The digital landscape is heavily populated by bots , often generating traffic comparable to human users. While many are malicious—such as scrapers, spammers, or imposters—a significant portion consists of “good bots” (also known as known bots) that perform essential, legitimate functions. These helpful agents are the digital workforce of the internet, responsible for indexing content for search engines, generating link previews on social media, and monitoring website health.

In the haste to block malicious traffic, accidentally excluding these beneficial crawlers can lead to serious operational issues: dropped search rankings, broken social media previews, and disrupted integrations. The challenge for any site administrator is to find the right balance—intentionally welcoming the necessary bots while excluding or throttling the rest.

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Basic Bot Identification: User Agents and Patterns

When a legitimate bot visits a website, it identifies itself with a user agent (UA) string . This is a small snippet of text that typically contains the name of the bot or its operating company (e.g., Googlebot , Bingbot ).

Because known, legitimate bots adhere to these predictable naming conventions, they can often be identified and categorized using patterns. For example, a search engine crawler might include the word “Googlebot,” while a social media preview agent might use “facebookexternalhit” or “Twitterbot.”

A Note on Security

Relying solely on the user agent string for security is risky. Malicious actors frequently spoof the UA strings of legitimate bots to gain access or hide their activity. Effective bot detection requires verifying the bot’s identity through other means (like IP address verification) and analyzing its behavior, as a simple UA filter is easily bypassed.

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The Major Categories of Legitimate Bots

Understanding the intent behind a bot’s visit is key to managing its access and resources. Legitimate bots can be grouped into several core categories based on their purpose:

1. Search Engine Crawlers

These are the digital explorers of the web. They navigate and read website content to index it for display on their search engine results pages. They are absolutely critical for SEO visibility .

• Function: Indexing web pages for global search results.
• Management: While essential, they can consume significant server resources. Site owners use the robots.txt file to guide them to the most relevant areas of the site and prevent excessive resource usage.
• Examples: Googlebot (Google), Bingbot (Microsoft), Baidu Spider (Baidu), YandexBot (Yandex).

Bot Name	User Agent (Example)	Purpose
Googlebot	...Googlebot/2.1...	Primary indexer for Google Search.
Bingbot	...bingbot/2.0...	Primary indexer for Bing Search.

2. Social Media and Content Preview Bots

These crawlers are triggered when a user shares a link to your website on a social platform. They fetch page metadata and images to generate a visually appealing link preview card (or snippet).

• Function: Generating accurate content previews for links shared across platforms.
• Management: Blocking these bots will result in bare URLs and missing previews, negatively impacting link engagement. They must generally be allowed access to ensure proper link display.
• Examples: facebookexternalhit (Meta/Facebook), Twitterbot (X), LinkedInBot , Pinterestbot , Slackbot .

Bot Name	User Agent (Example)	Purpose
Twitterbot	Twitterbot/1.0...	Generates X (Twitter) card previews.
Facebook Crawler	facebookexternalhit/1.1...	Generates previews for Facebook and Instagram.

3. SEO and Marketing Analytics Crawlers

These bots gather data used for market research, SEO audits, competitor analysis, and backlink checking. They are valuable tools for digital marketing professionals.

• Function: Collecting data points (backlinks, keyword rankings, content changes) for third-party SEO toolkits.
• Management: While they provide useful insights, they can sometimes be aggressive in their request volume and may need to be throttled or selectively blocked to conserve bandwidth. Many offer specific opt-out mechanisms beyond robots.txt .
• Examples: AhrefsBot , SemrushBot , MJ12Bot (Majestic SEO).

4. Monitoring and Uptime Bots

These are “guardian angels” that regularly check a site’s availability, performance, and response time to alert the owner in case of an outage.

• Function: Performing regular “health checks” to ensure a website remains online and responsive.
• Management: They are useful for site reliability but their frequent, automated pings must be filtered out of standard visitor analytics to prevent data skewing.
• Examples: Pingdom.com_bot , UptimeRobot , BetterStackBot .

5. AI and Large Language Model (LLM) Data Crawlers

This is a rapidly growing and newer category of crawlers, operated by AI companies to scrape and index vast amounts of public data. This data is then used for training large language models (LLMs) or powering real-time AI services.

• Function: Gathering training data for AI models (like those powering ChatGPT or Claude) or retrieving fresh information for AI answers.
• Management: Due to data ownership concerns and their high volume, this group is highly scrutinized. They often do not consistently respect robots.txt , requiring administrators to use more robust controls like blocking by UA string or IP range.
• Examples: GPTBot (OpenAI), ChatGPT-User (OpenAI), ClaudeBot (Anthropic), PerplexityBot (Perplexity AI).

6. Security and Vulnerability Scanners

These bots scan domains for exposed databases, open ports, vulnerable plugins, and other security flaws, often for threat intelligence and cybersecurity research.

• Function: Probing websites and connected devices to identify security vulnerabilities.
• Management: Reputable scanners announce themselves clearly. Their visits can be a useful signal to audit security, but they can generate significant traffic and may be blocked via a firewall if deemed disruptive.
• Examples: CensysInspect , Shodan .

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Best Practices for Managing “Good” Bot Traffic

Effective bot management is a necessary, ongoing practice. It requires a thoughtful approach that balances the need for search visibility and function with resource conservation and security.

1. Use robots.txt as the Foundation

The robots.txt file is the essential first layer of control.

• Restrict Low-Priority Areas: Use it to block crawlers from internal assets, staging environments, login paths, or low-value content.
• Customize Directives: Utilize agent-specific rules ( User-agent: Bingbot ) or Crawl-delay directives to manage the speed and frequency of visits from high-volume crawlers.
• Know Its Limits: Remember, robots.txt is advisory . Malicious or poorly programmed bots will ignore it.

2. Never Trust the User Agent Alone

Malicious actors constantly spoof known UA strings. Relying solely on the UA to grant access is a security risk.

• Verify by IP: For major crawlers (like Googlebot), perform a reverse DNS lookup on the visiting IP address to confirm the source’s authenticity.
• Analyze Behavior: Log the bot’s activity. If a “known” bot is exhibiting strange behavior (e.g., scraping at a high rate or accessing protected paths), it is likely an imposter.

3. Monitor and Analyze All Bot Activity

Bot traffic interacts directly with your infrastructure and data. It must be tracked just as rigorously as human traffic.

• Review Server Logs: Regularly analyze server and firewall logs to understand what content bots are requesting and how frequently.
• Flag High Volume: Watch for sudden spikes in traffic from new or existing bots that may indicate a resource issue or a potential attack.
• Filter Analytics: Ensure monitoring and uptime bots are excluded from standard visitor analytics to prevent skewing crucial performance metrics.

4. Apply Tiered Control Based on Purpose

Treat bots differently based on the value they provide and their potential impact:

• Allow Freely: Search engine crawlers (managed via robots.txt ) and social media preview bots.
• Rate-Limit: SEO/Analytics bots that provide value but can be aggressive with requests.
• Strictly Control/Block: New, unverified AI agents or vulnerability scanners that are deemed disruptive or whose data collection is not desired.

5. Commit to Continuous Review

The bot ecosystem is highly dynamic, especially with the rapid emergence of AI agents.

• Audit Rules Regularly: Review all access rules, filters, and allowlists every few months.
• Stay Informed: Keep up-to-date with new user-agent strings and documentation published by major bot operators.

Effective bot management requires visibility, precision, and adaptability to ensure that the legitimate digital workforce can function efficiently without compromising your site’s performance or security.