FuckCaptcha is a community-maintained field guide cataloguing 39 CAPTCHA and bot-detection systems with identification signals, difficulty ratings, and documented approaches for authorized research.
| Tool | vsmutok/FuckCaptcha — open field guide to 39 CAPTCHA and anti-bot systems with identification signals and documented approaches |
| Category | Reference documentation / anti-bot research guide (HTML, awesome-list style) |
| Primary Use | Identifying which CAPTCHA family a challenge belongs to (reCAPTCHA, hCaptcha, Turnstile, DataDome, Arkose) and comparing documented solver approaches and trade-offs during authorized testing |
| Safe Use | Educational reference for authorized security assessments, anti-bot engineering, and defensive research on systems you own or have explicit permission to test |
| Telemetry Note | Purely a documentation project — it runs no code against targets; the hosted guide at vsmutok.github.io/FuckCaptcha is a static site, so use of the reference itself leaves no footprint on any target |
Most security tooling on GitHub is executable code, but vsmutok/FuckCaptcha takes a different shape: it is a curated, CC0-1.0-licensed field guide that catalogs 39 distinct CAPTCHA and bot-detection systems in one navigable reference. Written primarily in HTML and structured as an awesome-list-style documentation project, it sits at roughly 135 stars and covers everything from legacy text challenges to modern behavioral anti-bot platforms like Kasada, DataDome, and Akamai Bot Manager. For professionals who encounter an unfamiliar challenge widget mid-assessment and need to identify it quickly, this is essentially a identification cheat sheet with editorial commentary attached.
The project's stated goal is straightforward and defensively useful: consolidate a fast-changing landscape of CAPTCHA systems into one maintained, citable reference. The README frames the material explicitly for education and authorized research, and the usage instructions repeat that constraint — keep testing inside environments where you have permission and respect applicable terms and privacy. That framing matters, because the guide's topics list (captcha-bypass, cloudflare-bypass, datadome, arkose, geetest) makes clear the content overlaps heavily with territory abused by credential-stuffing and scraping operators. The maintainers have chosen to document rather than weaponize, and the repository structure reflects that.
Structurally, the guide is a set of per-vendor Markdown pages under docs/captchas/, each covering one system with an overview, the challenge category it belongs to, references, and documented approaches with their limitations. The README's identification table links to 39 such pages, spanning reCAPTCHA v2, v3, and Enterprise, Cloudflare Turnstile, hCaptcha, GeeTest, Arkose Labs, Amazon WAF, DataDome, MTCaptcha, Tencent, Yandex SmartCaptcha, VK, Cap, Yidun, VAPTCHA, Shumei, Aliyun, Imperva, Kasada, HUMAN PerimeterX, Akamai Bot Manager, Slider, BotDetect, and a long tail including Amazon, Binance, TikTok, Audio, Altcha, Friendly, ATB, CaptchaFox, Capy Puzzle, CutCaptcha, Lemin, Prosopo Procaptcha, Temu, and ARCaptcha. The breadth alone is the value proposition — no single vendor's documentation gives you this comparative view.
What makes it operationally usable rather than just a link dump is the identification layer. Each entry pairs a visual thumbnail (assets/images/captchas/) with the reference page, so an analyst who screenshots an unknown widget during an authorized engagement can pattern-match it against the gallery and land on the right docs/captchas/*.md page. From there the guide provides context on the challenge family — visual puzzle, behavioral fingerprinting, invisible scoring — which is exactly the triage information you need before deciding how a control fits into a client's attack surface narrative.
A second editorial layer is the difficulty scale. The project defines five labels — 1 — Low through 5 — Very high — and applies them across entries. The README is refreshingly honest about what these mean: they are editorial estimates for navigating the guide, not guarantees of how a challenge will behave in any specific deployment. That caveat is technically important, because real-world CAPTCHA resistance depends enormously on configuration, risk scoring thresholds, and whether the vendor is running in visible-challenge or passive-fingerprint mode. Treating the ratings as rough orientation rather than ground truth is the correct reading.
The guide also ships a search-friendly web version hosted on vsmutok.github.io/FuckCaptcha, which mirrors the docs/ content in a browsable interface. For teams building internal wikis or writing assessment reports, this makes citation easier — you can link a client directly to the page on, say, Turnstile or Arkose rather than paraphrasing vendor marketing. The repository's CONTRIBUTING.md and PR-welcome posture suggest the intent is ongoing maintenance, which is critical in this space given how quickly anti-bot vendors rotate their client-side scripts and detection heuristics.
For defenders, the guide reads almost inverted from how an attacker would use it. Each CAPTCHA page documents the signals that identify that system and the approaches documented around it — which is simultaneously a map of where a given control tends to fail. A blue-team engineer deploying hCaptcha or GeeTest can use the same pages to understand which circumvention categories their vendor is exposed to, whether that's solver services, accessibility-mode abuse, or token-replay patterns. As a due-diligence aid when selecting an anti-bot vendor, a comparative reference like this is genuinely hard to find elsewhere in one place.
The project also maintains a docs/solvers.md index alongside the per-CAPTCHA pages, collecting the documented tooling and service landscape — both free/open-source options and commercial ones, per the project's own summary. From a research-integrity standpoint this is the most sensitive part of the repository, and the appropriate professional framing is documentary: knowing which solver ecosystems exist for which challenge types is core threat-intelligence for anyone responsible for bot mitigation, and the guide aggregates that scattered public knowledge into comparable entries with limitations noted.
Where does this fit in an authorized workflow? Three immediate cases stand out. First, web application assessments where you need to name and characterize a CAPTCHA control in the report rather than describing it generically. Second, purple-team exercises modeling automated-threat scenarios against your own staging environments, where identifying the deployed challenge type is step one. Third, anti-bot vendor evaluation, where the difficulty ratings and per-system pages give a structured starting point for questions you should be asking vendors about their resilience against documented approaches. None of these require evading anything you don't own.
Limitations are worth noting. The guide is documentation, not tooling — it will not solve anything for you, and its accuracy depends on community contributions keeping pace with vendor changes. The truncated README structure suggests the per-page depth varies by contributor interest, and the difficulty labels, as stated, are estimates. The license is slightly ambiguous in the context (a CC0-1.0 topic tag versus an MIT badge in the README), which contributors may want to reconcile. None of this undermines the core value.
The bottom line is that FuckCaptcha fills a real gap between vendor marketing pages and scattered forum posts. It is best understood as a field guide for the anti-bot ecosystem: identification first, comparative context second, documented approaches third, all wrapped in an explicitly authorized-use framing. For professionals who need to reason clearly about CAPTCHA controls — whether assessing them defensively or characterizing them during sanctioned testing — a maintained, 39-entry comparative reference with an interactive web version is a solid bookmark.
vsmutok/FuckCaptcha.Educational analysis for authorized security professionals. Use only in controlled, authorized environments.
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