Bot Management

Every request, classified in real time.

Tap a lane to see how Nanosek tunes each action.

ALLOW · score 30 – 99

Likely human

Normal browser sessions with consistent signals — JA3/JA4, headers, behavior, and challenge-pass history.

Pass through silently
No friction added
Logged for baseline

Plan bot protection View bot readiness checklist

On this page

AI summary Machine-readable context is available at /ai-index.json

Nanosek provides Cloudflare Bot Management services for organizations that need to detect, control, and reduce automated traffic across websites, APIs, login flows, checkout flows, content platforms, and business-critical applications. The service includes bot traffic discovery, bot score analysis, policy design, WAF and rate limiting alignment, allowlist strategy, false-positive tuning, rollout planning, monitoring, reporting, and managed Cloudflare operations.

cloudflarebot managementbot protectioncredential stuffingscraping protectionapi abusewafrate limiting

Who this is for

Security teams responsible for reducing automated abuse without damaging customer experience.

Platform, application, e-commerce, SaaS, and API owners protecting login, checkout, forms, search, content, and partner traffic.

Teams with Cloudflare Bot Management or Super Bot Fight Mode that need safer policy design, tuning, reporting, and managed operations.

What Cloudflare Bot Management helps protect

Credential stuffing

Automated login attempts can test leaked credentials at scale. Cloudflare Bot Management, WAF rules, Turnstile, and rate limits help separate high-risk automation from legitimate users.

Login automation

Repeated scripted login behavior can overload identity flows and create account takeover risk. Path-specific bot score policies and rate controls reduce abuse while preserving real sign-ins.

Account takeover attempts

ATO campaigns often combine residential proxies, rotating user agents, and targeted retries. Nanosek tunes layered controls using bot score, request behavior, WAF events, and identity context.

Web scraping

Scrapers can harvest pricing, content, listings, and market data. Bot score thresholds, verified bot handling, cache strategy, and scoped challenges help protect public pages.

Content harvesting

High-volume extraction can degrade performance and leak business data. Cloudflare analytics and rate limits help identify suspicious patterns before enforcement.

Inventory abuse

Automated traffic can reserve stock, check availability, or manipulate demand signals. Checkout and catalog controls need conservative rollout with business-owner approval.

Checkout abuse

Bots can attack payment, coupon, inventory, and purchase flows. Nanosek applies monitoring-first policies so payment callbacks and real buyers are not blocked.

API automation

APIs need endpoint-specific controls rather than generic page rules. Bot Management works with API Shield, mTLS, WAF custom rules, and rate limiting.

Fake account creation

Automated signup abuse pollutes user data and enables fraud. Turnstile, bot score, WAF rules, and form-specific thresholds reduce automated registrations.

Form spam

Lead forms and support forms attract low-cost automation. Turnstile and WAF rules can be tuned to preserve conversion while filtering abuse.

Partner and mobile API abuse

Legitimate automation must not be treated like hostile traffic. Nanosek defines scoped exceptions, service identity, API controls, and monitoring for trusted clients.

High-volume automated traffic

Uncontrolled request floods can increase cost and origin load. Cloudflare rate limiting, caching, bot policies, and Logpush visibility support sustained operations.

Why bot management needs careful deployment

Bot protection is powerful, but unsafe deployment can block critical legitimate traffic. Nanosek does not simply turn on blocking. We design a rollout from visibility to monitoring, challenge, and block based on path sensitivity, bot score, traffic type, and business risk.

Real usersSearch engine crawlersMobile applicationsPayment providersPartner integrationsMonitoring systemsInternal automationAccessibility toolsBusiness-critical API clients

Our Cloudflare Bot Management approach

Phase 1

Discovery and traffic baseline

Review current bot traffic, application flows, login endpoints, APIs, forms, search paths, checkout paths, and known automated clients.
Identify expected bots, verified bots, partner integrations, mobile clients, monitoring tools, and risky paths.

Phase 2

Bot signal analysis

Review bot scores, verified bot signals, JA3 and JA4 fingerprints where available, user agents, ASN, country, request rate, endpoint behavior, and WAF or security events.
Separate useful automation from harmful automation so policy decisions do not rely on one signal alone.

Phase 3

Policy design

Design policies for login, checkout, APIs, static content, forms, search, and high-risk endpoints.
Define when to allow, log, challenge, rate limit, block, or bypass based on path sensitivity and business risk.

Phase 4

Safe rollout

Start with logging and monitoring, then move selected paths to managed challenge or challenge.
Promote only validated abusive patterns to block while keeping rollback and exception handling ready.

Phase 5

Tuning and operations

Review false positives, tune allowlists and exceptions, build dashboards and alerts, and create an ongoing review process for new bot patterns.

Architecture

Bot score distribution by path, hostname, application flow, geography, ASN, client type, and endpoint sensitivity.

Verified bot handling for search engines and known good automation, separated from unknown or suspicious automation.

WAF custom rules, managed challenges, JavaScript detections, rate limiting, API Shield, mTLS, Turnstile, and sequence-aware controls where available.

Logpush, Security Analytics, GraphQL Analytics, dashboards, alerting, and review workflows for ongoing Cloudflare security operations.

Cloudflare controls

Cloudflare Bot Management

Primary detection layer for automated traffic using bot scores, behavioral signals, verified bots, and Cloudflare threat intelligence.

Bot score

Used to segment traffic by automation risk and apply different actions per path, flow, and business impact.

Verified bots

Used to avoid blocking legitimate crawlers and known good automation while still controlling unknown impersonators.

WAF Custom Rules

Used to combine bot score with URI, method, headers, geography, ASN, API path, and application-specific context.

Managed Challenge

Used as a safer enforcement step before blocking when traffic is suspicious but false-positive risk remains.

JavaScript detections

Used where browser behavior signals help separate human users from scripted clients.

Rate Limiting

Used to control repeated login attempts, search abuse, form submissions, API spikes, and high-volume scraping.

API Shield

Used for API discovery, schema validation, endpoint inventory, and tighter API-specific security posture.

mTLS

Used for trusted API clients, partner integrations, and service-to-service traffic where identity should be explicit.

Turnstile

Used on suspicious form, signup, or login flows when a low-friction human verification step is appropriate.

Sequence Rules

Used when request order or journey behavior is available in scope and helps detect automated misuse.

Logpush

Used to send bot, WAF, HTTP, and security events into SIEM or analytics workflows for investigation and reporting.

Security Analytics

Used for review of bot activity, WAF outcomes, challenge rates, bypasses, and attack patterns.

GraphQL Analytics

Used for reporting, trend analysis, and building repeatable operational views across zones and applications.

Cloudflare Workers

Used for advanced edge decision logic when rules need enrichment, custom routing, or application-specific handling.

Control	When Nanosek uses it
Cloudflare Bot Management	Primary detection layer for automated traffic using bot scores, behavioral signals, verified bots, and Cloudflare threat intelligence.
Bot score	Used to segment traffic by automation risk and apply different actions per path, flow, and business impact.
Verified bots	Used to avoid blocking legitimate crawlers and known good automation while still controlling unknown impersonators.
WAF Custom Rules	Used to combine bot score with URI, method, headers, geography, ASN, API path, and application-specific context.
Managed Challenge	Used as a safer enforcement step before blocking when traffic is suspicious but false-positive risk remains.
JavaScript detections	Used where browser behavior signals help separate human users from scripted clients.
Rate Limiting	Used to control repeated login attempts, search abuse, form submissions, API spikes, and high-volume scraping.
API Shield	Used for API discovery, schema validation, endpoint inventory, and tighter API-specific security posture.
mTLS	Used for trusted API clients, partner integrations, and service-to-service traffic where identity should be explicit.
Turnstile	Used on suspicious form, signup, or login flows when a low-friction human verification step is appropriate.
Sequence Rules	Used when request order or journey behavior is available in scope and helps detect automated misuse.
Logpush	Used to send bot, WAF, HTTP, and security events into SIEM or analytics workflows for investigation and reporting.
Security Analytics	Used for review of bot activity, WAF outcomes, challenge rates, bypasses, and attack patterns.
GraphQL Analytics	Used for reporting, trend analysis, and building repeatable operational views across zones and applications.
Cloudflare Workers	Used for advanced edge decision logic when rules need enrichment, custom routing, or application-specific handling.

Bot Management policy examples

Challenge low bot score traffic on login pages after observing false-positive rates.

Allow verified search engine crawlers while challenging unknown crawlers with crawler-like behavior.

Rate limit repeated failed login attempts by path, IP, identity signal, or request pattern.

Block obvious scraping patterns on catalog or content pages after validating business impact.

Apply stricter controls on API endpoints with API Shield, mTLS, WAF custom rules, and endpoint-specific rate limits.

Exclude trusted monitoring and partner IPs through scoped policies instead of broad bypasses.

Use Turnstile on suspicious form submissions, signup attempts, or low-confidence browser traffic.

Log before blocking on checkout flows, payment callbacks, and revenue-critical journeys.