Agents and Identification Strings

Bingbot identifies itself to web servers primarily through the string Mozilla/5.0 (compatible; bingbot/2.0; +http://www.bing.com/bingbot.htm). This string signals that the request originates from Microsoft's crawler and includes a URL linking to official documentation on the bot's behavior and verification methods. The format adheres to standard HTTP protocol conventions, allowing site administrators to distinguish legitimate Bingbot traffic from potential imposters via server logs. To enhance compatibility with modern websites that rely on browser-specific rendering, Bingbot employs variant user agent strings that emulate popular browsers. For desktop crawling, it uses strings such as Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko; compatible; bingbot/2.0; +http://www.bing.com/bingbot.htm) Chrome/W.X.Y.Z Safari/537.36, where W.X.Y.Z is dynamically updated to match the latest stable version of Microsoft Edge (for example, 80.0.345.0). Mobile variants simulate Android devices, like Mozilla/5.0 (Linux; Android 6.0.1; Nexus 5X Build/MMB29P) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/W.X.Y.Z Mobile Safari/537.36 (compatible; bingbot/2.0; +http://www.bing.com/bingbot.htm), again substituting the current Edge version for W.X.Y.Z. These emulations ensure Bingbot can access content gated behind user agent detection, such as JavaScript-rendered pages, while maintaining transparency about its crawler identity. The evolution of Bingbot's user agent strings began with a basic format upon its deployment in , using the simple bingbot/2.0 identifier to announce its presence. Over time, updated these strings to incorporate "evergreen" browser emulation, starting with announcements in late 2019 to reflect dynamic versions and improve rendering fidelity. A further transition in 2022 phased out the standalone historical string in favor of the detailed variants, aiming for better alignment with web standards and reduced blocking by sites enforcing strict checks. This progression supports Bingbot's core purpose of compliant crawling while providing a verifiable link to 's guidelines, which webmasters can use in basic detection and optional IP verification processes.

Crawling Capabilities

Bingbot employs a headless version of the browser as its rendering engine to execute and render dynamic web pages, enabling it to process modern, interactive content that relies on client-side scripting. This implementation is regularly updated to the latest stable version of , such as version 80 and beyond during the , ensuring compatibility with evolving web standards and improved performance in handling complex layouts and animations. In terms of resource handling, Bingbot primarily focuses on text extraction for indexing purposes but supports the crawling of elements like images and videos through its core operations and specialized sub-crawlers. For instance, serves as a dedicated crawler for , scanning content and linked websites to ensure , while BingVideoPreview handles video previews by fetching and processing video resources. Bingbot respects directives to manage access to these resources, allowing site owners to control crawling . Bingbot operates at a massive scale, distributed across Microsoft's global data centers to billions of URLs daily while optimizing for efficiency and minimal site impact. Its algorithms prioritize fresh content by assessing update frequency, site activity, and preferences, directing more frequent crawls to pages with recent changes to maintain an up-to-date . During the extraction process, Bingbot parses HTML using standards like HTML5 to identify structured elements such as headings, lists, and tables, even applying machine learning to segment page blocks when markup is suboptimal. It follows hyperlinks discovered on pages and prioritizes those from sitemaps and RSS feeds, extracting key metadata including titles from <title> tags, descriptions from meta elements, and other annotations like image alt text. For multilingual content, Bingbot leverages hreflang attributes in HTML or sitemaps to recognize and appropriately index alternate language versions of pages.

Identification and Verification

Detection Methods

Detection of Bingbot activity typically begins with analyzing server access logs to identify requests matching the bot's strings, such as "Mozilla/5.0 (compatible; bot/2.0; +http://www.bing.com/bingbot.htm)" or updated variants including compatibility indicators like "Mozilla/5.0 AppleWebKit/537.36 (, like ; compatible; bot/2.0; +http://www.bing.com/bingbot.htm)".[](https://www.bing.com/webmasters/help/which-crawlers-does-bing-use-8c184ec0)[](https://blogs.bing.com/webmaster/april-2022/Announcing-user-agent-change-for-Bing-crawler-bingbot) In these logs, patterns emerge such as sequential requests following links from submitted or internal site structures, indicating systematic discovery rather than random browsing. IP address patterns provide another layer of detection, as Bingbot originates from Microsoft-owned autonomous system number AS8075, with specific ranges listed in Microsoft's official file, including examples like 157.55.39.0/24, 207.46.13.0/24, and 40.77.167.0/24. These requests often involve high volumes from concentrated subnets, differing from typical user traffic distribution. Behavioral indicators in logs further distinguish Bingbot, characterized by rapid, automated requests without user-like interactions such as usage or session persistence, typically over direct HTTP or connections. The bot prioritizes indexable public pages, avoiding protected areas like login pages, and exhibits methodical progression through site hierarchies to extract content efficiently. For monitoring, server-side logging tools like or GoAccess can parse access logs to filter and visualize Bingbot traffic, while integrations with analytics platforms such as allow bot traffic segmentation through and -based rules, enabling pattern tracking without affecting human visitor data.

Verification Processes

To verify that incoming traffic claiming to be Bingbot originates from 's legitimate crawler, website administrators can employ several official methods provided by . These processes focus on cross-referencing IP addresses and hostnames to distinguish authentic Bingbot requests from potential impersonations. One primary verification step involves performing a on the suspect from logs. Legitimate Bingbot resolve to hostnames ending in "search..com", such as "msnbot-157-55-33-18.search..com". This format confirms affiliation with Microsoft's search . Following the reverse lookup, a forward DNS lookup on the resulting should resolve back to the original , ensuring consistency and preventing spoofing attempts. Microsoft also maintains a publicly accessible of known Bingbot IP addresses and ranges, available for download in format from . This includes approximately 28 specific CIDR prefixes such as 157.55.39.0/24, 207.46.13.0/24, and 40.77.167.0/24, associated with 's autonomous AS8075. Administrators are advised to compare log IPs against this regularly updated file, which should be refreshed daily to account for changes in Microsoft's infrastructure. For real-time validation, offers an online at https://www.bing.com/toolbox/verify-bingbot. Users input an into this web-based interface, which checks it against Microsoft's current database of addresses and provides an immediate of legitimacy. This is particularly useful for quick assessments without manual DNS queries. In addition to DNS checks, forward DNS (as noted above) and validation of the string—such as "Mozilla/5.0 (compatible; /2.0; +http://www.bing.com/bingbot.htm)"—are recommended, especially for high-security environments. These combined measures provide robust assurance that the crawler is genuine, complementing initial detection via user agents in access logs.

Crawling Behavior

Discovery and Indexing Process

Bingbot's discovery phase begins with a set of seed URLs, which serve as starting points for exploration, and primarily relies on following hyperlinks from already known pages to identify new content across the web. This process is augmented by submissions from webmasters, including sitemaps that list important URLs and RSS or Atom feeds that signal updates to dynamic content, enabling more efficient detection of fresh material. This process is further enhanced by protocols like IndexNow, enabling publishers to notify Bing of content changes in real-time for immediate crawling. Algorithms then prioritize discovery based on factors such as predicted freshness, relevance to user queries, and the quality of inbound links, allowing Bingbot to process billions of potential URLs daily while focusing on high-value additions to the index. In the crawling phase, once URLs are discovered, Bingbot sends HTTP requests to fetch the corresponding web pages, downloading their and associated resources in a manner designed to minimize load. budgets are dynamically allocated based on site-specific factors, including size, historical update frequency, and response times, ensuring that larger or more frequently updated sites receive appropriate attention without overwhelming resources. This polite crawling approach adjusts request rates iteratively, using signals like download times and connection errors to optimize efficiency and respect site performance limits. Following retrieval, the extraction and processing stage involves parsing the downloaded to identify and isolate core content, employing models to segment pages into meaningful blocks such as main text, headers, and while filtering out boilerplate like footers or ads. Duplicates are detected and deduplicated early, with only the most authoritative version retained based on signals or redirect patterns, and structured data marked up with schema.org is extracted to enrich understanding of entities like products or events. For dynamic content generated via , Bingbot employs a to render pages, ensuring comprehensive capture of client-side modifications. Finally, during indexing, the processed content is incorporated into Bing's search along with associated , such as extracted keywords, annotations, and freshness timestamps, to facilitate quick retrieval and ranking for queries. Re-crawling is scheduled algorithmically to detect changes, with high-priority sites—those showing frequent updates or high user engagement—typically revisited daily to maintain accuracy and timeliness. This closed-loop workflow ensures the remains comprehensive and current, balancing scale with .

Compliance with Web Standards

Bingbot fully respects the protocol by parsing the file located at the root of each , such as http://www.[example.com](/page/Example.com)/robots.txt, and applying directives without falling back to other hosts if the file is absent. It honors specific sections for User-agent: Bingbot or the legacy msnbot, prioritizing them over the wildcard User-agent: * for general rules, and supports key directives including Disallow to block paths (e.g., Disallow: /private/), Allow to permit access (e.g., Allow: /public/ overriding a broader disallow), and ensures changes propagate after a caching period of up to 24 hours. To mitigate server overload, Bingbot adheres to the Crawl-delay directive in , which specifies a pause (typically 1-30 seconds) between consecutive requests, effectively limiting the daily crawl volume—for instance, a 10-second delay allows approximately 8,640 pages per day—and takes precedence over other rate controls. Complementing this, Bingbot implements built-in politeness policies through adjustable crawl rates configurable in , where site owners can set hourly patterns (e.g., slower during peak like 9 AM–5 PM) to align with , dynamically reducing speed on low-bandwidth sites based on response times. Bingbot also complies with page-level web standards, including the noindex meta tag (e.g., <meta name="robots" content="noindex">) to prevent indexing of specific pages, and respects URL tags (e.g., <link rel="canonical" href="https://example.com/preferred">) to consolidate duplicate content signals during indexing. Additionally, it properly handles HTTP status codes, such as interpreting Not Found responses to exclude non-existent pages from the index and respecting 301/302 redirects for URL normalization.

Issues and Controversies

Impersonation and Security Risks

Malicious actors frequently impersonate Bingbot by spoofing its string, such as "Mozilla/5.0 (compatible; bingbot/2.0; +http://www.bing.com/bingbot.htm)", to gain unauthorized access to websites. This tactic allows bad bots to bypass restrictions or measures designed to permit legitimate crawlers while blocking others, enabling activities like large-scale content scraping for data theft or probing for vulnerabilities as part of DDoS campaigns. According to security analyses, such impersonation contributes to the broader landscape of evasive bad bots that mimic legitimate user agents to evade detection and conduct automated attacks. A notable security vulnerability associated with Bingbot's crawling process was discovered in , involving a persistent (XSS) flaw in its video indexing system. Security researcher Supakiad S. reported that Bingbot ingested unsanitized —such as video titles, descriptions, and owner names—from external sites without proper escaping, allowing injected payloads to be stored and executed when users viewed affected videos on Bing's search results pages. This issue, which exploited a misconfigured content-type header ( instead of ), could lead to , cookie theft, or attacks on unsuspecting users. confirmed the vulnerability and patched it by August 5, , through the Microsoft Security Response Center (MSRC). Legitimate Bingbot crawling can also inadvertently expose sensitive endpoints if websites fail to implement proper access controls, potentially revealing internal or during indexation scans. While Bingbot adheres to standard protocols, this amplifies risks when combined with impersonation, as fake bots may exploit the same paths to target vulnerabilities like or unauthorized . To mitigate impersonation and related risks, website administrators should verify incoming Bingbot requests using Microsoft's official tools, such as the public Verify Bingbot service, which performs reverse DNS lookups to confirm if an resolves to a bing.com or search.msn.com . Additionally, cross-referencing s against Microsoft's published of Bingbot addresses helps identify non-standard origins indicative of spoofing. for anomalous behavior, including irregular request patterns or from unverified ranges, further enables proactive blocking of malicious actors without disrupting genuine crawling.

Performance and Over-Crawling Concerns

Since 2018, webmasters have reported instances of Bingbot engaging in over-crawling, where the bot makes excessive requests to websites, sometimes exceeding 100 per minute, which can overwhelm resources particularly on dynamic or sites. These aggressive crawling patterns have led to elevated CPU and usage, contributing to site suspensions in shared hosting environments. For example, a 2023 case documented over 40,000 requests to a single domain in a short period, resulting in strain and temporary loss of traffic from other search engines. Conflicts with content delivery networks (CDNs) like have also arisen, where unverified or atypical Bingbot requests trigger (WAF) blocks or false positives. Specifically, ' Site Scan feature, which uses distinct IP addresses from standard Bingbot operations, can be misidentified and blocked by Cloudflare's managed rules designed to detect fake bots. This issue requires temporary WAF exceptions to allow scans to proceed, highlighting interoperability challenges between Bingbot and security configurations. User complaints from 2023 to 2025 frequently highlight Bingbot spamming sites with requests for irrelevant URLs or parameters, such as unrelated search queries appended to site paths, often from verified Microsoft IPs. In response, Microsoft directs site owners to Bing Webmaster Tools for crawl management, including submitting feedback or adjusting indexing requests, while recommending robots.txt directives like Crawl-delay to throttle Bingbot's rate—values such as 1 second for slow crawling or up to 10 seconds for extremely slow. The overall impacts include potential site slowdowns and increased hosting costs due to resource consumption, with smaller sites on shared plans being particularly affected as bots compete with legitimate traffic. These concerns underscore the need for balanced crawling algorithms, though 's behavior remains less resource-intensive on average compared to some AI-focused crawlers.