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A bot filter can block legitimate visitors when it treats a single clue—a crawler-like User-Agent, a busy IP address, or a low bot score—as conclusive. Each signal can be useful, but its meaning depends on the route, traffic source, counting method, and action attached to the rule. These are common failure patterns, not proof that every implementation blocks real users.
Why is my website blocking real users as bots?
Usually, a rule has turned a useful signal into a hard decision without enough context. An IP address may represent many people, a User-Agent can be shared or misleading, and a bot score is an estimate rather than a verdict. The risk of a false positive varies by site, endpoint, traffic source, and rule configuration.
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OWASP describes bot defense across edge, application, and backend layers and cautions against relying on a single control. A filter should fit the operation it protects, and its outcomes should be monitored so that mistaken blocks can be found and corrected. See the OWASP Bot Management and Anti-Automation Cheat Sheet.
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1. Treating a bot-like User-Agent as proof
A request can claim to come from Googlebot or Bingbot simply by sending a matching User-Agent header. The header alone does not authenticate the crawler. Cloudflare’s fake-bot detection compares bot-like User-Agent patterns with source verification, such as reverse DNS or IP validation. A mismatch can also catch legitimate services that use a bot-like header but originate from a different IP range.
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Cloudflare identifies Google Cloud Workflows or Cloud Functions, Bing Webmaster Tools Site Scan, and monitoring or testing tools as examples of services that can be affected. Its guidance on fake bot detection blocking legitimate requests recommends a narrow exception—such as for a known source IP or range, URI path, or ASN—rather than broadly disabling the detection rule.
What to check before making an exception
- Confirm the service and the source associated with the request; do not trust the claimed User-Agent by itself.
- Check whether the matching rule is limited to the affected path or is applied site-wide.
- Use the narrowest verified exception that solves the problem. A broad exception can also exempt unrelated traffic.
2. Treating an IP request count as a person or bot identity
IP-based limits are easy to configure, but an IP address is not necessarily one user. Many visitors may share an address, while one user’s address may change. A request count can also mix harmless page loads with sensitive actions if the rule is too broad.
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Cloudflare’s rate-limiting best practices illustrate why the counter should match the operation under protection. For an OTP validation endpoint, counting only error responses can prevent valid submissions from consuming the limit. The examples also use different thresholds and actions for a particular price-lookup action and describe using a session cookie to group requests across changing IPs. Those values are configuration examples, not universal thresholds.
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Choose the route, response, and counting key deliberately
- Match the exact URI path and protected action instead of applying a broad request-wide limit.
- Count the response type that signals abuse where appropriate. For OTP validation, failed attempts may be more relevant than successful ones.
- Choose a key suited to the activity. IP and session cookie are examples in Cloudflare’s guidance; neither is right for every endpoint.
- For login limits, OWASP recommends using multiple keys as appropriate and warns that a single combined IP-plus-username bucket can let attempts spread across many usernames without triggering the intended limit.
These choices balance two failure modes: an overly broad or shared counter can burden legitimate users, while a poorly chosen key can make the limit easy to evade. OWASP’s cheat sheet discusses recording useful request context, including time, request ID, route, status code, IP, ASN, country, fingerprint, and User-Agent.
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3. Treating a low bot score as a command to block
A bot score is a product-specific signal, not a complete account of why a request occurred. Cloudflare says its heuristics engine assigns a score of 1 to requests with a missing or empty User-Agent. It identifies corporate proxies or WARP environments that strip the header as a common false-positive trigger. Its scoring behavior and availability are specific to Cloudflare, not a universal standard; see its bot-score documentation.
A hard block based only on a low score can therefore affect traffic whose unusual signal has a legitimate explanation. Cloudflare recommends learning traffic patterns before deploying rules, starting small, and tuning with analytics and security events. Its guidance on challenging bad bots distinguishes blocking definitely automated traffic from challenging likely automated traffic; a challenge can give legitimate users a way through. The documentation notes that rule choices should reflect the site’s nature and tolerance for false positives.
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Use the action that matches your confidence
- Observe traffic first if you do not yet know how a signal behaves on the affected routes.
- Use a challenge when requests are suspicious but the cost of blocking a legitimate visitor is meaningful.
- Reserve hard blocks for cases where the evidence and the site’s tolerance for false positives justify them.
How to stop bots without blocking real users
Compare the rule’s scope, counter, enforcement, and feedback before turning it on. A rule that works on a narrow login or OTP endpoint may be inappropriate for an entire site; a rule that is safe for a low-impact resource may be too strict for account access.
| Control | Signal scope and overlap | Endpoint and counting fit | Enforcement and feedback |
|---|---|---|---|
| User-Agent rule | A claimed header can be shared or spoofed; verify the source rather than treating the string as proof. | Scope any exception to a verified source, route, or ASN. | Review affected requests before broadening an exception. |
| IP-based rate limit | An IP can be shared or change over time. | Match the protected route and action; choose a counting key that fits the activity. | Monitor outcomes and adjust the rule if legitimate requests are constrained. |
| Bot-score rule | A low score can reflect missing context, such as a stripped User-Agent. | Interpret the score in the context of the route and traffic source. | Consider a challenge for uncertain traffic; review analytics and security events before tightening enforcement. |
Exceptions need the same care as blocks. Shared or frequently changing IPs may make IP allowlisting unsuitable, and a fingerprint can overlap with legitimate traffic. Cloudflare’s Bot Feedback Loop guidance advises checking for legitimate use of a fingerprint before blocking on it.
A practical rollout checklist
- Observe the affected traffic. Review the route, source, status, and rule outcome before enforcing a new threshold. Cloudflare recommends learning traffic patterns and starting with small thresholds.
- Constrain the rule. Match the route and operation you intend to protect, not unrelated requests.
- Pick an appropriate key and action. Consider whether requests share an IP, whether identity changes, and whether a challenge or logging stage is safer than an immediate block.
- Monitor and revise. Keep enough request detail to diagnose false positives, then adjust the scope, key, threshold, or action based on what the traffic shows.
There is no neutral cross-site statistic in the cited guidance establishing how often these three patterns block legitimate users. Cloudflare’s numeric thresholds are examples for specific configurations, not general benchmarks.
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