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The Complete Guide to Cloudflare Bot Management

Contents


Abstract

In this comprehensive guide, we will present Cloudflare Bot Management and the value it provides in addressing automated abuse. We will outline categories of bot traffic, explain the detection signals behind Cloudflare’s scoring and verification, and compare the capabilities across service tiers. We will then share a practical thirty-day deployment methodology, rule patterns, and guidance for managing verified and AI-driven bots, before concluding with key metrics, pitfalls, and expected outcomes


Illustration showing Cloudflare Bot Management filtering harmful bots and allowing real users through a protective shield.

1) Definition and motivation

Bots are automated clients. Some are good, such as search crawlers, uptime monitors and link previewers, while many are harmful, including credential stuffing, scraping, carding, scalping and more. The impact of such activity can be significant, ranging from distorted analytics and reduced SEO performance to direct financial losses, regulatory exposure and degraded user experience..

Cloudflare Bot Management is Cloudflare’s Enterprise capability that labels every request with a bot score and a verified‑bot signal so you can take precise action at the edge before traffic harms your application. For smaller sites, Bot Fight Mode (Free) and Super Bot Fight Mode (Pro/Business) provide lighter controls that can be deployed in minutes.


2) How Cloudflare Bot Management works

Cloudflare classifies automated traffic using a blend of:

  • Behavioural modelling and machine learning trained on global and per‑site traffic.

  • Network and device fingerprints, TLS and HTTP characteristics.

  • JavaScript detections where enabled.

  • Positive identification for Verified Bots from trusted platforms.

Two signals are exposed to your rules and logs:

  • cf.bot_management.score – an integer 1–99 indicating the likelihood a request is automated. Lower is more bot‑like.

  • cf.bot_management.verified_bot – true when Cloudflare has authenticated a known good bot or crawler.

You combine these with paths, headers, ASN, country, methods, and rate limits to create targeted policies. Begin with lenient actions, then increase enforcement.


Visual diagram of Cloudflare Bot Management detection flow, showing how incoming traffic is analysed and filtered by behavioural models and machine learning

3) Capabilities by plan

3.1 Bot Fight Mode – Free

Baseline control intended for low‑risk or informational sites. Detects common automation patterns and applies computational challenges to abusive traffic. Deployment effort is minimal and policy surface is small.

3.2 Super Bot Fight Mode (SBFM) – Pro/Business

Provides configurable sensitivity, optional JavaScript detections, static resource handling and scoped application. Suitable when rapid deployment is required and policy complexity is moderate.

3.3 Bot Management – Enterprise

Provides per‑request ML scoring, granular policy authoring, analytics and logging integrations. Commonly selected for authenticated, transactional and API workloads.

Operational guidance: SBFM is commonly used for low‑risk marketing or informational sites; Bot Management is generally selected for authenticated, transactional and API workloads.

4) Integration points within the Cloudflare platform

  • WAF & Custom Rules – apply score‑based actions and combine with any request attribute.

  • Rate Limiting Advanced – shape abuse on idempotent endpoints using robust keys such as headers or session IDs.

  • API Shield – enforce schema validation and mTLS where appropriate on APIs.

  • Security Analytics & Bot Analytics – visualise distributions by score, path, country, ASN, and engine, near real time, up to 30 days.

  • Logpush & Log Explorer – pivot on score, verified bots, and attributes without shipping logs off‑platform.

  • Turnstile – add lightweight user challenges on anonymous flows that tolerate a bit of friction.

  • Workers – customise responses or enrich logging based on bot signals.

  • AI crawler controls – default blocking of known AI crawlers for many zones, with pathways to allow, negotiate, or monetise via Pay‑Per‑Crawl.


5) Selection criteria: SBFM versus Bot Management

Criterion

SBFM (Pro/Business)

Bot Management (Enterprise)

Detection depth

Preset sensitivities, JavaScript detections

Full ML score per request, rich signals in rules

Policy control

Simple profiles and toggles

Fine‑grained rules per path, method, header, ASN

Observability

Basic events

Bot Analytics, Security Analytics, Logpush, Alerts

API/mobile

Basic

First‑class, header‑aware, score‑driven

Time to value

Minutes

Hours to days with staged hardening

Typical use

Marketing sites, blogs

Login, checkout, APIs, mobile gateways

Static resources: with score‑based rules, static files can be included or excluded explicitly. Start by excluding critical assets if you see breakage, then re‑introduce carefully.


7) Implementation methodology (first 30 days)

Days 0–3 – Observe

  1. Turn on Bot Fight Mode or SBFM at conservative settings.

  2. Add Log‑only rules that reference cf.bot_management.score and your sensitive paths.

  3. Watch Bot Analytics, Security Analytics, and Events daily. Note noisy ASNs, countries, and paths.

Days 4–10 – Targeted friction where it matters4. Apply Managed Challenge on login, admin, checkout, and key /api/ routes for low‑score and non‑verified traffic.5. Add Rate Limiting on authentication and search endpoints.6. Allow verified bots by signal, not by user agent.

Days 11–20 – Extend and add API discipline7. Harden scraping hotspots, refine thresholds.8. Enforce API Shield on sensitive endpoints: schema validation and mTLS for trusted clients.9. Document exceptions, and build a small regression script for critical user journeys.

Days 21–30 – Enforce and operationalise10. Promote effective rules from Log to Managed Challenge, then to Block where safe.11. Publish weekly dashboards and alerts for bot spikes.12. Run a rollback drill and publish your runbook.

Supplementary material: For a concise demonstration of steps 1–6, see the configuration walkthrough video: Guide to Cloudflare Bot Management – configuration walkthrough.


8) Reference rule patterns

Keep new rules in Log for a few days. Move to Managed Challenge once you are confident. Use Block sparingly on small, well understood surfaces.

Low‑score, not verified

not cf.bot_management.verified_bot and cf.bot_management.score <= 20

Harden login and admin

(http.request.uri.path in {"/login", "/wp-login.php", "/admin"})
and not cf.bot_management.verified_bot

Protect APIs

http.request.uri.path contains "/api/"
and not cf.bot_management.verified_bot
and cf.bot_management.score <= 30

Guard by ASN or country

(ip.geoip.country in {"CN", "RU"} or ip.geoip.asnum in {"12389", "9009"})
and not cf.bot_management.verified_bot
and cf.bot_management.score <= 30

Rate limiting sketchLimit /api/v1/login to 10 requests per minute per IP or session key. Challenge or delay above the threshold and tune to real user behaviour.


9) Handling verified (“good”) bots

  • Prefer cf.bot_management.verified_bot over brittle user‑agent matching.

  • Maintain a short, purposeful allowlist for essentials only: search crawlers, ad‑tech delivery, link previewers, uptime monitors.

  • Review exceptions weekly and look for spoofing attempts.

  • Keep social previews working by allowing Slack, Discord, and similar unfurlers to fetch canonical URLs and images.

  • For publishers, monitor crawl coverage and index freshness after policy changes.


Flat illustration of verified good bots passing through Cloudflare protection while malicious bots are blocked.

10) AI crawlers and content protection

AI training scrapers often ignore robots.txt. Cloudflare provides three helpful levers:

  1. Default blocking of known AI crawlers on many zones, with clear controls to allow or opt out.

  2. Verified Bots and message signatures to positively identify legitimate agents.

  3. Pay‑Per‑Crawl to negotiate and monetise access where appropriate, plus deception tools such as AI Labyrinth to increase traversal cost for non‑compliant crawlers.

Use these features alongside your bot rules so that legitimate partner bots are welcomed and unwanted AI agents are kept out or channelled into paid pathways.


11) Observability and evaluation metrics

  • Bad bot share on sensitive endpoints.

  • Challenge solve rate and bypass rate.

  • False positives on authenticated or paying users.

  • SEO and ad signals – crawl coverage, index freshness, and delivery latency.

  • Latency and conversion – TTFB and checkout completion.

  • Alert hygiene – Z‑score spikes on low‑score traffic, and anomaly by ASN/country.

Build a weekly dashboard and attach alerts to sudden changes in bot share or solve rate. Keep one canary rule in Log to detect drift.


12) Practical considerations and common pitfalls

  • Start with Log, not Block. Ramp friction on the smallest surface that buys you safety.

  • Exclude critical static assets early if you see breakage, then re‑introduce with care.

  • Do not trust user‑agent alone. Treat it as an informative string, not an identity.

  • Prefer session or device keys for rate limiting over raw IPs.

  • For APIs, pair Bot Management with schema validation and mTLS on high‑trust clients.

  • Document a bypass header for emergency ops and restrict it tightly.

  • Review top ASNs and countries monthly. Attackers move. Your rules should too.

  • Educate stakeholders that Bot Management is not a fraud engine. It reduces noise and cost, and protects capacity. Transactional fraud needs additional signals.


13) Technical notes and FAQs

Is there a magic threshold? No. Many teams start with <= 20 for Block or Challenge on anonymous traffic and <= 30 on /api/, then tune to reduce false positives.

Will this break SEO? Handled correctly, no. Allow verified crawlers and keep an eye on index coverage after policy changes.

Can I use Workers to customise responses? Yes. Many teams alter caching, add headers, or serve lightweight pages when score is low.

What about mobile apps? Treat gateways as APIs. Bind tokens to device or session context and validate on every call. Consider mTLS on trusted apps.


14) Appendix – quick reference

  • Fields: cf.bot_management.score, cf.bot_management.verified_bot, optional cf.bot_management.static_resource.

  • Dashboards: Bot Analytics, Security Analytics.

  • Logs: Logpush fields include bot score and verified bot. Use Log Explorer for ad‑hoc pivots.

  • Alerts: enable Bot Detection alerts for spikes in low‑score traffic.

  • Complementary controls: WAF, Rate Limiting Advanced, API Shield, DDoS, Turnstile, Workers.


Glossary

  • Bot score – a Cloudflare‑provided probabilistic indicator (1–99) of how likely a request is automated; lower values indicate higher likelihood of automation.

  • Verified bot – a Cloudflare signal asserting that the requesting agent is a positively identified, legitimate bot (for example, major search engines or platform previewers).

  • Managed Challenge – an adaptive challenge mechanism at the edge that introduces graduated friction to suspicious clients while minimising user impact.

  • Super Bot Fight Mode (SBFM) – configurable bot protections available on Pro/Business plans, including sensitivity controls and optional JavaScript detections.

  • Bot Fight Mode (BFM) – baseline bot protections available on the Free plan, intended for informational or low‑risk sites.

  • API Shield – a set of API‑specific safeguards including schema validation and mutual TLS (mTLS) for trusted clients.

  • Turnstile – a lightweight, privacy‑focused user challenge that can be applied to anonymous flows.

  • Rate‑limiting key – the identifier (for example, IP, session header, or device token) used to apply rate limits to actors rather than networks.

  • ASN (Autonomous System Number) – an Internet routing identifier used to group IP prefixes; useful for correlating traffic from the same network operator.

  • OWASP OAT – the OWASP Automated Threats taxonomy used to classify automated abuse patterns (for example, credential stuffing or scraping).

  • AI crawler – an automated agent that fetches content for training or inference of AI models; may ignore robots.txt and requires explicit policy.

  • Pay‑Per‑Crawl – a Cloudflare mechanism that enables negotiated, metered access for compliant crawlers to content, with controls for monetisation.

  • Canary rule – a rule kept in log‑only mode to detect drift and provide a baseline for comparison after policy changes.

  • Static resource flag – an optional indicator used to identify static assets so that policies can treat them separately from dynamic requests.


Further reading – Nanosek blog

  • Cloudflare Log Explorer: A Comprehensive Technical Report for Cloudflare Users – operational analysis and use‑cases for native log forensics. Read on Nanosek.

  • Blocking AI Bots and Monetising Content: Inside Cloudflare’s Pay‑Per‑Crawl Revolution – background on AI crawler controls and monetisation levers. Read on Nanosek.

  • Cloudflare Page Shield: Detailed Technical Review – client‑side protection and positive blocking policies. Read on Nanosek.


References

 
 
 

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