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A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11Protect an online store from abusive bots with a measured, layered defense: identify the endpoints being targeted, preserve legitimate automation, apply narrow controls to risky actions, and watch for false positives before blocking traffic. Not every automated visitor is harmful—search crawlers, monitoring agents, and accessibility tools can be legitimate.
Identify what the bots are doing before choosing a control
Scraping is only one kind of automated abuse. A store may also face credential stuffing, fake account creation, inventory hoarding, card testing, gift-card enumeration, or misleading business metrics. The right response depends on the endpoint and the business risk; a single site-wide request ceiling will not address every problem.
OWASP’s Bot Management and Anti-Automation Cheat Sheet maps different endpoint classes to different risks and controls. Use traffic analytics and request logs to find unusually frequent or suspicious activity, then prioritize the affected operation:
- Catalog, search, and price lookups: investigate suspected harvesting of product data and repeated queries.
- Login and account creation: look for credential-stuffing attempts or automated fake signups.
- Cart and checkout: investigate inventory hoarding or automated purchases.
- Public APIs: identify which operations are being called and whether the access pattern fits the client or integration.
Controls should match the operation. A rule suitable for repeated product searches may be inappropriate for checkout or a customer-facing API.
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Keep legitimate crawlers and services working
Before tightening controls, make an inventory of expected search crawlers, uptime monitors, accessibility tools, integrations, and mobile or in-app clients. Where your platform supports it, verify a crawler’s claimed identity; do not rely solely on a request’s self-description. Create explicit exceptions or separate handling for known operational traffic.
A blanket block on automated requests can interfere with search discovery, monitoring, integrations, or customer access. OWASP describes the goal as raising the cost of abusive automation while keeping legitimate users and bots unaffected. Cloudflare likewise advises distinguishing malicious bots from legitimate traffic in its guide to stopping malicious bots while allowing legitimate traffic.
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Rate-limit the actions that matter
Apply limits to meaningful operations—such as repeated price lookups or catalog queries—rather than relying only on a blunt, site-wide request cap. Choose an appropriate identity signal and combine it with behavior where possible. An identity can be a session or another application-specific signal; no single signal is reliable in every situation.
Cloudflare’s rate-limiting best practices include ecommerce examples for repeated price lookups, with actions such as managed challenge or block, as well as a session-cookie pattern for lookups submitted in JSON bodies. These are configuration examples, not universal thresholds. Derive limits from your own legitimate traffic and operational tolerance, and test them against normal shopping behavior before enforcement.
Add bot classification or challenges if narrow limits are not enough
A web application firewall (WAF) or bot-management service can classify automated traffic and provide monitoring, rate limiting, challenges, or blocking. Capabilities vary: some controls identify bots that disclose themselves, while others are designed to detect automation that attempts to disguise its identity.
AWS WAF Bot Control
AWS distinguishes a common level, focused on self-identifying bots, from targeted protection for more evasive automation. Targeted protection adds techniques including browser interrogation, fingerprinting, behavioral heuristics, and machine-learning analysis. AWS identifies evasive scraping, residential proxies, headless browsers, and automated purchasing as use cases for targeted protection. See the AWS WAF Bot Control rule group and AWS’s guidance on choosing and configuring Bot Control for a use case.
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Cloudflare bot products
Cloudflare documents Bot Fight Mode, Super Bot Fight Mode, and Enterprise Bot Management, with differences in customization, per-request scores, endpoint handling, and analytics. Its overview identifies ecommerce as a use case for the more granular Enterprise product. Features depend on product and plan, so check Cloudflare’s current overview of bot solutions before selecting a tier.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Deploy in observation mode, then tune enforcement
Start by examining available bot analytics, security events, labels, or logs. For AWS Bot Control, count mode labels traffic without blocking it. AWS recommends reviewing what is detected and checking for legitimate traffic that may be misclassified before moving to blocking. Cloudflare also describes reviewing bot analytics and requested paths before applying controls.
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- Observe: enable the relevant analytics, labels, or count/monitor mode where available; record which paths and operations attract suspicious traffic.
- Check exceptions: confirm that expected crawlers, monitors, integrations, and customer clients are not being caught by a rule.
- Scope a control: apply a narrow rate limit, challenge, or block to the affected endpoint or behavior rather than broad traffic categories.
- Review impact: monitor conversion, customer-support complaints, crawler access, and false-positive reports after changing enforcement.
- Escalate carefully: block only when the observed classifications and impact give you confidence the traffic is abusive.
A challenge can add friction for legitimate shoppers if it is applied too broadly. AWS also notes that Bot Control adds cost based on evaluated request volume; scope rules and their order with cost in mind.
Compare options against your store’s setup
Compare controls by what they detect and how well they fit your existing hosting and operations—not just by whether a product advertises bot protection.
| What to compare | Questions to ask |
|---|---|
| Detection scope | Does it identify only self-identifying bots, or also automation that disguises itself and uses browser automation? |
| Control granularity | Can rules differ by endpoint, operation, bot category, or confidence level? |
| Legitimate automation | Can verified search crawlers, health checks, and known services be allowed or handled separately? |
| Deployment fit | Does it work with your CDN, WAF, API gateway, store platform, and client integrations? |
| Monitoring and tuning | Are analytics, logs, observation or count modes, and a false-positive workflow available? |
| Cost | Does pricing depend on request volume, protection level, or plan? Confirm current terms with the vendor. |
For example, AWS says Bot Control incurs additional fees and that costs depend on the number of evaluated requests. Cloudflare’s product tiers differ in available controls and analytics. Check current vendor documentation and pricing for your configuration rather than assuming a feature or price applies to every store.
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