DEV Community: Markus

Low-Code/No-Code vs CAPTCHA: can you automate CAPTCHA solving without writing code?

Markus — Thu, 02 Oct 2025 06:27:21 +0000

A CAPTCHA is essentially a bite-size Turing test meant to separate scripts from humans. If you’ve spent any time online, you’ve seen it all-from the “I’m not a robot” checkbox to mosaic puzzles hunting for traffic lights and crosswalks. For most people it’s a mild nuisance; for automation teams it’s a recurring roadblock. The question is blunt: can Low-Code/No-Code platforms get past or resolve CAPTCHAs without traditional programming? Let’s unpack it.

What is a CAPTCHA and which kinds are out there

Before we touch bypass tactics, map the usual CAPTCHA species automation engineers face.

Google reCAPTCHA v2. The popular workhorse from Google. Typically appears as the “I’m not a robot” checkbox (No CAPTCHA reCAPTCHA). If the system doubts your humanity, it escalates to image tasks-“pick all the buses,” “find the crosswalks.” There’s also an Invisible variant that triggers challenges on suspicious traffic without a visible click.
Google reCAPTCHA v3. The latest Google flavor runs quietly in the background. It scores behavior-mouse movement, click cadence, session history-on a 0.0–1.0 scale. Low score = likely bot. Ideally, humans see nothing; risky sessions may be blocked or pushed into an extra gate (often a v2-style test).
hCaptcha. A privacy-forward alternative by Intuition Machines. The mechanics mirror reCAPTCHA-classification tasks and image grids-but the difficulty skews higher for end users. Enterprise customers get invisible options; on the free tier, manual solving is the norm.
Cloudflare Challenge and Turnstile. Cloudflare historically leaned on Google and later hCaptcha, then launched Turnstile in 2022.
Challenge shows an interstitial that inspects your browser posture: JS support, TLS soundness, cookies, IP reputation, and more-then may ask for a “not a robot” proof.
Turnstile moves checks into the background to avoid riddles and tiles; if signals look off, it can still surface an interactive prompt (including hCaptcha). Developers can drop in the free widget as a reCAPTCHA replacement that issues a confirmation token without sending data to Google.

Bottom line. reCAPTCHA v2/v3 and hCaptcha all chase the same goal-filter bots-via explicit tasks or covert scoring. Cloudflare layers its own invisible screening on top. None is bulletproof: tuned too hard and users suffer; tuned too soft and sophisticated bots slip through. By design, all of them slow down automation until a human-grade answer appears.

Why CAPTCHAs derail automation - how to bypass CAPTCHA without code

CAPTCHAs exist to snap automated flows. If you’re scraping, batch-creating accounts, or submitting forms on autopilot, repeated actions almost guarantee an encounter. Site owners deter abuse and spam; automation developers-even on legitimate work like QA, public-data aggregation, or routine form handling-hit friction. Miss the CAPTCHA and the workflow collapses.

Solving CAPTCHAs automatically is difficult by intent. Image grids demand computer vision that tolerates distortions; even “simple” text CAPTCHAs evolved beyond toy OCR with noise, rotation, and decoys. Vendors continually raise the bar. AI helps, but “100%” is fantasy-formats change, tasks diversify, models misfire.

Meanwhile, defenders aren’t invincible. Over time, mass-scale bypass tactics emerged:

Human relay. “CAPTCHA farms” route challenges to people for cents and seconds. A bot sends an image or site parameters; within ~10–20 seconds, an operator or model returns the solution. To the site, it looks like a legitimate user response.
Token harvesting & cookie games. Attempts to reuse solved tokens or exploit side doors-e.g., grabbing g-recaptcha-response out of context or faking a “verified” cookie state.
Human-like behavior. Headless browsers with stealth plugins, varied user-agents and proxies, jittered delays, mouse trajectories-anything to earn a friendlier v3 score or avoid v2 entirely. No guarantees, though.
Computer vision. Cheaper, better, more accessible-yet rotating image sets (e.g., hCaptcha) and machine-visible watermarks still trip automated solvers.

So yes, there’s a mature market that “solves CAPTCHAs for you.” The next question: how-and whether-to plug this into no-code stacks. First, a scan of the platforms.

Low-Code/No-Code platforms for automation CAPTCHA Bypassing

No-code/low-code let you assemble working bots and integrations without hand-coding-think visual canvases, flow diagrams, ready modules, and connectors. In web-adjacent automation, three names dominate:

Zapier. A pioneer of the “trigger → action” recipe, with 6,000+ integrations. Perfect service glue, not a browser driver. Crucially, Webhooks let you call arbitrary HTTP endpoints-your bridge to any API. For clickstream automation it’s limited, but as an orchestrator it shines.

Make.com (ex-Integromat). A more flexible visual engine: branches, loops, variables, granular HTTP handling, HTML/JSON parsing. It supports proxies and parallel runs. In CAPTCHA contexts, you can wire any solver API, build wait-poll cycles, and keep it all visual.

UiPath. Classic RPA for real UI: browsers, desktops, office apps. A powerful activity palette and .NET under the hood. The weak spot is CAPTCHAs-robots “see” iframes or images but not semantics. UiPath counters with Computer Vision (useful for UI, not hard CAPTCHAs) and Marketplace components that integrate directly with solver APIs. Drag a block, send the challenge, receive the answer, inject it back.

Also in the mix. n8n (self-hosted Zapier/Make), Automation Anywhere, Blue Prism, IFTTT, plus browser-centric tools like Selenium IDE, Axiom.ai, Automa, and the SEO-favorite ZennoPoster (a visual action editor with branching and code hooks).

Tactics without coding: reduce CAPTCHA frequency-and handle it when it appears, or just Bypass CAPTCHA

1) Prevent the CAPTCHA

Prefer official APIs. If there’s a sanctioned interface, use it. In no-code land, that’s a connector instead of brittle web emulation.
Mimic normal behavior. Reasonable pacing, proper headers, and IP hygiene. Residential proxies beat datacenter IPs that Cloudflare flags. Make/n8n support proxies natively; Zapier needs an external relay; UiPath can run through VPN/proxy.
Persist sessions & cookies. Reuse real user auth and cookies (e.g., cf_clearance) to dampen challenges-understanding these expire and environment changes (IP, browser updates) reset your standing.

These steps lower odds, not eliminate them. At scale, you’ll still face CAPTCHAs.

2) Solve CAPTCHA through external services

Rolling your own solver is costly and brittle. API services do the heavy lifting-humans, models, or hybrids behind a simple contract.

Notable providers:

2Captcha. Veteran solver for image CAPTCHAs and modern types (reCAPTCHA v2/v3, hCaptcha, FunCaptcha, GeeTest). Send an image (base64) or site params (sitekey + URL), then poll for status. The response is text (for classic CAPTCHAs) or a token to inject. Cheap, fast, and easy to wire: HTTP/Webhooks in Make/Zapier; a ready UiPath Marketplace component that returns g-recaptcha-response.
Anti-Captcha. Similar model: people + infra, SDKs and plugins across stacks, UiPath components, HTTP APIs for Make/Zapier.
DeathByCaptcha. Long-running Western service with compatible APIs.
SolveCaptcha. Hybrid approach-AI first, human fallback.

Example wiring (Zapier + Browserless):

Schedule in Zapier. Kick off on cadence.
Browserless HTTP call. Remote Chrome opens the page, extracts sitekey or raw HTML.
Webhook → 2Captcha. POST with API key, task type, sitekey, and page URL; receive a task ID.
Delay & poll. Wait 15–20s, GET status until ready.
Receive token. Grab the g-recaptcha-response.
Browserless submit. Inject token into the hidden field and submit.
Handle response. Parse, store, notify-whatever the flow dictates.

All blocks, no code.

In Make.com, it’s even smoother: HTTP → wait → HTTP (loop until result) → continue, with native HTML parsing and branches.

In UiPath, the robot captures the challenge (screenshot or iframe data), calls a solver via a Marketplace activity, and injects the answer. For v2 tokens you’ll often use Inject JS to set document.getElementById("g-recaptcha-response").value.

Comparison across platforms for bypass CAPTCHA nocode methods

Zapier. Minimal HTML touch, excellent orchestration via Webhooks and delays; relies on external tools for the heavy lifting.
Make.com. Visual logic that feels close to code-loops, conditions, parallelization, proxies, HTML parsing. CAPTCHAs become just another module.
UiPath. Strong with real UI. Solves CAPTCHAs by leaning on solver APIs and targeted scripting to place tokens.

Conclusions

By 2025, low-code/no-code can run sophisticated automations-service meshes, data collection, UI emulation-with almost no hand-coding. CAPTCHAs remain the speed bump that stops naive flows. Platforms avoid native “bypass” features to discourage abuse, so the practical path is prevention (APIs, hygiene, sessions) plus external solvers, all wired visually.

Net takeaway: don’t let CAPTCHAs cap your throughput. With sane scenario design and the right integrations, you can build reliable, repeatable automation-without writing a single line of code.

Python Web Scraping: Practical Ways to Bypass Anti-Bot Protection (Proxy Rotation, CAPTCHA Services)

Markus — Thu, 18 Sep 2025 08:46:47 +0000

Scrapers hit tripwires sooner or later. Sites rate-limit IPs, drop tricky CAPTCHAs, or stack other checks. Here’s how to set up Python scraping that keeps moving when defenses kick in.

In real projects you don’t get a dozen silver bullets. Without heavy custom R&D, two routes cover most needs. Rotate proxies to spread traffic. Send CAPTCHAs to services like 2Captcha or SolveCaptcha for tokens or text answers.

Web Page Scraping and Blocks: Quick Context

Scraping means programmatic collection of site data. In Python you usually reach for requests to talk HTTP and a parser like BeautifulSoup to read HTML. That works until the target guards the door.

Two headaches pop up most often.
IP blocking. Flood one address and the server might throw 429 Too Many Requests, or shove you onto a check page.
CAPTCHA. The site asks you to prove you’re human, from a simple checkbox to image puzzles.

You might also see empty payloads. The script runs, nothing meaningful lands, and you wonder where it went. Let’s cut through what prevents that.

Proxy Rotation for Scraping

Why proxies matter
High-throughput scraping from one IP screams automation. Blocks follow. A pool of proxies lets you change source IP per request so filters back off. At scale, skipping proxies looks sloppy.

What to pick
Free lists exist, sure, but they break, lag, or come pre-flagged. You can find a gem, though it takes hustle and local knowledge. Paid options fit serious runs. Datacenter for speed and price. Residential or mobile when you need more stealth and region variety.

Python wiring

requests supports proxy dicts out of the box. To rotate, cycle a list. Clean and simple.

import requests
import itertools

# Rotating set: http/https/socks5 supported, auth optional
PROXIES = [
    {"http": "http://111.222.333.444:8080", "https": "http://111.222.333.444:8080"},
    {"http": "http://user:pass@555.666.777.888:3128", "https": "http://user:pass@555.666.777.888:3128"},
    # {"http": "socks5://127.0.0.1:9050", "https": "socks5://127.0.0.1:9050"},
]

proxy_iter = itertools.cycle(PROXIES)
test_url = "http://httpbin.org/ip"

for idx in range(3):
    prx = next(proxy_iter)
    try:
        r = requests.get(test_url, proxies=prx, timeout=(5, 10))
        print(f"Request {idx + 1} via {prx['http']} -> {r.json()}")
    except requests.RequestException as exc:
        print(f"Request {idx + 1} via {prx['http']} failed: {exc}")

You’ll prune dead proxies quickly. Some drop. Some get banned. Most teams add health checks or pay for automatic rotation. Proxies cut CAPTCHA frequency, especially on reCAPTCHA, though stubborn sites still challenge you at low rates.

CAPTCHA Types and Why They Bite

Classic text CAPTCHA
Distorted letters or digits inside an image. OCR can read toy samples. Real noise and warping wreck naive OCR.

Google reCAPTCHA v2
The well-known box. Sometimes a checkbox that checks behavior, sometimes an image grid, sometimes invisible with behavioral triggers only.

Google reCAPTCHA v3
No puzzle on screen. The script assigns a hidden score from 0.0 to 1.0 based on activity. Low score means challenge or denial. You don’t “solve” it in the usual way. You present a token with an acceptable score.

hCaptcha and FunCaptcha (Arkose Labs)
hCaptcha serves object-finding tasks and shows up on Cloudflare and others. FunCaptcha uses micro-interactions like rotate or assemble gizmos. Both change tactics often.

Other stuff
GeeTest sliders, image permutations, audio prompts, math, one-off vendor puzzles. No one-size-fits-all trick. You tailor per family.

How People Actually Bypass CAPTCHA

You have two playbooks.

1) Prevent it from showing up
Tune the scraper for human-like behavior. Slow down. Spread requests across IPs. Rotate User-Agent to mimic real browsers. Randomize delays. Avoid the same click or URL paths. Respect robots.txt. Reuse cookies so you look like one person, not a parade of strangers. This often keeps gates open. We think this saves more budget than anything.

2) Solve it when it pops
When a page throws a challenge, send it to a specialized service. The service returns a token or the answer text. Most providers combine AI with human backup. Quick ones go through models in seconds. Tough ones reach human workers and still finish within a workable window.

2Captcha leans on a global crowd to deliver consistent results for a fee per solve. SolveCaptcha uses a hybrid flow. AI answers light tasks in 2–5 seconds. If detection spikes or confidence drops, humans step in. You cover nearly every common CAPTCHA with this, at the cost of a few seconds and small spend per attempt.

Plan for that. Every solve adds latency and minor cost. Avoid challenges when you can, solve when you must.

Solving Classic Text CAPTCHAs

The problem
You get an image with scrambled glyphs and need clean text.

Approach
You can try Tesseract through pytesseract. It wins with clean fonts but falls apart on gnarly sets unless you train a serious model. Send it to 2Captcha or SolveCaptcha instead. Both accept files or base64 and return text.

Install

pip install 2captcha-python solvecaptcha-python

2Captcha example

from twocaptcha import TwoCaptcha

client = TwoCaptcha('YOUR_2CAPTCHA_API_KEY')
out = client.normal('captcha.jpg')
print("Recognized text:", out['code'])

If the image lives behind dynamic markup, grab it with Selenium, crop the element, then send base64. Same end result.

SolveCaptcha example

from solvecaptcha import SolveCaptcha

cli = SolveCaptcha('YOUR_SOLVECAPTCHA_API_KEY')
res = cli.image('captcha.jpg')
print("Recognized text:", res['code'])

Set a sensible timeout at init. If the window expires you get an error. Retry logic helps in bursts.

Beating reCAPTCHA v2

The setup
The page embeds a widget that yields g-recaptcha-response after success. You need that token.

How services handle it
You pull the sitekeyfrom the page, usually inside a g-recaptcha element or iframe URL. Send your API key, the target URL, and that sitekey to the provider. They reply with a task ID, then a token a few seconds later. You place that token into the hidden field or through JS and submit.

2Captcha

from twocaptcha import TwoCaptcha

solver = TwoCaptcha('YOUR_2CAPTCHA_API_KEY')
ans = solver.recaptcha(sitekey="SITE_KEY_FROM_PAGE", url="https://target.site/page")
token = ans['code']
print("reCAPTCHA token:", token)

Under the hood the library posts a job then polls for completion with that job ID. Same rhythm if you call the HTTP API directly.

About proxies and IP consistency
Google often checks the IP context. If your HTTP request hits the site from a German proxy but the solve came from a worker somewhere else, the site may reject the token. Providers let you pass a proxy so the solve originates from the right region and IP class.

from twocaptcha import TwoCaptcha

solver = TwoCaptcha(
    'YOUR_2CAPTCHA_API_KEY',
    defaultTimeout=120,
    proxy={
        'type': 'HTTPS',
        'uri': 'login:password@123.45.67.89:3128'
    }
)
resp = solver.recaptcha(sitekey="...", url="https://target.site/page")

Finalizing
With requests, include g-recaptcha-response=TOKEN in your POST body. With Selenium, write the token into #g-recaptcha-response and trigger the form submit or the site’s callback.

reCAPTCHA v3 and Cloudflare Turnstile

reCAPTCHA v3
No visual puzzle. You request a token that carries a score. 2Captcha supports this. You pass sitekey, pageurl, version=3, and a minimum score like 0.3 or 0.7. Submit the token the same way as v2. If the site demands 0.9 and your token doesn’t meet it, you might need better behavior signals or a more realistic browser profile. Honestly, sometimes you just tighten the traffic pattern.

Turnstile
Cloudflare’s alternative with extra checks. The page expects a cf-turnstile-response token. Both 2Captcha and SolveCaptcha return those. You send site key and page URL. Average solve time sits around seconds territory according to our analysts and field logs. Inject the token and finish the form or AJAX call.

hCaptcha and FunCaptcha

hCaptcha
Looks like reCAPTCHA but runs on a different backend. You supply sitekey and pageurl. Many sites require IP match between solve and request. Proxyless can work on some installs, not all. Safer path uses the same proxy you use for page traffic.

from twocaptcha import TwoCaptcha

s = TwoCaptcha('YOUR_2CAPTCHA_API_KEY')
r = s.hcaptcha(sitekey="SITEKEY_HCAPTCHA", url="https://target.site/page")
token = r['code']

Place it into h-captcha-response then submit.

FunCaptcha (Arkose Labs)
These puzzles need real interaction in the browser. Services still solve them. You pass public_key, often an svc_url, and sometimes a blob captured from the page. 2Captcha exposes funcaptcha for this path. SolveCaptcha supports Arkose too. Arkose checks IP carefully. Residential proxies tend to work better. The response usually contains a token and sometimes a session pair. You wire both where the site expects them.

Image Selection, Coordinate Clicks, Sliders, GeeTest

Some puzzles ask you to click objects or drag sliders. You can build a computer vision workflow or let a provider return coordinates or a finished token set.

Clicks
Send the image, ask for n clicks. The service responds with x,y pairs. You replay them with Selenium.

GeeTest
Typical flow returns values like validate and challenge along with other fields. You insert them into JS hooks or hidden inputs, then continue the site’s verification chain. Both 2Captcha and SolveCaptcha support this pattern.

Vendor CAPTCHAs from Yandex, VK, and others also show up. Most land within these same service APIs.

Helpful Python Libraries for Solving

2captcha-python
Official 2Captcha client. Covers major CAPTCHA families, proxy settings, async modes, and stays current.

solvecaptcha-python
SolveCaptcha’s client. Works with reCAPTCHA, hCaptcha, FunCaptcha, Turnstile, GeeTest, and more. Syntax stays close to 2Captcha so swapping feels easy.

captcha_solver (RuCaptcha)
Client for RuCaptcha and 2Captcha.

2captcha-solver
Third-party with focus on reCAPTCHA v2 v3, hCaptcha, FunCaptcha. Has async variants for high concurrency.

captchatools
Multi-provider wrapper. You can set a primary and a fallback. If balance runs out or latency spikes, it switches. Supports proxies and async. According to our data, teams like the failover a lot.

twocaptcha-extension-python
Glue for Selenium or Playwright so you solve in the browser context without extensions. Handy when your automation lives inside a real browser.

You’ll also find clients for Node.js, PHP, C#, Go, Java, Ruby, C++. Browser add-ons exist too. Enter your API key once and the add-on observes pages, solves challenges, and injects answers.

Conclusion

Keep your scraper looking like a person. Rotate proxies and user agents. Add jitter to timing. Persist cookies. When the site throws a challenge, ship it to a trusted solver and feed the returned token straight into the flow.

Expect solves to cost a few seconds per hit plus a small fee. Budget for retries. With that discipline you keep pulling data from guarded sites, at scale, day after day. Maybe a little luck helps too.

The Showdown of ML Models: how the web fights back against CAPTCHA solvers

Markus — Thu, 04 Sep 2025 08:54:47 +0000

Introduction: CAPTCHA and the shifting threat landscape

CAPTCHA—“Completely Automated Public Turing test to tell Computers and Humans Apart”—started life as a neat spam shield: give humans a tiny task that’s awkward for machines (warped text, pick-the-object tiles) and block the bots. That bargain held in the early 2000s. Then deep learning happened. Modern vision and speech models now crush the “classic” challenges—often cleaner, faster, and more consistently than people.

The trend line isn’t subtle. Advanced solvers routinely clear reCAPTCHA v2; many bots succeed across 85–100% of tasks while humans hover lower on single attempts, and machines are frequently quicker. In 2025, CAPTCHA data is more training set than tripwire.

So what changed on defense? We’ve entered an ML-vs-ML stalemate. Offense leans on recognition models and full-browser automation; defense stacks adaptive challenges, passive risk scoring, and UX-friendly alternatives. Below is a field guide to the current playbook, how we got here, and what’s replacing the old puzzles.

How bots got good at CAPTCHAs

The attack surface exploded with breakthroughs in deep learning and CV/NLP. That unlocked reliable solutions for tasks that used to be brittle:

OCR on distorted text. “Squiggly letters” are easy prey now; off-the-shelf nets read noisy glyphs with high reliability.
Image tiles (reCAPTCHA v2). “Find the traffic lights” is just classification/detection at scale. Solver APIs routinely hit >90% on common sets, even as providers rotate angles, crops, blur, and multi-object scenes.
Audio variants. Pump the clip through speech-to-text and move on. Extra noise and filtering slow things down, but they don’t stop automated pipelines.
Behavior impersonation. For invisible scoring (e.g., reCAPTCHA v3), attackers spin real browsers via Selenium/Puppeteer/Playwright, simulate cursor micro-jitter, scrolling, idle gaps, and request tokens from sessions “warmed” with cookies and plausible fingerprints.
Human-in-the-loop hybrids. “Solve-at-scale” farms pair nets for fast paths with human workers for edge cases, pushing success toward 100%. Think browser farms, rotating proxies, model cascades, and human fallback.

How websites raise the bar: evolving CAPTCHAs—and moving beyond them

Defense isn’t just “harder puzzles.” It’s a layered approach that mixes challenge design, passive signals, and infrastructure-level controls.

1) Make the puzzle adaptive (and weirder)

Goal: stay solvable for humans, hostile for models.

New interaction patterns. Sliders, drag-to-fit pieces, ordered clicks—tasks that tap fine motor control and short-term reasoning, forcing bespoke automation per variant.
Dynamic generation & diversity. Rotating fonts, languages, textures, object sets, and on-the-fly synthesis make pretraining less effective. Systems like “smart” CAPTCHAs randomize difficulty and style per request.
Adversarial seasoning. Subtle perturbations and style remixes that don’t bother humans but push models off-track—ML used as counter-ML.
Risk-based escalation. Low-risk traffic gets a tap-and-go; suspicious sessions see multi-step, harder flows. Net effect: humans rarely notice; automation gets the boss level.

Caveat: crank it too far and conversions tank. The art is maximizing machine pain while keeping human friction minimal.

2) Behavior analysis & “invisible” checks

The most effective “CAPTCHA” is the one users don’t see.

Telemetry & micro-challenges. In the background, scripts probe supported Web APIs, timing, rendering quirks, and proof-of-work nibbles. Odd delays or headless fingerprints push risk up.
Server-side ML scoring. Signals feed a classifier trained on massive traffic. Output is a risk score: high means block or escalate; medium triggers a lightweight challenge; low sails through.
Fully passive by default. Many flows never surface a widget at all. A badge might appear; that’s it. Only ambiguous cases bubble up a simple click.
Of course, attackers adapt: richer headless stealth, real engines, and synthetic behavior. Hence the next layers.

3) Multi-factor and off-CAPTCHA gates

For meaningful actions (auth, checkout, money moves), puzzles aren’t enough.

MFA/2FA. SMS, authenticator apps, hardware tokens, or biometrics dramatically cut automated abuse—even if a CAPTCHA is bypassed.
Contextual server rules. WAF/anti-DDoS challenge modes that trigger on anomalies: request bursts, header oddities, geo patterns. These sit in front of the app and can interpose a challenge or block entirely.
Device/browser fingerprinting. GPU, fonts, canvas/WebGL quirks, screen/resolution combos—correlate signals to spot impossible mixes and replayed identities.

4) Alternatives that don’t look like CAPTCHAs

Not every gate needs a widget.

Honeypots. Hidden fields/links that only naive bots touch. Submit with the trap filled? Drop the request.
Time-based friction. Buttons that activate after human-plausible delays, or thresholds that flag “too-fast-to-be-human” forms.
Content-aware filters. Spam classifiers on text + meta (IP, cadence) decide moderation automatically—no puzzle required.
Bot-management SaaS. Platforms like DataDome/PerimeterX/Cloudflare Bot Management classify requests in real time across dozens of signals, injecting challenges only as needed. The selling point: strong coverage with almost zero UX tax.

Taken together, modern stacks treat visual CAPTCHAs as the last guardrail. Behavioral filters, traps, rate limits, and device checks do most of the work; a puzzle appears only when confidence dips.

Solutions in practice: global vs. local ecosystems

Abroad (Google, Cloudflare, hCaptcha, etc.)

Google reCAPTCHA. From v1 text to v2 tiles to v3 scores, plus Enterprise mode with deeper analytics and integrations (e.g., WAF). Big-data advantage is real—but so are measurable bypasses under certain conditions.
Cloudflare Turnstile. “No-CAPTCHA CAPTCHA.” Mostly invisible, privacy-forward positioning, heavy on background probes and network-scale models.
hCaptcha & FriendlyCaptcha. Privacy and variety (hCaptcha), or proof-of-work puzzles computed by the user’s device (FriendlyCaptcha). Both reduce user friction, though strong ML adversaries still chip away at them.
Full-stack bot shields. DataDome/PerimeterX act as request firewalls with ML detection, challenge orchestration, and device intel.

In Russia (Yandex ecosystem and others)

Yandex SmartCaptcha. Risk-adaptive modes, widget or invisible operation, and policy controls tuned for regional compliance and infra (Yandex Cloud).
Legacy puzzle CAPTCHAs (e.g., KeyCaptcha). Game-like drag-and-fit flows—seen less today but noteworthy as early UX-first attempts.
CAPTCHA minimization. Banks/government services often defer to identity steps (SMS, state portal auth) and keep puzzles for abnormal patterns only.

The tech is convergent worldwide—what differs is integration surface (clouds, compliance, data gravity) and vendor preferences.

Conclusion: what replaces CAPTCHA

We’re past the age where “spot the bus” keeps bots out. ML closed that gap. The way forward is defense in depth: passive telemetry, robust scoring, rate shaping, device identity, and strong identity proof for sensitive actions—while reserving visual puzzles as a backstop.

Expect CAPTCHAs to morph into things that test abilities still awkward for machines (abstract reasoning, multimodal common sense, emotion-laden cues), or to disappear behind risk engines entirely. For builders, the takeaway is simple: a lone CAPTCHA is not a strategy. Ship a layered system that adapts as quickly as attackers do—and make sure legitimate users barely notice it’s there.

A Financial Deep Dive: What It Costs to Bypass CAPTCHA — and When Different Solvers Make Sense

Markus — Wed, 27 Aug 2025 08:53:45 +0000

CAPTCHAs keep websites safe from bots, but for folks automating the grind (SEO, marketing, QA), they become a recurring speed bump: they break scrapers, slow mass registrations, and clog pipelines. The market’s answer is paid CAPTCHA-solving services: fully manual (a human at the keyboard), fully automated (AI handles it end-to-end), and hybrid (algorithms chew through the easy stuff, humans catch the hard cases). We’re not touching open-source here — this article is all about commercial tools, budgets, and real-world economics. Below is a straight-shooting breakdown of what it costs to solve different CAPTCHA types (reCAPTCHA, hCaptcha, Arkose Labs, etc.), where human labor is the bargain, where AI rules, and at what scale it’s smarter to switch to bundles or subscriptions.

The Lay of the Land: CAPTCHA Types and Their Price Tags for CAPTCHA Bypassing

Prices dance to the tune of complexity. The trickier the CAPTCHA, the longer it takes to “chew,” and the higher the bill. Before you shout “why is this so expensive?!”, ask yourself: what exactly are you trying to solve?

Google reCAPTCHA. The most ubiquitous family (v2, v3, Invisible). On crowd platforms, reCAPTCHA v2 typically lands at $1–3 per 1,000. On 2Captcha that’s $1–$2.99 per 1,000 solved v2 prompts. AI services usually come in lower: ~$1 or less per 1,000.

hCaptcha. Cloudflare’s favorite. In both complexity and pricing it sits broadly in the same ballpark as reCAPTCHA. Many providers quote $1–2 per 1,000 for manual solving; automated APIs often hover at ~$1 or less per 1,000.

Arkose Labs (FunCaptcha). Boss-fight tier: interactive 3D puzzles. The bill jumps noticeably — ₽160–₽3000 per 1,000 (or roughly $30–$35 per 1,000 at peak difficulty). In this roundup, Arkose is the priciest creature in the CAPTCHA zoo.

Why reCAPTCHA Bypass Is So Cheap: What’s Inside the Price

Simple mechanics. reCAPTCHA v2 draws from a small, repetitive task pool (classic: pick the traffic lights on a 3×3 grid). YOLO-style models have been “snapping” these for ages.

Scale squeezes margins. Millions of daily challenges create volume, and volume pushes unit margins down. Crowd services spend about $0.40 per 1,000 on operator pay; AI services spend on servers, GPUs, and proxies. At this scale, the per-challenge cost sinks to fractional cents.

Engineering overhead. API/SDK support, ban resistance (proxy pools, anti-detect), quality control (retries/adjudication), refunds for bad solves — all tiny line items that get baked into the final price.

Why hCaptcha Solving Costs More — Complexity → Cost (Makes Sense)

Tasks keep shifting. hCaptcha rotates task phrasing and categories aggressively. Add behavioral signals — mouse movement, browser fingerprints, statistical scoring — and you’ve got extra layers of pain for automation.

R&D and re-training. To maintain accuracy, AI providers must constantly harvest fresh datasets and re-train models. That means GPU hours, annotation spend, and engineers on staff. Result: automated hCaptcha pricing tends to ~$0.90–$1.5 per 1,000, while manual solving stays around $1–2 per 1,000.

The proxy tax. hCaptcha often sits behind Cloudflare, which nudges you toward warm residential or mobile proxies with decent reputation. Some vendors bundle proxies; others don’t — and your total cost of ownership per solve climbs.

Why Arkose Labs (FunCaptcha) “Bites”: Where the High Price Comes From

The nature of the puzzles. Arkose MatchKey is a collection of interactive 3D mini-games with a huge permutation space. Training a robust, general-purpose solver is both slow and expensive.

Automation rarely saves the day. Most AI solvers tap out here, so providers route these challenges to humans. Harder tasks → longer solve times → higher pay.

Operator scarcity. Not every worker wants to wrestle complex 3D scenes, so services sweeten the pot with bonuses. Market reality: $30–$50 per 1,000 isn’t unusual.

Infra overhead. Beyond labor, you’re looking at buying Arkose challenge packs, storing/processing heavier graphics, maintaining high-reputation proxies, and shipping constant updates — all of which stack into the final number.

What Else Nudges the Price of CAPTCHA Bypassing (Beyond CAPTCHA Type)

Quality guarantees. Double-solving (sending a challenge to multiple humans) boosts accuracy but inflates cost.

SLA speed. Need responses “right now”? Providers must keep more capacity idling on standby — urgency comes with a premium.

Volume & discounts. Big buyers get deposit bonuses and better unit rates. Retail pricing for smaller customers is naturally higher.

FX & risk. Many operators are in developing regions; currency swings and regulatory friction get priced into reserves and margin.

Business math. Revenue per 1,000 − (labor/inference + proxies/servers + R&D + risk) = margin. reCAPTCHA is cheap because automation is cheap; hCaptcha costs more due to model upkeep; Arkose is barely automatable — hence the order-of-magnitude difference.

Quick note: prices are quoted per 1,000 CAPTCHAs. Need only a hundred? That’s pocket change. But at tens of thousands and up, even a $1 difference per 1,000 becomes real money.

The CAPTCHA-Solving Ecosystem: Who Solves What and How

Three main camps:

Manual (crowd). Humans handle the challenges.
Automated (AI). Models solve without human intervention.
Hybrid. Algorithms do the easy stuff; humans get the edge cases.

Manual CAPTCHA Solvers (Crowdsourcing)

2Captcha / RuCaptcha. The genre classic. Thousands of operators worldwide. Pricing $1–$3 per 1,000 (simple images closer to $0.5–$1; reCAPTCHA and tougher jobs ~$2–$3). RuCaptcha’s ruble rates track similarly (e.g., reCAPTCHA v2 ~₽65–₽160 per 1,000). Speed is middling (~10–30 s per challenge), queue-dependent. On simple tasks, accuracy is near perfect.

Anti-Captcha. Same model: broad coverage (reCAPTCHA v2/v3, Enterprise, hCaptcha, GeeTest, etc.), with pricing around $0.7–$2 per 1,000. Throughput and accuracy are comparable to 2Captcha.

Other players. DeathByCaptcha, ImageTyperz, and more. Many blend human labor with light automation for speed. Pricing ~$1.39–$3.99 per 1,000. Humans are universal (they’ll tackle rare types), but real-time performance can dip at peak times.

Automated CAPTCHA Solvers (AI)

CapMonster Cloud. Neural network solver in the cloud — no humans. The hook: multiple times cheaper than manual. Simple images ~$0.3 per 1,000, reCAPTCHA v2/v3 at fractions of a cent; latency often < 1 second. Caveat: exotic or brand-new types may underperform until models catch up (typical accuracy on mainstream tasks ~95–99%).

Local installs. XEvil, CapMonster Pro — licenses you run on your own infra. One-time purchase; then near-zero marginal inference. But you pay in servers, proxies, and maintenance. Worth it at massive, steady throughput.

Hybrid CAPTCHA Solvers (AI + Humans)

SolveCaptcha. AI clears the bulk; operators pick up the hard cases. Pricing stays low — ~$0.5 per 1,000 for standard tasks, with support for reCAPTCHA v2/v3, FunCaptcha, ClickCaptcha, etc. Faster than pure manual thanks to AI triage; reported accuracy up to 99% via human top-offs. Constraint: AI throughput caps during spikes.

DeathByCaptcha as hybrid. Auto + humans, but pricing often $0.99–$3.99 per 1,000, notably higher than leaner hybrids — more focused on the English-speaking market and integrations.

TL;DR of the landscape. Manual is universal but slower and pricier. AI is lightning fast and dirt cheap per unit, but doesn’t cover everything. Hybrids try to bottle both: AI’s economy + human reliability — often the most balanced price/perf for production.

Budgets by Scenario: Counting Money Without Illusions

Scenario 1 — One-off tests (small volume).
A QA script, a couple of manual signups — 100–500 CAPTCHAs/month. Even at $2/1,000, 500 solves ≈ $1. Pick whatever’s handy (2Captcha, SolveCaptcha), ignore bundles/subscriptions. Some hybrids offer trials — nice to have, not essential.

Scenario 2 — Daily scraping (medium volume).
Say you run ~10,000 CAPTCHAs/day (≈ 300k/month). Manual at $2/1,000 → ~$600/month. Hybrid at $0.5/1,000 → ~$150. AI at $0.3/1,000 → ~$90. Important: AI accuracy is usually 95–96%, and retries are billable; hybrids often don’t charge for unsolved cases. At 300k/month the delta is small, but at millions it snowballs. For steady scraping, AI/hybrids usually win. Confident in your volume? Look at bundles (500k+ often unlocks serious discounts).

Scenario 3 — Mass registrations (large volume, tough types).
Plan: 50,000 accounts, 1–2 CAPTCHAs each → roughly ~75,000 solves with a mix of reCAPTCHA and Arkose. Manual Arkose at a floor of ₽160/1,000 across ~25k puzzles is ₽4000 ($40). The remaining 50k reCAPTCHA at ~$1.5/1,000 adds ~$75. Total ~$115. A hybrid can compress this to ~$50 (AI eats most reCAPTCHA). Pure AI can be even cheaper per attempt, but Arkose often breaks automation. Pragmatic split: AI for reCAPTCHA/hCaptcha, manual for Arkose. Real-world total ~$60 instead of $115. At bigger scales, mixing methods nearly always reduces blended unit cost.

Bundles vs. Subscriptions: When to Flip the Switch

Bundles (prepaid). Buy volume upfront, drop the effective unit price. Great when your flow is stable and you’ll burn through the quota; downside is cash locked in.

Subscriptions (unlimited). Some providers offer flat monthly plans. The classic is $24.99/month “all you can solve.” With 300k/month, that beats paying $90–$150 a la carte. Find your break-even: if $25 covers >25k at $1/1,000, everything above is upside. Watch the fine print: speed, concurrency, and “fair use” caps.

Roll your own (capitalized). Buying a license (XEvil/CapMonster Pro) turns OpEx into CapEx. A $50 license “pays for itself” at ~50k solves (vs $1/1,000). After that, marginal cost is tiny — but you shoulder infra and maintenance; if CAPTCHA types shift, the investment can stall. This shines at huge, steady volumes.

Summary. For small/medium workloads, pay-as-you-go is fine. At tens of thousands per month, run the numbers on bundles/unlimited. At hundreds of thousands or millions, evaluate licenses and hybrid strategies.

Final Note

Bypassing CAPTCHAs isn’t just engineering — it’s arithmetic. Prices range from pocket-change to dozens of dollars per thousand, depending on the protection and the solving method. reCAPTCHA and hCaptcha sit in the “moderate” band for manual solvers and much cheaper with AI. Arkose Labs is pricey and tricky — factor it into mass signups and risk strategy.

Don’t choose out of habit. Manual platforms solve anything but cost more and move slower. AI is near-instant and almost free per unit, but doesn’t cover the whole menagerie. Hybrids are the production sweet spot. At small volumes, pricing barely matters. At tens of thousands, always model TCO: line-by-line comparisons of per-solve pricing, bundles, and subscriptions.

And yes, money talks — but architecture walks. Blend services to fit your reality: AI for the bulk, humans for hard mode. Do that, and you’ll squeeze maximum value from your budget while keeping pipelines fast, stable, and predictable.

Comparing CAPTCHA-Solving Services: Beyond Pricing, Inside the Tech

Markus — Tue, 19 Aug 2025 07:39:24 +0000

CAPTCHAs were invented to keep bots at bay, but in testing and automation they often become obstacles that need to be bypassed. Over the years, specialized services have emerged to handle this problem — relying on a mix of human workers and machine learning to decode challenges at scale.

In this article, we’ll walk through four of the most notable platforms — 2Captcha, SolveCaptcha, AntiCaptcha, and DeathByCaptcha. Instead of just looking at price tags, we’ll break down architecture, supported puzzle types, speed, reliability, APIs, and what makes each platform unique.

This is a technical deep dive designed for developers: you’ll see comparison tables, pros and cons, and a discussion about which tool makes the most sense for different automation scenarios.

CAPTCHA Bypass Services - Main Players

2Captcha — A long-time veteran with one of the largest pools of human solvers worldwide. This gives it nearly universal coverage: from old-school text CAPTCHAs and reCAPTCHA in all its forms, to regional challenges (Yandex, VK) and niche formats like image rotations. The service is basic but effective, with a minimal web interface, browser add-ons, and a straightforward HTTP API.

SolveCaptcha — A newcomer (2024/2025) with a hybrid twist. It markets itself as a fast, AI-first service: easy puzzles are handled by neural networks in a few seconds, while multi-step or tricky cases are redirected to humans. This way, the platform aims to combine speed with reliability. Its API is a drop-in replacement for 2Captcha, plus it offers a Chrome/Chromium extension. Support spans nearly every modern type — from reCAPTCHA v2/v3/Enterprise to Cloudflare Turnstile and Arkose FunCaptcha.

AntiCaptcha (AntiGate) — Operating since 2007, AntiCaptcha also leans heavily on human workers but has built infrastructure that scales easily. Its integrations stand out: JSON task-based API, unlimited thread handling, browser plug-ins, and official SDKs for Puppeteer, Selenium, and iMacros.

DeathByCaptcha (DBC) — Another long-standing service, with over 15 years of operation. One of the first to adopt a hybrid OCR+human model, it auto-solves simple CAPTCHAs in seconds and passes the rest to people. DBC covers not just visual puzzles but also audio CAPTCHAs, which makes it unique. Its API clients span multiple languages and even mimic other service protocols for compatibility.

What CAPTCHA Types Each CAPTCHA Bypass Services Supported

All four platforms cover the basics: reCAPTCHA (v2, v3, Invisible, Enterprise), hCaptcha, Arkose FunCaptcha, Cloudflare Turnstile, and GeeTest.

2Captcha: famous for handling rare and local formats.
AntiCaptcha: supports “custom tasks,” where workers can perform arbitrary scripted actions.
DeathByCaptcha: notable for audio CAPTCHA support.
SolveCaptcha: aims for full coverage with automatic detection.

APIs and Integration of CAPTCHA Solve Services

2Captcha: classic two-step HTTP model (in.php + res.php), with optional callbacks. Extensive language support.
SolveCaptcha: 100% API-compatible with 2Captcha, with client libraries on GitHub and a Chrome extension.
AntiCaptcha: modern JSON task system (createTask / getTaskResult), no thread limits, SDKs for major automation frameworks.
DBC: multiple API protocols, including compatibility with AntiCaptcha and DeCaptcher.

Speed and Scale of Each CAPTCHA Bypass Services

SolveCaptcha: 3-5 seconds on simple CAPTCHAs, ~8-13 seconds for reCAPTCHA v2.
2Captcha: 7-20 seconds depending on solver availability
AntiCaptcha: typically 10-20 seconds, faster for simple images.
DBC: OCR ~9 seconds; human involvement 15-30 seconds.

For parallelism: AntiCaptcha and SolveCaptcha are built for high-volume workloads; 2Captcha can handle spikes thanks to its workforce, though queueing delays may occur; DBC can throttle with surge pricing during peak times.

Accuracy and Reliability of Each CAPTCHA Recognition Services

Across the board, accuracy rates hover around 95-99% when humans are in the loop. Simple text puzzles are almost always correct on the first attempt. All four platforms offer refunds or error reporting for failed results.

Uptime is strong: AntiCaptcha advertises 99.99% availability since 2007, 2Captcha is rarely down, SolveCaptcha (as a newer player) has had no major outages so far, and DBC is generally stable despite occasional hiccups.

Developer Experience and UX of Each CAPTCHA Bypass Service

2Captcha: minimal dashboard; massive amount of community knowledge and third-party tutorials.
AntiCaptcha: feature-rich dashboard with logs, guides, and onboarding.
SolveCaptcha: modern SaaS-style interface, load graphs, bid controls, interactive docs.
DBC: simple panel, less polished, but functional.

Docs vary: 2Captcha and AntiCaptcha are the most extensive, SolveCaptcha is clean and beginner-friendly, while DBC benefits from protocol compatibility (you can reuse AntiCaptcha docs).

Support:

SolveCaptcha stands out for fast responses (24/7, email + Telegram).
2Captcha has tickets, email, and active community forums.
AntiCaptcha provides support, though feedback suggests mixed responsiveness.
DBC relies on tickets and email, but availability is limited outside business hours.

Pricing of Each CAPTCHA Solve Services

All four operate on a pay-as-you-go model, charging per solved CAPTCHA. Prices range roughly between $0.5-$3 per 1,000 CAPTCHAs, depending on type and service. AntiCaptcha is the only one offering subscriptions for predictable volumes.

Payment methods include bank cards, crypto (Bitcoin, USDT), and e-wallets. 2Captcha accepts the widest range (including Qiwi and mobile top-ups). DBC offers discounts for crypto and bulk deposits.

Community and Reputation of Each CAPTCHA Solve Services

Each service has an active user base:

2Captcha — valued for scale and long-standing reliability
SolveCaptcha — recognized as a fast and modern newcomer.
AntiCaptcha — preferred for enterprise-level workloads.
DBC — still relevant thanks to hybrid workflows and audio support.

Bottom Line

CAPTCHA-solving platforms have matured into ecosystems where human labor and algorithms work side by side. The four reviewed services share the same foundation — affordable solving with high accuracy — but differ in strengths:

2Captcha: the all-rounder with unmatched coverage and a massive worker pool
SolveCaptcha: cutting-edge performance, best when speed is non-negotiable
AntiCaptcha: infrastructure built for scale, with extra flexibility.
DeathByCaptcha: hybrid workflows, audio handling, and legacy compatibility.

For developers, the right choice depends on your workload: small scripts, high-volume pipelines, or edge cases like audio. In many setups, mixing services ensures stability. One thing is certain: CAPTCHAs are no longer the end of automation — just another step in the pipeline.

Service - Approach - Typical Cost - Avg. Solve Time - Supported Types - API & Tools - Stand-out Features

2Captcha - Human workforce - $1-3 / 1,000 reCAPTCHAs$0.5 / 1,000 images - 15-30s (reCAPTCHA)<10s simple _- Nearly all: reCAPTCHA, hCaptcha, FunCaptcha, GeeTest, Yandex, VK - _Classic HTTP API, pingback, libs for major languages, browser extensions - Largest worker pool, Android app for solvers, huge community footprint

SolveCaptcha - Hybrid (ML + human) - $0.5 / 1,000 images$0.55 / 1,000 reCAPTCHAs~$2.99 / 1,000 FunCaptcha - 8-13s (v2)2-3s (v3)3-5s OCR - reCAPTCHA v2/v3/Enterprise, hCaptcha, FunCaptcha, Turnstile, GeeTest, more - 2Captcha-compatible endpoints, GitHub libs (8 langs), webhook, Chrome add-on - Launched 2024, AI speed boost, full compatibility, 24/7 support

AntiCaptcha - Human workforce - $1 / 1,000 reCAPTCHAs$0.5 / 1,000 images - 15-25s (v2)5-15s simple - All major + custom tasks (reCAPTCHA, hCaptcha Enterprise, Turnstile, FunCaptcha, GeeTest v4) - JSON task API, no thread limits, browser plug-ins, SDKs (Selenium, Puppeteer, iMacros) - Running since 2007, 99.99% uptime, subscription option

DeathByCaptcha - OCR + human hybrid - ~$1-3 / 1,000dynamic surge pricing at peaks - 9s OCR15-35s with humans - Wide coverage: reCAPTCHA v2/v3, hCaptcha, FunCaptcha, GeeTest v4, audio CAPTCHAs, niche types - Multiple API styles (incl. AntiCaptcha/DeCaptcher), official clients (Python, Java, C#), browser add-ons - 15+ years in market, unique audio CAPTCHA support, crypto discounts

The Business of Bypassing "I'm not a robot": Who Profits From the War on CAPTCHA - Сomparison of CAPTCHA Solving Services

Markus — Fri, 25 Jul 2025 09:43:08 +0000

In the digital economy, every website is a fortress. And at the gate stands a sentry named CAPTCHA, whose sole job is to filter out soulless bots from living customers. But what if your business is that very "robot"? If you scrape competitor prices, analyze the market, or test software, that sentry becomes your number one enemy.

It is on this battlefield that an entire invisible industry was born—services for picking digital locks. These are not mere "solvers," but complex platforms where artificial intelligence and thousands of people from around the world work side by side. We decided to conduct an audit of this gray cardinal of the internet to find out which of its players is worthy of your budget. Four gladiators will face off in our ring: the behemoths 2Captcha and AntiCaptcha, the international veteran DeathByCaptcha, and the daring newcomer SolveCaptcha.

Meet the Fighters: Whose Business Models Are Behind the Logos? How the Presented CAPTCHA Bypass Services Position Themselves

Before cracking open their tech stacks, let's understand the philosophy of each. After all, a unique business strategy is hiding behind every API.

2Captcha: The People's Champion. Imagine an Uber, but for solving captchas. 2Captcha's business model is pure crowdsourcing in its rawest form. A giant, distributed army of low-cost workers is ready to manually crack any protection, no matter how bizarre. Their secret weapon is scale. When you have workers in every time zone, you can guarantee a result almost every time. This is an industrial conveyor belt powered by human resources.

SolveCaptcha: The Tech Upstart. This player burst onto the market in 2024-2025 with a single goal: to disrupt the status quo. Their strategy is not just people, but a "centaur": a hybrid of neural networks and the human mind. The AI handles simple tasks in a flash, saving the client precious seconds and cents. But complex puzzles where the machine falters are instantly routed to human solvers. In essence, this is an attempt to dump on speed and price without sacrificing quality. Their trick for luring clients is full API compatibility with the market leader, 2Captcha.

AntiCaptcha: The Corporate Heavyweight. This veteran, on the market since 2007, realized long ago that the main client is big business. Their philosophy is precision, power, and fault tolerance for enterprise tasks. Like 2Captcha, they rely on an army of people, but their infrastructure is tailored for industrial volumes and peak loads. Their key distinction is a focus on clients for whom even a minute of downtime means losing big money.

DeathByCaptcha (DBC): The Cunning Strategist. DBC is one of the pioneers of the hybrid approach, combining machine vision and human labor for over 15 years. But there's a juicy detail: industry rumors suggest that for complex tasks, they long used the API of... their competitor, 2Captcha, essentially acting as a reseller with a fancy wrapper. Whether it's true or not, this model shows just how complex the market is. Their strategy is to be flexible and compatible, even if it means "renting" someone else's capacity.

The Arsenal: What Digital Fortresses Can a CAPTCHA Solving Service Crack?

The value of any "lock-picker" is determined by the thickness of the walls it can penetrate. Today's captchas are not just crooked letters, but multi-level quests.

2Captcha possesses almost encyclopedic knowledge. Over the years, they have collected "master keys" for practically everything on the web: from all versions of Google reCAPTCHA to specific regional protections. Their "omnivore" nature is a direct consequence of their business model: when a new lock appears, the army of people learns to open it.

AntiCaptcha is no slouch in its assortment, but it adds a unique service—"special forces on demand" (Custom Tasks). Through the API, you can assign any non-standard task, for example, "complete a survey on a website," and human solvers will execute it. This is no longer just captcha solving, but a full-fledged outsourcing of microtasks.

DeathByCaptcha covers the entire gentleman's suite of protections but has a niche weapon in its arsenal—cracking audio captchas. This opens the door for automation where other services are powerless, for instance, in scenarios designed for people with visual impairments.

SolveCaptcha, as befits an ambitious newcomer, has tried to implement everything at once. Their system promises to automatically recognize the type of protection and select the right key, taking this headache away from the developer. They claim support for all popular systems with an accuracy that rivals the veterans.

Conclusion: For standard tasks like bypassing reCAPTCHA v2, any of the fighters will do. But if you need something exotic, the devil is in the details: 2Captcha is strong in unique and regional tasks, AntiCaptcha offers the services of a "digital mercenary," DBC knows how to listen, and SolveCaptcha is trying to become the universal Swiss army knife.

Plugging into the Matrix: How Easy Is It to Integrate a CAPTCHA Bypass Service into Your Business?

The key success factor is not just power, but ease of integration. Nobody needs a super-tool that requires a doctorate to operate.

API 2Captcha: The "English Language" of the Anti-Captcha World. Their API has been on the market for so long that it has become the unspoken standard. It's a simple and straightforward two-step move: send a task, get an ID; check back with the ID, grab the solution. For the lazy, there are "webhooks," where the service sends the answer to you. Simplicity and a huge community where every possible problem has already been solved are its main trump cards.

API SolveCaptcha: The "Trojan Horse" Tactic. These guys made a clever move: their API 100% mimics the API of the market leader, 2Captcha. For the client, migration is a five-minute affair: change one address and key in the code. This is a brilliantly simple way to lure clients by offering them better conditions without needing to rewrite software.

API AntiCaptcha: A Professional's Toolkit. Instead of a simple protocol, they offer a more complex but more flexible JSON API built on the concept of "tasks." It's like the control panel of an airplane compared to the steering wheel of a car. It's complex, but it gives you full control. Their main trump card is the officially declared absence of limits on parallel requests. This is an "unlimited autobahn" for those who need a lot, right away.

API DeathByCaptcha: The Chameleon. DBC's main trick is its ability to mimic third-party APIs. Their libraries can work with the protocols of 2Captcha or AntiCaptcha. This makes them the perfect "fallback airfield": if your main provider goes down, you can switch to DBC painlessly.

Integration Summary: For newcomers and those who value simplicity, the straight path leads to 2Captcha or SolveCaptcha. For industrial scales and complex projects where full control is needed, it's AntiCaptcha. And if you need flexibility and a "Plan B," take a closer look at DeathByCaptcha.

The Survival Race: Who is Faster and More Resilient? Compare CAPTCHA Bypass Services by Speed

In the world of automation, every second counts. The speed of a solution directly impacts your costs.

The Sprint (Simple Captchas): In short-distance races, the "centaurs" win. SolveCaptcha and DeathByCaptcha, thanks to their AI modules, solve text captchas in 3-9 seconds, while "human-powered" services like 2Captcha and AntiCaptcha spend 7-20 seconds on it.

The Marathon (Complex Captchas): Over long distances, like reCAPTCHA, it's not just muscle but logistics that decide the outcome. SolveCaptcha surprises again here, showing some of the best results (4-8 seconds), likely due to a pool of "warmed-up" accounts. 2Captcha and AntiCaptcha are stable marathon runners who reliably finish in 10-25 seconds.

Throughput (Scalability): If you need to send hundreds of requests per minute, the width of the "highway" matters. AntiCaptcha offers an unlimited superhighway. SolveCaptcha is a modern, multi-lane highway with a huge reserve capacity. 2Captcha is a large but sometimes congested city grid. And DeathByCaptcha can introduce "toll roads" during peak hours, raising the price to cope with the influx.

Reliability: All players claim accuracy above 95%. An important nuance is the refund policy. 2Captcha, SolveCaptcha, and DBC will refund your money for an error without issue. But AntiCaptcha has a reputation for being a service that doesn't like to admit its mistakes.

Customer Service: Who Will Shake Your Hand, and Who Will Tell You to Get Lost? Compare Support for Each CAPTCHA Solve Service

Interfaces: AntiCaptcha and SolveCaptcha offer stylish SaaS dashboards with graphs and analytics. 2Captcha is a utilitarian garage with nothing superfluous.

Support: 2Captcha and SolveCaptcha are famous for their responsiveness and willingness to help. AntiCaptcha, however, is followed by a trail of stories about rigid and non-customer-oriented communication in the spirit of "that's your problem." DeathByCaptcha helps, but only during business hours, which is inconvenient for a global business.

The Price Tag: What's the Cost of "Invisibility"? What CAPTCHA Solve Service is Cheapest

Everyone works on a "pay-for-results" model. On average, 1,000 reCAPTCHA solutions will cost you $1-3. SolveCaptcha often dumps on price thanks to its hybrid model. And AntiCaptcha is the only one to offer a business option: a monthly subscription for those with predictable volumes.

The Final Verdict: Choosing Your Weapon for Your Mission. What CAPTCHA Solve Service is Better?

The market for CAPTCHA-bypassing solutions is not just a set of utilities, but an arena with different fighters, each with their own tactics.

2Captcha is the reliable tank. Proven, all-terrain, a bit clunky, but it will never let you down. Ideal when you need maximum reliability and predictability.

SolveCaptcha is the stealth fighter jet. Fast, technological, and aimed at surgical strikes. It's your choice if every second counts and you value a modern approach.

AntiCaptcha is the industrial battleship. Built for large-scale battles and corporate clients who need unlimited power and complete control.

DeathByCaptcha is the Swiss army knife. A flexible and versatile tool that may not be the best in every category, but it is the perfect backup option and a master of specific tasks.

Ultimately, behind each of these platforms lies an entire shadow economy where neural networks and real people from all over the world make the internet a little more transparent for business. Your only task is to choose the right tool that will help you avoid getting distracted by the endless "I'm not a robot" puzzles.

AI Agents: From Board-Room Buzz to Practical Asset

Markus — Thu, 19 Jun 2025 10:33:08 +0000

Not a week passes without executives predicting that artificial intelligence will erase entire job categories. Intrigued, I set out to explore the mechanisms behind that prophecy. Early verdict: wholesale human redundancy is not on tomorrow’s agenda, yet the systems already on the market are powerful enough to alter cost structures and decision cycles today.

Defining the Agent

An AI agent is, in essence, a large language model housed inside a software shell supplied with tasks and instruments. The shell accepts live data, drafts an action plan, invokes external APIs, and corrects itself if something breaks. Metaphorically, the language model supplies intellectual horsepower; the shell lends arms and legs plus a clear business mandate. Typical mandates include full-service travel reservations, overnight email triage, and automated management reporting.

A Small Case Study: Smarter CAPTCHA Handling

Consider the mundane CAPTCHA. Developers must still specify whether the puzzle is GeeTest, reCAPTCHA or hCaptcha; mislabel it and the workflow stalls. Insert an agent at this layer and the code audits the challenge on its own, selects the right decoder and ships the answer—no conditional logic required. Only two years ago that scenario belonged to science fiction; today it appears in beta builds.

Standard Anatomy of an Agent

Planner – decomposes a strategic goal into smaller, verifiable jobs.
Memory – stores every prior step so the system retains context and learns from misfires.
Perception – reads queries, files, sensor feeds, websites—any external signal.
Action – executes calls, writes records, dispatches messages.

The cycle looks like this: input → plan → act → evaluate → write to memory → repeat.

Design Templates

Monolith vs. Ensemble
A lone multifunctional agent can clear modest backlogs, yet large projects benefit from a cast: Architect, Developer, Tester and Integrator.

Up-Front Blueprint
An Architect agent drafts the whole roadmap before a single API fires—akin to a senior engineer designing a data centre.

Relay Chain
Once the plan is frozen, specialised agents hand off work sequentially: Developer commits code, Tester probes defects, Integrator merges pull requests.

Checklist Contracts
Plans convert into granular checkpoints, each one easy to audit.

ReAct Loop
Many teams prefer an iterative “think-do-check-think” rhythm that adjusts strategy in real time.

Swarm Coordination
For heavyweight tasks—say, embedding Stripe payments into legacy code—multiple agents communicate through a graph, sharing messages and state.

Market Toolkit

Framework - Purpose - Commercial Edge

LangChain - Chains LLM calls with tools - High customisability

LangGraph - Graph view of LangChain flows - End-to-end observability

SmolAgents - Lightweight starter kit - Rapid prototyping

Auto-GPT/BabyAGI - Open-source autonomous demos - Experimental automation

Copilot / Bedrock / ADK - Big-tech cloud wrappers - Integrated enterprise stack

Many developers mix and match: LangChain drives orchestration, Hugging Face hosts the model, cloud Copilots expose SaaS glue.

Ten-Minute Prototype (Python + LangChain)

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
ChattyAgent: compact LangChain demonstration.
"""

import os
from dotenv import load_dotenv

# --- credentials ---
load_dotenv()
API_KEY = os.getenv("OPENAI_API_KEY")
if not API_KEY:
    raise RuntimeError("OPENAI_API_KEY missing")

# --- libraries ---
from langchain.agents import initialize_agent, AgentType, Tool
from langchain_openai import ChatOpenAI
from langchain_community.utilities import WikipediaAPIWrapper
from langchain_experimental.tools.python.tool import PythonREPLTool
from duckduckgo_search import DDGS
from langchain.chains import LLMMathChain
from langchain.memory import ConversationBufferMemory

# --- search helper ---
def web_search(text: str, limit: int = 3) -> str:
    with DDGS() as ddgs:
        hits = ddgs.text(text, max_results=limit)
    if not hits:
        return "No results."
    return "\n".join(
        f"{idx+1}. {h.get('title','No title')} — {h.get('href',h.get('link',''))}"
        for idx, h in enumerate(hits)
    )

# --- toolbox ---
tools = [
    Tool("WebSearch", web_search, "DuckDuckGo internet lookup"),
    Tool("Wikipedia", WikipediaAPIWrapper().run, "Encyclopaedia fetch"),
    PythonREPLTool(),
    Tool(
        "Calculator",
        LLMMathChain(
            llm=ChatOpenAI(temperature=0, model_name="gpt-3.5-turbo", openai_api_key=API_KEY),
            verbose=True,
        ).run,
        "Math operations",
    ),
]

# --- brain & memory ---
llm = ChatOpenAI(temperature=0, model_name="gpt-3.5-turbo", openai_api_key=API_KEY)
memory = ConversationBufferMemory(memory_key="history", return_messages=False)

# --- agent ---
agent = initialize_agent(
    tools=tools,
    llm=llm,
    agent=AgentType.CHAT_ZERO_SHOT_REACT_DESCRIPTION,
    memory=memory,
    verbose=True,
)

# --- CLI loop ---
def main() -> None:
    print(">>> Agent online. Type 'exit' to quit.")
    while True:
        user = input("\nYou: ")
        if user.lower() in {"exit", "quit"}:
            break
        try:
            reply = agent.invoke(user)
        except Exception as err:
            reply = f"Error: {err}"
        print(f"\nAgent: {reply}")

if __name__ == "__main__":
    main()

Operational Highlights
Credentials load from .env.
Tools cover search, reference, Python execution and maths.
Memory stores dialogue for context.
The ReAct engine decides which tool to deploy each turn, yielding an expandable, ChatGPT-like console.

Business Scenarios Already Live

Software Delivery – Agents now draft code, assemble tests and patch vulnerabilities, trimming sprint overhead.
Knowledge Search – They query databases and knowledge graphs, returning causal explanations, not mere text snippets.
Client Support – Context-aware chatbots can authorise refunds or book appointments without human routing.
BI & Document Flow – Systems distil bulky reports into dashboards or auto-filled templates.
Personal Productivity – Assistants can coordinate travel, steer smart devices and maintain calendars autonomously.

Constraints to Monitor

Fragile Planning – Large models still hallucinate; multi-step logic needs supervision.
Context Limits – Long dialogues risk truncation unless augmented memory is in place.
Debug Difficulty – Traditional unit tests reveal little about emergent reasoning chains.
Data Exposure – Logs and third-party calls can leak confidential fields.
Compute Cost – Unbounded loops chew through GPU hours and API quotas.
Security Gaps – Prompt injection or tool abuse may trigger harmful calls.

No agent handling critical data should run without circuit breakers and rollback policies.

Security Agenda

Sandboxing, detailed audit trails, rate throttling, dependency vetting and minimal privilege remain non-negotiable. Corporates increasingly enforce an “explain-before-execute” rule: the agent must justify major actions to a human supervisor.

Testing Methodology

Sandbox runs intercept every tool call.
Edge-case suites probe malformed inputs and network failures.
Instrumentation records every internal decision.
Module unit tests isolate connectors and memory routines.
Hybrid metrics mix LLM accuracy scores with classic coverage ratios.
Human inspectors sign off before production deployment.

Iterative cycles—generate, execute, autopsy, improve—remain the only route to stable behaviour at scale.

Outlook

AI agents are shifting from laboratory novelty to line-item in IT budgets. Frameworks such as LangChain and LangGraph reduce entry barriers, yet expanded autonomy raises exposure. Deployed wisely, agents already compress timelines for code delivery and client service; deployed recklessly, they invite headlines no risk officer wants to read. Market momentum suggests agents will soon rank alongside RPA and microservices as default enterprise components. Executives would do well to audit use-cases now—before the competition trains its own digital staff.

AI vs. CAPTCHA—Setting the Scene - How AI CAPTCHA Solver conquer the market

Markus — Wed, 04 Jun 2025 06:55:13 +0000

CAPTCHAs—those warped phrases, tile grids (“click every traffic light”), and garbled voice clips—are now internet staples, separating flesh-and-blood visitors from automated scripts. Anyone who writes bots or runs end-to-end QA tests has seen an otherwise flawless routine crash the instant a CAPTCHA appears. The obvious follow-up: Can software match human speed and accuracy at cracking these tests? This guide walks through the answer, tracing the journey from early OCR tactics to today’s deep-learning powerhouses.

Catalog of CAPTCHA Formats and Their Pitfalls for Bots - What do AI CAPTCHA Solvers Encounter

Format - What Users See - Why It Trips Code

Distorted Text -Skewed letters/numbers to type in - Overlapping glyphs break classic OCR segmentation

reCAPTCHA v2 - Checkbox + 3×3 image grid - Requires image-content recognition and behavioral cues

reCAPTCHA v3 / Cloudflare Turnstile - Invisible; score computed in the background - Bot must mimic dozens of micro-behaviours—timing, focus shifts, GPU fingerprint

hCaptcha / FunCaptcha - Photo sets or mini 3-D games - Each provider rotates its visual puzzles to foil training data

GeeTest-style Jigsaws - Drag slider to fit puzzle piece - Needs both computer vision and human-like mouse motion

Audio Challenges - Noisy recording of digits/words - Modern ASR chips away, but heavy distortion raises WER for machines

Behavioral “Honeypots” - Hidden form fields, timing traps - Purely checks authenticity of interaction, no puzzle to “solve”

Key takeaway: every variety targets a different machine weakness, so a universal solver must be multi-modal—text, images, acoustics, and behaviour modeling all at once.

Historical Tactics: From Rule-Based Filters to Deep Nets - History of CAPTCHA AI Solvers

1 Classic OCR Era

Early scripts cleaned backgrounds, sliced each character, and ran template or Tesseract recognition. Worked fine until creators added colored noise, random fonts, and merged glyphs.

2 Escalation and Machine-Learning Counterpunches

As CAPTCHAs grew noisier, researchers switched to SVMs and decision trees trained on labelled symbols. Gains were incremental.

3 Deep-Learning Breakthrough

Google’s 2014 study was the watershed: a convolutional network hit 99.8 % on the toughest text puzzles, outperforming average humans. Text-only CAPTCHAs were effectively obsolete; Google pivoted its own product to image grids and behavioural scoring soon after.

Modern Neural Arsenal - Best AI CAPTCHA Solvers

Model Family - Core Strength - CAPTCHA Use Case

CNNs - Spatial feature extraction - Single-symbol ID, photo-tile object detection

RNNs / LSTM / GRU - Sequence memory - Audio CAPTCHAs, left-to-right text decoding

CRNNs - CNN front + bi-LSTM tail - End-to-end reading of entire warped word images

Transformers (ViT, Swin) - Global self-attention - Scene-based puzzles, hybrid image-text prompts

GANs - Synthetic data generation - Infinite training samples with evolving distortions

Real-world metric: a CRNN trained on 20 000 synthetically generated images solves previously unseen text CAPTCHAs in < 30 ms with > 98 % accuracy.

Implementation Playbook—Tools, Code, and Services - Has Free AI CAPTCHA Solver?

1 Open-Source Repositories

CAPTCHA-Solver (PyTorch): script to generate training data, train CNN-BiLSTM-CTC, and benchmark.
Buster Browser Add-on: plays reCAPTCHA audio, pipes to Google Speech-to-Text, pastes answer automatically.
captcha (Python): dataset generator—custom fonts, wavy lines, color gradients.

2 Commercial APIs

Provider Type - Examples - Avg. Solve Time - Success Rate - Cost / 1 000

Human Crowd - 2Captcha, Anti-Captcha - 7–20 s - ≈ 99 % - $2 – 3

Pure AI - noCaptchaAI - ~5 s - up to 99 %* - $0.8 – 1

Hybrid - SolveCaptcha - 5–15 s - 99.9 % - $1 – 2

* Accuracy dips when a brand-new puzzle style launches, until the model is retrained.

Why Deep Nets Work Better - What the better Human CAPTCHA Solver or AI CAPTCHA Solver

No manual segmentation: CTC-based networks align predictions to variable-length ground truth automatically.
Domain transfer: Fine-tune once, apply to a cousin CAPTCHA with minimal extra data.
GPU-level speed: Tens of milliseconds per frame; bottleneck is often browser automation, not inference.
Synthetic training data: GANs or image-processing pipelines create millions of variations overnight.

Strategic Implications for Site Owners

Visual distortion alone is no longer sufficient — add behavioural analysis or token-based risk scores.
Rotation of puzzle styles must be frequent; static datasets give solvers time to retrain.
Accessibility trade-offs: tougher audio CAPTCHAs may lock out visually impaired users.
Server-side profiling (TLS fingerprint, WebGL hash, interaction entropy) is emerging as the long-term defence.

Forecast—Toward a Post-CAPTCHA Web for AI CAPTCHA Solvers

AI now reads messy text, spots objects, and parses noisy audio at or above human level. Providers are leaning into invisible checks that weigh device reputation and real-time behaviour. In the future, cryptographic client attestation (think WebAuthn tokens or hardware-bound proofs) could replace puzzle challenges altogether.

Bottom line: the battle is shifting from “solve this riddle” to “prove you’re a trustworthy endpoint.” Developers building either side of the fence should plan for multi-factor, continuously learning systems—because static obstacles, however clever, won’t stand up to the next neural upgrade.

Browser CAPTCHA Solver Extension: where the balance of power now lies between algorithms and human typists

Markus — Tue, 27 May 2025 09:18:05 +0000

Why “free of charge” almost never means “cost-free” and what determines the economics of outsourced recognition

The moment the developer hits a dead end or why you need Auto CAPTCHA Extension

A software engineer automates acceptance tests, a data-scouting start-up builds a harvesting bot, an investment analyst installs a screen-scraper to keep track of competitors’ prices. In every story the first batches run perfectly—until the browser displays the dreaded panel: a check box saying I’m not a robot or a mosaic of photographs demanding every picture with a pedestrian crossing. The pipeline grinds to a halt, and the junior specialist scrolls through endless logs without understanding why the routine fails. The culprit is the CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart)—a barrier expressly created to repel automated traffic.

If the bot belongs to the company and serves an entirely lawful objective, the engineer must either remove the obstacle or arrange for automatic bypass. From that point the market offers two conceptual routes:

In-house scripting. The team writes a bespoke solver, assumes the legal and technical maintenance burden and wins full control—but only as long as new puzzle formats do not appear.
Delegation to a third party. The firm buys capacity from a remote provider that guarantees delivery of ready-made tokens in return for micro-payments. The service cost is booked as an operating expense; all algorithmic headaches are outsourced.

This survey examines three plug-ins that illustrate the spectrum of commercial proposals:

SolveCaptcha – a subscription platform marrying machine-learning models with hired operators;
Buster – an open-source extension that eliminates only Google’s voice check and charges nothing;
2Captcha – a mature marketplace with thousands of home-based workers entering codes day and night.

A note on methodology: dozens of smaller products exist, yet the chosen trio maps the principal business niches, and further multiplication of examples would only blur the picture.

2. Why robots stumble where humans glide - CAPTCHA Solver Extension

Category - Typical riddle - Built-in defence

Classic image CAPTCHA - Deformed letters or numbers that must be typed - Basic OCR can handle easy specimens; aggressive distortion still confuses software

Google reCAPTCHA v2 - Check box plus image grid—or invisible widget monitoring mouse moves - Behavioural analysis assigns risk before any picture is shown

reCAPTCHA v3 / Cloudflare Turnstile - No user input; system silently generates a risk score - Back-end validation via token with minimal threshold

hCaptcha / FunCaptcha (Arkose) - Proprietary 2-D and 3-D puzzles, rotating objects, drag-and-drop tiles - Frequent updates, device fingerprinting

GeeTest - Slider puzzles and jig-saw fragments, common in China - Challenge–response pair with time stamp and mouse-path verification

Audio CAPTCHA - Distorted spoken digits for visually impaired visitors - Automatic speech recognition (ASR) must cope with synthetic noise

Because the defensive arsenal evolves continuously, a “solve-everything engine” remains an elusive target for software architects.

3. Inside any Browser Anti CAPTCHA Extension Solver: Four Mandatory Stages

Widget discovery
A content script inspects the Document Object Model (DOM) for tell-tale elements—<div class="g-recaptcha">, an iframe from google.com/recaptcha, a class h-captcha, or dynamically injected JavaScript. The plug-in harvests the site-key, the URL, and links to images or audio.
Task dispatch
Collected parameters travel to the supplier through a REST interface; authentication rests on the customer’s API token. Graphic CAPTCHAs may be uploaded as binary blobs; reCAPTCHA and hCaptcha are usually identified by public key and page address; audio files are fetched by the extension and forwarded likewise.
Token injection
The plug-in polls the API every few seconds (or listens to a WebSocket) until the answer arrives, then populates hidden fields such as g-recaptcha-response, programmes a JavaScript callback and, where necessary, emulates a mouse drag. To the hosting website the sequence is indistinguishable from genuine human input; in many cases the user never sees the challenge.
Token injection
The plug-in polls the API every few seconds (or listens to a WebSocket) until the answer arrives, then populates hidden fields such as g-recaptcha-response, programmes a JavaScript callback and, where necessary, emulates a mouse drag. To the hosting website the sequence is indistinguishable from genuine human input; in many cases the user never sees the challenge.

Chrome, Edge and Firefox restrict such activities to content scripts with declared permissions; Manifest V3 additionally obliges developers to migrate long-running background pages to service workers, cap memory footprints and abandon blocking webRequest. Both commercial plug-ins reviewed below have converted their code bases accordingly.

4. SolveCaptcha – betting on neural speed of Auto CAPTCHA Extension

4.1. Commercial positioning

SolveCaptcha entered the Chrome Web Store in early 2025 and immediately adopted the rhetoric of a “full-cycle recognition platform”. The company sells credits in blocks; unused balance carries forward without expiry. Management emphasises compliance: traffic is routed through European servers, GDPR requests are honoured, and the extension sits in the Accessibility catalogue rather than in Productivity, a diplomatic gesture towards browser moderators.

4.2. Technical workflow

Fast lane – distorted texts, simple picture grids and numeric audio are processed by proprietary CNN and ASR models in 2-5 s.
Slow lane – multi-layer FunCaptcha or Arkose rotation tasks are escalated to freelance staff, average turnaround 25-35 s.
Slow lane – multi-layer FunCaptcha or Arkose rotation tasks are escalated to freelance staff, average turnaround 25-35 s.
Behaviour lane – reCAPTCHA v3 tokens require a minimum confidence score (0.3 to 0.9 chosen by the client). SolveCaptcha spins up headless Chromium instances, injects realistic mouse paths and keyboard events and secures a token in ≈ 3 s, falling back to live workers if Google raises suspicion.

4.3. Price list (USD per 1 000 tasks)

Format - Median time - Tariff

Text or math image - 3-5 s - 0.35

reCAPTCHA v2 - 5-12 s - 2.00

reCAPTCHA v3 (score ≥ 0.7) - 2-3 s - 2.20

GeeTest - 11 s - 0.80

Cloudflare Turnstile - 14 s - 0.80

FunCaptcha (simple) - 25 s - 2.99

FunCaptcha (bank grade) - 30-60 s - up to 50.00

4.4. Integration highlights

Ready-made ZIP bundle for Chrome headless; CI orchestration via command line --load-extension.
JavaScript SDK for Node.js; Python helper on PyPI.
Webhook option for high-volume clients (reduces polling overhead).

A caveat: although the marketing page mentions hCaptcha, the current build of the plug-in lacks that module.

5. Buster – the free audio tactician of Anti CAPTCHA Extension

5.1. Niche and mechanics

Buster targets a single market niche: Google reCAPTCHA v2 where the visitor may switch from image to sound. After the user presses the extension’s icon, Buster clicks the headphones glyph, fetches the MP3, feeds it to the browser’s speech service and pastes the recognised digits. The process consumes no external API and therefore no money.

5.2. Strengths

MIT licence, code on GitHub; no telemetry beyond anonymous ASR queries.
Works in Chrome, Firefox, Edge and Opera; user base > 600 000.
Saves time for individuals who browse behind VPNs or privacy overlays and therefore meet reCAPTCHA frequently.

5.3. Restrictions

Supports only the audio branch of reCAPTCHA v2; invisible widgets without manual flip to audio cannot be bypassed.
Requires a user gesture; unsuitable for unattended crawlers and CI pipes.
Excessive volume may persuade Google to suppress the audio option entirely for the offending IP address.

6. 2Captcha – labour arbitrage at industrial scale of CAPTCHA Solver Extension

6.1. Operational model

2Captcha, founded in the mid-2010s, connects corporate customers with a distributed workforce mostly located in regions with lower wage expectations. Workers install a light client or log in via a web panel, input codes non-stop and earn between 50 cents and two dollars per hour depending on demand.

6.2. Extension capabilities

Detects reCAPTCHA v2/v3, FunCaptcha, GeeTest, Yandex, VK, KeyCaptcha, Capy and a dozen lesser formats.
Automatically pastes solutions; optional on-click approval for security audits.
Source code of the plug-in is public; customers may verify that no browsing data leaves the machine apart from the challenge payload.

6.3. Performance and charges

Category - Typical latency - Fee per 1 000

Text image - 5-10 s - 0.50

reCAPTCHA v2 - 20-40 s - 1.00–3.00

FunCaptcha - 25-45 s - ≈ 3.00

During demand spikes—Black Friday, mass airdrops in crypto, concert ticket launches—waiting time can exceed one minute, an inevitable side-effect of human throughput.

6.4. Developer resources

GitHub examples for Puppeteer, Selenium and Playwright; NPM package 2captcha generates promises that resolve when the token arrives. Documentation covers retries, error codes and minimum score negotiation for reCAPTCHA v3.

By the way, you can compare services in real time and decide which extension to use on the captchathecat service. It's a pity there is no Buster here, it would be more visual.

7. Comparative business appraisal

Factor - SolveCaptcha - 2Captcha - Buster

Technology core - Hybrid AI + human - Human majority - Browser ASR

Average turnaround - 5-20 s - 10-60 s - 10-20 s

Code transparency - Closed source - Extension open - Full source

Minimum spend - Top-up ≥ $5 - Top-up ≥ $1 - $0

Format coverage - Broad (hCaptcha pending) - Widest - One format

Headless/CI - Native ZIP build - Supported by docs - Unsupported

Main risk - Service halts if balance empty - Queue delay at peak load - Audio may vanish

Ideal user - SaaS, e-commerce scalers, QA teams - Data farms, adtech, grey-hat operators - Private individuals, accessibility activists

8. Practical deployments

Competitive intelligence. Retail chains monitor rivals’ catalogues via scraper clusters; both SolveCaptcha and 2Captcha integrate easily into Kubernetes jobs, amortising a few cents per 100 pages against multi-million revenue decisions.
Continuous delivery. Banks run nightly smoke tests on production clones; a headless Chrome with the SolveCaptcha ZIP solves login barriers automatically, ensuring that the dev-ops dashboard remains green until genuine defects arise.
Regulatory reporting. Rating agencies download thousands of annual statements from public registries protected by GeeTest; integrating a solver prevents manual batch-keying or illegal scraping via shared passwords.
Accessibility services. Public libraries deploy Buster on patron PCs so that visually impaired readers can pass Google challenges without staff assistance.
Illicit arenas. Spam factories and sneaker bots rent vast quotas at 2Captcha rates; the provider stresses neutrality—“We only deliver tokens, client purpose is none of our business.”

9. Conclusion: choose by workflow, not by slogan

Free software is attractive until the first regression build is blocked at three in the morning. Human clouds are reliable until a flash crowd exhausts the queue. AI appears unbeatable until the CAPTCHA designer changes the distortion filter. In practice many organisations settle on a tiered defence strategy: Buster as the zero-cost first attempt; if the audio switch is absent, fall back to SolveCaptcha for speed; should loads surge beyond AI capacity, route the overflow to 2Captcha’s army.

What matters is not the marketing label—machine or human—but the balance of risk, latency and compliance that best matches the company’s automation portfolio. In that calculus, every plug-in reviewed above has a place.

FunCaptcha by Arkose Labs - how to bypass Arcose Labs Funcaptcha

Markus — Wed, 14 May 2025 07:53:45 +0000

How FunCaptcha Operates and Why It Blows Past Classical CAPTCHA Relics - why you should know it to create Funcaptcha solver

Our ongoing expedition, “Fantastic CAPTCHAs and How to Tame Them,” has reached a particularly spiky creature: FunCaptcha, forged in the laboratories of Arkose. Instead of forcing you to squint at mangled glyphs or pick every picture with a traffic light, FunCaptcha tosses you into bite-sized mini-games: 3-D puzzles, logic brainteasers, and audio riddles that feel like casual entertainment for humans yet morph into a migraine for bots.

Signature FunCaptcha Trial Types - important knowledges for bypass Arcose Labs Funcaptcha

Image Spin-Ups
A creature, tool, or doodad appears upside-down. With arrow buttons, you must twist it upright. Spatial perception is trivial for people, but algorithms frequently stumble over angle detection and object contours.
Condition-Based Selection
Think of a dice tray puzzle: “Pick the pair whose pips add to 11.” The solver needs to grasp context and basic arithmetic at image level—something generic CV still finds prickly.
Interactive Drag-and-Drop
Sometimes you slide a jigsaw piece into its socket or steer a mascot through a wireframe maze. Pattern recognition plus sequential instructions equals yet another hurdle for scripts.
Semantic Audio Quizzes
Forget the classic “type what you hear.” Arkose lines up multiple clips and asks, for instance, “Which sample is a snare drum?” or “Where is the only human voice?” The task judges comprehension, not transcription—dramatically upping the automation bar.

Because instructions lean on icons instead of words, the widget feels borderless for humans while bots must decode task meaning, not OCR. Many devs lovingly dub the system “f-CAPTCHA” for the headaches it induces.

Why Automating FunCaptcha Is Brutally Difficult and hard for Funcaptcha solver

Ever-Shifting Puzzle Library
Arkose perpetually rolls out fresh game variants. One MatchKey series alone can exceed 1,250 micro-scenarios, blowing up training-set requirements into the hundreds of thousands.
Context + Motion
The attacker has to read the rule, identify objects, and perform precise actions under varying angles, lighting, and canvas positions. Pure pattern matching crumbles.
The MatchKey Script Trap
On load, the widget injects a per-session JS blob (nicknamed dapib) that must spit out a dynamic hash—tguess—proving honest execution. Without it, even a perfect visual answer dies server-side.
Hardware & Behavior Fingerprinting
Screen size, WebGL timing, pointer cadence, historical tokens—Arkose packages everything into a stealthy “blob.” Skip legitimate browser signals, and the gate slams shut or the puzzle mutates into nightmare mode.
Strict Timers & Error Caps
Linger beyond ~15 s or bomb a handful of attempts, and the whole board reshuffles. Low-latency answers are mandatory.

Collectively, these layers demand full human-grade emulation: real browser, real 3-D interaction, and near-human reasoning.

Scouting a Site for FunCaptcha Credentials

Before you can poke Arkose’s API, you need two nuggets:

Public Key (pk)
Service URL (surl)

They’re usually embedded in a hidden input such as:

<input id="FunCaptcha-Token" name="fc-token"
 value="702178f80cd6ade39.2875608305|r=eu-west-1|...|pk=2CB16598-CB82-4CF7-B332-5990DB66F3AB|...|surl=https%3A%2F%2Fclient-api.arkoselabs.com|...">

Spot data-pkey attributes or snoop DevTools’ Network tab for calls to /fc/gfct/. Grab any optional blob while you’re there; some integrations insist on it.

“f-CAPTCHA” War Plans: Three Main Tactics

Outsource to a Paid Solver (2Captcha, RuCaptcha, SolveCaptcha, …)
Easiest. Send publickey, surl, and pageurl; wait ~20 s; receive a ready-to-inject token.

Python SDK Sketch (2Captcha):

from twocaptcha import TwoCaptcha

solver = TwoCaptcha("YOUR_API_KEY")
result = solver.funcaptcha(sitekey=PUBLIC_KEY, url=PAGE_URL, surl=SURL)
token  = result["code"]
print("Arkose token:", token)

Raw HTTP alternative:

# submit captcha
submit = f"http://2captcha.com/in.php?key={API_KEY}&method=funcaptcha&publickey={PUBLIC_KEY}&surl={SURL}&pageurl={PAGE_URL}"
cap_id = requests.get(submit).text.split('|')[1]

# poll for result
while True:
    time.sleep(5)
    res = requests.get(f"http://2captcha.com/res.php?key={API_KEY}&action=get&id={cap_id}").text
    if res.startswith("OK|"):
        token = res.split('|',1)[1]
        break

Fast, but you’re hostage to provider latency and their update cycle.
DIY & Open-Source Arsenal
Audio attack: pull legacy audio, pipe through Google STT—works only where simple digits remain.
Neural nets: train angle detectors or dice-pip counters; success stories exist but crumble on each Arkose refresh.
Arkose-specific scripts: GitHub repos reverse-engineer fingerprint blobs and tguess; combine with your own CV or manual solving.

3.Full Browser Emulation (Selenium, Playwright, Puppeteer)
Fire up Chrome, load the widget genuinely, and either…

Hand off to a paid solver — browser keeps fingerprints authentic.
Solve inline — capture canvas, run OpenCV, auto-click arrows, drag pieces, etc. Powerful yet fragile and CPU-hungry.

Hybrid stacks are common: attempt local ML first, fall back to 2Captcha on timeout.

Each Route’s Sandtraps

Paid APIs: ~15–30 s turnaround, per-solve cost, downtime on new puzzle types, IP mismatch unless proxying.
Open Source: huge data appetite, constant maintenance, many repos already stale.
Browser Bots: heavy resource footprint, headless detection, selectors break when Arkose tweaks CSS.

No silver bullet—Arkose can chain multiple mini-games or upgrade difficulty mid-flow.

MatchKey: Arkose’s Next-Gen Counteroffensive

1,250+ visual variants per challenge
Hybrid audio-visual sequences
Response-bound dynamic hashes
Dozens of semantic audio prompts with randomized noise
Built-in ML benchmarking to keep attacker cost sky-high

Still, the cat-and-mouse marathon continues; solvers iterate just as aggressively.

By the way, you can compare captcha recognition services with each other - here is a good service for comparison - captchathecat.

Choosing Your Weapon

Scenario - Best Bet

Small batch, need speed - Paid solver API

Massive scale, tight budget - Home-grown ML / audio trickery

End-to-end QA, security audits - Selenium + solver or inline ML

Mix-and-match strategies often hit the sweet spot between cost and hit rate.

Epilogue

FunCaptcha stands among the most sophisticated, bot-repellent gatekeepers alive, evolving from simple “spin the puppy” to polymorphic MatchKey gauntlets. Yet with enough ingenuity—whether rented human brainpower, bleeding-edge CV, or browser puppetry—determined developers can still slip past the barriers. Your optimal path depends on volume, wallet, and risk appetite, but remember: in this arena, today’s breakthrough is tomorrow’s baseline.

GeeTest CAPTCHA: A Technical Breakdown and Bypass GeeTest Guide for Developers

Markus — Fri, 25 Apr 2025 12:34:29 +0000

Most developers working on scraping, automation, or bot infrastructure eventually run into modern CAPTCHA systems that are specifically designed to block them. One of the most resilient among them is GeeTest CAPTCHA, a sophisticated and adaptive anti-bot solution developed in China.

In this guide, we’ll explore the inner mechanics of GeeTest, understand why it’s particularly difficult to automate, and review multiple effective strategies for bypassing both version 3 and version 4 of the system.

What Is GeeTest CAPTCHA and Why Is It So Challenging for Bypass GeeTest?

Unlike traditional CAPTCHAs that rely on static image text recognition, GeeTest introduces interactive, behavior-tracking puzzles. These puzzles often include sliders, drag-and-drop interactions, or mini-games. What makes this system unique is its deep inspection of user behavior and its device profiling techniques, which make automated solutions extremely difficult to develop.

Key Features That Complicate Automation:

Interactive Puzzles: The user is required to perform a dynamic interaction such as dragging a slider or clicking icons. These can’t be bypassed by simple HTTP requests.
User Behavior Analysis: GeeTest monitors mouse movement, speed, trajectory, and reaction time.
Device Fingerprinting: It gathers detailed data including your browser version, screen resolution, installed fonts, timezone, WebGL signature, and canvas rendering fingerprint.
Encrypted Validation: For version 4, the user’s interaction data is encrypted before being sent to the server, which validates it internally. You can’t simply spoof a token—you must generate it through the expected logic.

GeeTest CAPTCHA Version Comparison: v3 vs. v4 (What is Difficulter for Bypass)

Understanding which version of GeeTest you are dealing with is important because the logic and bypass approaches differ substantially.

GeeTest v3 (Legacy Version)

Challenge Displayed: Always visible (slider, icon CAPTCHA, etc.)
Parameters Used: gt and challenge
Typical Flow: Loads gt.js, then uses /get.php and /validate.php for request handling
Types of Challenges:

a) Slider puzzle

b) Icon click/drag CAPTCHA

c) Less commonly: space puzzles

GeeTest v4 (Adaptive CAPTCHA)

Challenge Displayed: May be silent (OneTap) or interactive
Parameters Used: A single captcha_id passed via the frontend initialization objec
Typical Flow: Uses JavaScript loader from /v4/ paths like gcaptcha4.js, interaction is encrypted into a w payload
Validation: Requires generating a fully encrypted payload with full interaction history

To Identify the Version:

If you see both gt and challenge on the page, it's v3. If you see only captcha_id and scripts loaded from /v4/, it's v4.

CAPTCHA Types Used by GeeTest - Can You Bypass Geetest?

Here are the most common types of challenges you’ll encounter:

Slider Puzzle: Drag the puzzle piece to complete the image. Requires human-like motion to pass.
Icon CAPTCHA: Click on certain icons or drag them to correct locations. Mouse movement and timing are tracked.
IconCrush CAPTCHA: A visual matching game used in v4; involves identifying and clicking a sequence of matching icons.
Gobang: A board-style game where the user places tiles. It’s generally triggered when traffic is flagged as suspicious.
Space CAPTCHA: Rare type; involves dragging elements into designated positions.
OneTap / NoCaptcha: A “Verify” button is shown. If GeeTest determines you are human based on prior interactions, no puzzle is presented.

How GeeTest Detects Automation - That Is Why GeeTest Bypass May Be Challenge

Behavioral Analysis

Mouse movement (XY coordinates per millisecond)
Smoothness and randomness of dragging
Time taken to begin interaction after challenge loads
Order and frequency of clicks

Device Profiling

User-Agent and navigator flags (e.g., navigator.webdriver)
Plugins, MIME types, fonts, language, timezone
Canvas/WebGL output (pixel-level fingerprinting)
Audio rendering via AudioContext

Network Signals

IP address geolocation
Proxy detection
Volume and frequency of requests

Server-Side Heuristics

Machine learning models analyze hundreds of metrics such as timing consistency, request header patterns, and DOM interaction sequences
Builds a trust score or directly accepts/rejects responses

Methods for Bypass GeeTest CAPTCHA

Let’s now explore practical approaches for bypassing GeeTest v3 and v4, depending on your level of control, infrastructure, and performance requirements.

Using CAPTCHA-Solving Services (e.g., 2Captcha, RuCaptcha, SolveCaptcha)

Workflow:

Extract required parameters:

v3: gt, challenge, page URL
v4: captcha_id, page URL (service retrieves challenge itself)

Send data to the CAPTCHA service
Poll for response and inject the validated token(s)

Example:

import requests, time

API_KEY = "YOUR_2CAPTCHA_KEY"
gt = "site-specific-gt"
challenge = "site-challenge-token"
page_url = "https://example.com"

# Submit CAPTCHA
resp = requests.post("http://2captcha.com/in.php", data={
    "key": API_KEY,
    "method": "geetest",
    "gt": gt,
    "challenge": challenge,
    "pageurl": page_url
})

if not resp.text.startswith("OK|"):
    raise Exception(f"Error submitting CAPTCHA: {resp.text}")

captcha_id = resp.text.split('|')[1]

# Poll for result
for _ in range(20):
    time.sleep(5)
    res = requests.get(f"http://2captcha.com/res.php?key={API_KEY}&action=get&id={captcha_id}")
    if res.text == "CAPCHA_NOT_READY":
        continue
    if res.text.startswith("OK|"):
        print("GeeTest Response:", res.text.split("|", 1)[1])
        break

Pros:

Works reliably for both versions
Fast integration (especially for MVPs or prototypes)
Reasonable cost (~$0.001–$0.002 per CAPTCHA)

Cons:

Reliance on external API
Latency of 5–20 seconds
May not support highly complex puzzles like Gobang without fallback to humans

And by the way, you can check what service is better using service captchathecat (it’s free).

Image-Based Solving with OpenCV (Slider-Only)

If you want to fully automate GeeTest without external services, using OpenCV for slider-based challenges is a great option.

How it works:

Extract puzzle images (background + slider piece)
Use cv2.matchTemplate() to detect where the puzzle fits
Simulate human-like dragging using Selenium or Puppeteer

import cv2
import numpy as np

bg = cv2.imread("captcha_bg.png", 0)
piece = cv2.imread("captcha_piece.png", 0)

bg_edges = cv2.Canny(bg, 50, 150)
piece_edges = cv2.Canny(piece, 50, 150)

result = cv2.matchTemplate(bg_edges, piece_edges, cv2.TM_CCOEFF_NORMED)
_, _, _, max_loc = cv2.minMaxLoc(result)
print("X Offset to drag:", max_loc[0])

This offset can be used in a drag script to simulate natural mouse movement.

Pros:

Instant local solving (<1s)
Full control and no third-party dependency

Cons:

Only works for slider CAPTCHAs
Requires periodic updates if GeeTest changes images or mechanics

Emulated Interaction via Headless Browsers

Another practical option is using browser automation tools (Selenium, Puppeteer, Playwright) to perform challenges as if a user is present.

Steps:

Launch browser with stealth configuration
Monitor for CAPTCHA
Solve via API or CV
Inject solution via browser form or JS call

Puppeteer example (JS):

const gt = await page.evaluate(() => window.gt);
const challenge = await page.evaluate(() => window.challenge);

const response = await solveViaAPI(gt, challenge, page.url());
const { validate, seccode } = response;

await page.evaluate((ch, val, sec) => {
    document.getElementById('geetest_challenge').value = ch;
    document.getElementById('geetest_validate').value = val;
    document.getElementById('geetest_seccode').value = sec;
    document.querySelector('form').submit();
}, challenge, validate, seccode);

Note: You must obfuscate browser fingerprints using tools like:

puppeteer-extra-plugin-stealth
undetected_chromedriver
Anti-detect browsers (Multilogin, Mimic)

Protocol-Level Emulation (Advanced)

For teams with the necessary reverse-engineering skills, it is possible to mimic GeeTest’s internal encryption routines.

v3:

Reverse gt.js and emulate movement track signing

v4:

Decode the AES/RSA logic that produces the w value

This requires full replication of JavaScript-based cryptographic logic, often rewritten in Python or Node.js. It’s fast and reliable once implemented—but brittle.

Warning: GeeTest frequently updates its logic. This is a high-maintenance, high-reward strategy suitable only for large-scale or critical automation infrastructure.

Best Practices to Avoid Detection if You Don't Want to Bypass GeeTest

Use residential or mobile proxies; avoid datacenter IPs
Align language, timezone, and screen size with IP location
Spoof all navigator/browser properties accurately
Introduce random delays and jitter in user simulation
Avoid retrying failed CAPTCHAs repeatedly from the same session or IP

Final Thoughts

GeeTest CAPTCHA is a well-architected, behavior-driven protection system. It’s one of the most advanced tools used to block automated traffic today. That said, it’s not impenetrable. With the right combination of API services, computer vision, browser automation, and stealth, it is possible to reliably solve both v3 and v4 variants.

For developers building scraping tools, automation bots, or testing frameworks, understanding and bypassing GeeTest can be an essential skill. And with future updates—like a potential v5—coming down the pipeline, the need to stay adaptable has never been more critical.

Let me know if you'd like this version delivered as Markdown, optimized for dev blogs, or published into docs format.

Bypassing Funcaptcha in 2 ways solutions

Markus — Fri, 18 Apr 2025 14:33:53 +0000

Arkose Labs introduces different types of captcha protection.
2Captcha is Arkose Labs captcha (Funcaptcha) solver. In this article, we will look at 2 options for completing tasks for the user.
The instructions describe the process of interacting with API.

Details about the tasks

Funcaptcha has two main options:

Standard grid captcha
funcaptcha_compare

Grid captcha type:

In this case, the user is offered a set of images divided into sections with numeric labels. He must select an image corresponding to the provided text description.

Example: On the left side there is an image with the number 8, and on the right there is a set of images with various objects. The user needs to select an image where the sum of the object values is 8.

Funcaptcha_compare type:

In this version, there is also an image at the bottom, but this time with a set of icons. At the top of the image, there is a set of icons with different permutations. Users must match the icons on the left side with those on the top right side.

Example: Fruit icons are shown, and on the top on the right side are the same icons, but in a different sequence. The user needs to match each icon.

How to solve a captcha using the API?

Get the image of captcha

To solve the captcha in this way, you need to transfer the ENTIRE image.

Open the "Network" tab in your browser's developer tools.
Find a request with a captcha image, this is a request with a URL https://client-api.arkoselabs.com/rtig/image...
In the section 'Headers', you will find a field containing the URL of the captcha image.
Open the image and save it, after you can convert it to base64.

Get the text instruction

Find the element with instructions for the captcha var taskElement = document.querySelector('.sc-1io4bok-0');
Get text from element var taskText = taskElement.textContent || taskElement.innerText;

Important: The textinstructions must be in English!

Request examples

Necessary to send the original image files and not screenshots.

Using APIv1

API endpoint: https://2captcha.com/in.php

Using APIv2

Method: createTask API endpoint: https://api.2captcha.com/createTask

GridTask

APIv1

{
    "method": "base64",
    "key": "key",
    "recaptcha": 1,
    "json": 1,
    "img_type": "funcaptcha",
    "textinstructions": "pick the image where the darts add up to 8",
    "body": "/9j/4AAQSkZJRgABAQEAYABgAAD/4QBoRXhpZgAA"
}

APIv2

{
    "clientKey": "key",
    "task": {
        "type": "GridTask",
        "body": "/9j/4AAQSkZJRgABAQEAYABgAAD/4QBoRXhpZg",
        "comment": "pick the image where the darts add up to 8",
        "imgType": "funcaptcha"
    }
}

Funcaptcha_compare type

APIv1

{
    "method": "base64",
    "key": "key",
    "recaptcha": 1,
    "json": 1,
    "img_type": "funcaptcha_compare",
    "textinstructions": "Match the icons on the left with the icons on the top faces of the dice (1 of 1)",
    "body": "/9j/2wCEAAoHBwgHBgoICAgLCgoLDhgQDg0NDh0VFhEYIx8lJCIfIiEmKzcvJik0KSEiMEExNDk7Pj4+JS5ESUM8SDc9PjsBCgsL"
}

APIv2

{
    "clientKey": "key",
    "task": {
        "type": "GridTask",
        "body": "/9j/2wCEAAoHBwgHBgoICAgLCgoLDhgQDg0",
        "comment": "Match the icons on the left with the icons on the top faces of the dice (1 of 1)",
        "imgType": "funcaptcha_compare"
    }
}

The picture must be intact, without changes in size or cropping.

Response example

From the received response, we take the captcha ID and, using it, request a response with a GET request of the form:

For APIv1

https://2captcha.com/res.php?

For APIv2

https://api.2captcha.com/getTaskResult

The result contains the number of clicks that need to be clicked, for example:

{
  "status": 1,
  "request": "click:3"
}

Using the Response

The result of the request is represented by a set of coordinates in the "click" format:2". The number indicates how many times you should click on the arrow to successfully solve the captcha.

References

Additional information:

Price
Code samples on the official page in GitHub.

Support

If you still have questions about the service, you can ask a question:

We value feedback and want to make sure the service is perfect for your needs.