What Is Bot Traffic and How to Identify It

Bot traffic is activity on a web resource generated by automated programs (bots) instead of real users. These programs can be either beneficial, such as search crawlers, or malicious, such as spam bots or DDoS bots.

According to the Imperva Bad Bot Report 2025, automated requests now account for 51% of all web traffic, with the share of malicious bots rising to 37%. Cloudflare Radar confirms the trend: in Ukraine during 2024, a steady increase in unwanted activity was recorded, with bots accounting for 8% of data flow at one of the country's largest providers.

Types of Bots

Bots can be divided into two main categories: beneficial (white) and malicious (black), depending on their goals and impact on web resources.

White Bots

1. Search crawlers: scan and then index web pages so that search engines can provide up-to-date search results. Examples include Googlebot or Bingbot.
2. Monitoring bots: used to check website performance, page availability, loading speed and error presence. Examples include Uptime Robot or Pingdom.
3. Chatbots: simulate conversation with a human and are used for customer service, providing information or assisting with site navigation.
4. Data collection bots: can be used for regular collection of public information (e.g., product prices or competitors' metadata).
5. Testing bots: automate testing of web applications, APIs and other systems by simulating user behavior to detect potential errors.

Black Bots

1. Spam bots: used to send unwanted messages, comments, register fake accounts on forums, blogs or social networks. The main goal is distributing ads, phishing links or malicious content.
2. Click fraud bots: simulate clicks on ads (e.g., contextual ads) to artificially increase the advertiser's costs or drain a competitor's budget.
3. DDoS bots (Distributed Denial of Service): part of botnets (networks of infected computers) and used to overload website servers with massive numbers of requests, making them unavailable to real users.
4. Registration bots: create large numbers of fake accounts on sites, often for further use in spam campaigns, fraud or to access restricted content.
5. Vulnerability scanning bots: look for weak points in website and server security to later exploit them for hacking, injecting malicious code or stealing data.
6. Human impersonation bots: the most advanced malicious bots that attempt to precisely mimic human behavior on a website (mouse movements, scrolling, clicks) to bypass protection systems and appear as real users.
7. Sniping bots: in e-commerce, may be used to monitor competitor prices, as well as automatically receive discounts or purchase scarce goods.

How to Identify Bot Traffic

• low time on site and high bounce rate: the user visits one page and immediately leaves;
• abnormally high frequency of visits from one IP address: many requests from a single source in a short time;
• unusual user behavior: no mouse movement or scrolling, transitions that are too fast or too slow;
• requests to non-existent pages or system files: attempts to access «hidden» URLs or scripts;
• traffic geography: traffic spike from unusual regions or countries;
• non-standard or outdated User-Agent: use of unknown or long-outdated browser identifiers;
• traffic spikes during off-hours: abnormal activity at times when the target audience is usually inactive;
• low conversion rate with high traffic: many visitors but few target actions (purchases, registrations);
• spam in forms (comments, registration): forms filled with meaningless data or links.

Methods of Detecting Bot Traffic

Each method alone does not provide a complete picture, but combining several approaches can effectively identify and block unwanted traffic.

Consequences of Ignoring Bot Traffic

If bot traffic is not given due attention, it can distort analytical data, preventing sound marketing decisions. False indicators increase advertising costs. Additionally, malicious bots may scan for vulnerabilities, steal content or overload the server, reducing website performance and increasing the risk of DDoS attacks. As a result, SEO efficiency, user trust and overall site stability decline.

Recommendations for Minimizing Bot Traffic

Minimizing bot traffic requires a comprehensive approach combining preventive measures with active monitoring and blocking.

1. Implement CAPTCHA and reCAPTCHA in contact, registration and other interactive forms to distinguish people from programs.
2. Configure filters in analytics systems to exclude known bot traffic by IP addresses or User-Agent.
3. Regularly analyze server logs to detect abnormal behavior patterns and block suspicious activity sources.
4. Use a Web Application Firewall (WAF) that filters malicious traffic before it reaches your server, protecting against a wide range of bot attacks.
5. Consider using a CDN (Content Delivery Network) with bot protection features to distribute load and filter unwanted traffic.
6. Implement Honeypots — hidden elements on the site that are invisible to humans but accessible to bots; interaction with the trap indicates a bot and allows blocking.
7. Limit the number of requests (rate limiting) from one IP address over a set period to prevent excessive bot activity.
8. Regularly update CMS software, plugins and server software to close known vulnerabilities that bots could exploit.

Conclusion

Bot traffic accounts for a significant share of modern visits and must be distinguished from real users. By identifying signs of automated requests and combining behavioral analysis, User-Agent and IP checks, JavaScript tests, WAF and known bot lists, unwanted activity can be blocked in time. Ignoring the issue leads to inflated advertising costs, vulnerabilities and reduced site performance, so regular monitoring, log filtering and preventive protection measures should be part of an ongoing strategy.

FAQ

How can a sudden spike in website visits during off-hours indicate bot activity?

A sudden spike in visits during off-hours, especially at night or on weekends when user activity is expected to be low, is a strong indicator of bot activity. Bots operate 24/7 and are not affected by time zones or work schedules.

What behavioral patterns on the site recorded in web analytics can serve as «red flags» for detecting malicious bots?

Abnormally high bounce rates, very short or unnaturally long time on site, viewing a limited number of pages without logical transitions, as well as unusual traffic sources or geographic locations.

Besides skewing statistics, what direct security threat can a significant volume of malicious bot traffic pose to a website?

Besides skewing statistics, a large volume of malicious bot traffic can pose a direct security threat through DDoS attacks, brute-force login attempts, content scraping (data theft), exploiting vulnerabilities in web applications or executing spam attacks via contact forms.

Are there free or publicly available tools that can help a small website owner detect suspicious bot activity?

Yes, small websites can use Google Analytics to monitor traffic anomalies and behavior patterns. Server log analysis tools (such as Awstats, GoAccess) and basic firewall configurations (e.g., WAF like ModSecurity for Apache/Nginx) can also track and block suspicious IP addresses or User-Agents.

What strategies exist for blocking or filtering unwanted bot traffic at the server or CDN level?

At the server or CDN level, strategies include IP address filtering (black/whitelisting), User-Agent blocking, using CAPTCHA to verify human activity, request rate limiting from one IP address, and applying a Web Application Firewall (WAF) that analyzes and blocks abnormal requests based on rules.