A sudden bot-traffic spike is a signal to investigate, not proof of an attack. First check whether users or your origin are affected, then compare edge and origin logs with normal traffic, verify what kind of automation is making the requests, and apply the narrowest control that addresses the observed behavior. Watch for false positives and confirm the change helped.
1. Confirm the impact and affected parts of the site
Start by checking whether the traffic increase has caused a user-facing or infrastructure problem. Look for increased latency, errors, failed logins, checkout failures, or elevated origin load. Identify the affected hostnames and paths, and note when the change began. Keep a timestamped incident record so you can compare symptoms with later rule changes.
A spike alone does not establish malicious scraping, a DDoS attack, or a legitimate crawler surge. Treat service impact and traffic characteristics as separate questions: determine what is happening to the site, then investigate who or what is making the requests.
2. Compare the spike with normal traffic
Review logs from both the CDN or WAF edge and the origin, and compare the event with a representative normal period. Microsoft’s Application (Layer 7) DDoS protection guidance recommends checking for changes in request rate, client IP count, geography mix, user-agent distribution, and requested URIs.
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- Volume and timing: When did the increase start, how quickly did it grow, and is it sustained or intermittent?
- Source mix: Did the number of client IPs, geographic distribution, or user-agent mix change? These are clues, not proof of identity.
- Paths and query patterns: Are requests concentrated on a costly endpoint, a sensitive action, or repeated URL and query combinations?
- Responses: Look for unusual status-code patterns, including 429 Too Many Requests and high volumes of 403 or 404 responses.
- Protection events: Check firewall and CDN logs for rate-limit, challenge, block, or other rule decisions that coincide with the spike.
Cloudflare notes that a general way to identify some bot traffic is to rate-limit requests producing a large volume of 403 or 404 responses at the origin; that pattern can help focus an investigation, but it is not by itself proof that every matching request is unwanted. See Cloudflare’s rate-limiting best practices.
3. Determine whether the traffic is useful, suspicious, or self-inflicted
Do not block a client merely because its user-agent claims to be a crawler or because its IP appears in a chart. Verify known crawlers using the verification methods and labels available in your provider’s controls, then examine their actual request behavior and the paths they access. A recognized search crawler may be beneficial; an evasive scraper or automated client targeting expensive or sensitive routes may not be.
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Also check whether your own protections are contributing to the symptoms. A rise in 429 responses, rate-limit events, or firewall decisions may indicate that a control is throttling legitimate users or integrations rather than stopping unwanted automation. Identify the responsible rule or setting before changing it.
Provider features vary. AWS distinguishes common bot protection, which can identify self-declared bots, from targeted protection that adds detection for bots concealing their identity. Its AWS WAF Bot Control documentation describes those approaches and their labels. Cloudflare documents combining bot scores with rate limits and session cookies in its Bot Management guidance. These are examples of provider-specific controls, not guarantees that every site has the same signals or options.
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4. Choose a targeted mitigation
Match the intervention to the pattern you found. Prefer a rule scoped to the affected URI, behavior, session, or bot category over a broad block based on one IP, country, or user-agent string. The appropriate control depends on the traffic, the site’s existing CDN/WAF capabilities, and whether the route is safe to challenge.
| Observed situation | Possible response | What to watch |
|---|---|---|
| High request volume concentrated on a particular route | Use a rate-based rule scoped to the route or relevant behavior. AWS describes rate-based controls for high-volume activity and sensitive URIs in its rate-based rule guidance. | Legitimate usage of that route, 429 responses, origin load, and whether the unwanted pattern declines. |
| Requests appear automated, but identity or intent is uncertain | Where supported, use a challenge or observe/label mode before moving to a hard block. Review the provider’s events and labels. | Challenge failures, successful legitimate sessions, and effects on APIs or integrations. |
| Repeated requests trigger many origin 403 or 404 responses | Consider a narrowly scoped rate limit for the relevant paths or response pattern, following the provider’s guidance. | Whether the pattern comes from unwanted automation or a broken link, client, or deployment. |
| Verified automation is useful and behaves as expected | Allow or handle it according to the site’s provider controls rather than treating all crawlers alike. | That the verification remains valid and the crawler is not causing harmful load on sensitive routes. |
Do not copy an example request threshold as a universal safe limit. Cloudflare and AWS guidance tie rate decisions to traffic patterns, URI impact, and site configuration; a suitable threshold for one route or site may be harmful on another.
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5. Validate the change and check for false positives
After enforcing a rule, compare the same signals you used to diagnose the spike. Confirm that unwanted requests or their impact have fallen, while legitimate users can still reach important pages and complete critical flows. Review challenge, block, and rate-limit events alongside user-facing errors.
AWS advises reviewing Bot Control labels and checking that legitimate traffic is not mislabeled before moving to block mode. Challenges can also disrupt real users or integrations, especially on APIs and other critical flows, so inspect those paths specifically. If errors increase or useful traffic is caught, narrow or roll back the rule and investigate the matching requests before trying a broader control.
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6. Reassess and record what worked
Once the site is stable, remove temporary rules that are no longer needed. Keep only controls whose scope and effects you understand. Record the observed pattern, the rule changes, any side effects, and the thresholds that proved appropriate for your own traffic; that record can make a later incident easier to diagnose.
When to involve your provider
If users are experiencing service disruption, origin capacity is under pressure, or the traffic appears volumetric, contact your hosting, CDN, or WAF provider and follow your organization’s incident process. Provider context matters because the logs and mitigation options available depend on the products and configuration in use. The cited guidance does not establish one universal request rate or impact threshold for escalation.
Why there is no universal bot threshold
Normal traffic varies by site, route, time, and user activity, and a request rate that is harmless for one URI may overload another. Some targeted detection features also need observations during normal operations to establish baselines. AWS documents baseline requirements for some targeted protections in its Bot Control documentation; turning on such a feature during an incident may not provide mature detection immediately. Use observed impact and your own baseline rather than a threshold copied from another site.
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