REAL-TIME · ML-POWERED · ZERO CAPTCHAS

Every bot. Caught.
Every human. Through.

Prynt detects bots in under 50ms using six independent detection layers — from simple scripts to sophisticated headless browsers — without CAPTCHAs, challenges, or friction for legitimate users.

Start Blocking Bots → See Detection Demo
99.7%
Bot detection rate
0.01%
False positive rate
<50ms
Detection latency
0
CAPTCHAs served
Live Feed

See what we're catching right now.

A real-time view of bot traffic detected across the Prynt network. Every row is a real detection — classified, scored, and actioned in milliseconds.

Threat Feed
Blocked today: 847,291 Human pass rate: 99.99%
TimeVisitorBot TypeConfidenceActionLatency
14:23:08.412pv_7xN2qK...
AutomationPuppeteer
99.8%Block12ms
14:23:08.287pv_4mT9wL...
HeadlessChrome (headless)
98.4%Block18ms
14:23:08.103pv_9rF6gM...
Human
99.9%Allow8ms
14:23:07.891pv_2hG5cX...
ScraperPython requests
99.2%Block6ms
14:23:07.654pv_5kX8nR...
CredentialStuffing attack
97.6%Block22ms
14:23:07.512pv_6wT3pL...
Human
99.7%Allow9ms
14:23:07.341pv_1pN4sQ...
AutomationSelenium
99.5%Block14ms
14:23:07.198pv_8jK2mN...
API AbusecURL / Scripted
96.1%Block4ms
14:23:06.987pv_3dF7gH...
Human
99.8%Allow11ms
14:23:06.812pv_0bC9dE...
HeadlessPlaywright
99.1%Block16ms
Bot Taxonomy

We classify. You decide.

Prynt doesn't just detect bots — it classifies them by type, framework, and intent. Use the taxonomy to apply different policies to different threats.

🤖
Automation FrameworksCritical

Browser automation tools controlled by scripts. Used for account creation, ticket scalping, credential stuffing, and form spam at scale.

Puppeteer
Playwright
Selenium / WebDriver
Cypress (abuse)
👻
Headless BrowsersHigh

Browsers running without a visible UI. Often used with stealth plugins to mimic real user environments and bypass basic detection.

Headless Chrome
Headless Firefox
PhantomJS
Stealth plugin variants
🕷️
Scrapers & CrawlersHigh

HTTP-level bots that extract content, pricing, or inventory data. Range from simple scripts to sophisticated distributed crawling systems.

Python requests / httpx
Scrapy / Colly
Custom HTTP clients
Residential proxy rotators
🔑
Credential StuffingCritical

Automated login attempts using stolen username/password combinations from data breaches. High velocity, distributed across proxies.

OpenBullet / SentryMBA
Custom credential checkers
Combo list attacks
API AbuseMedium

Direct API calls bypassing the frontend entirely. Used for inventory sniping, rate limit abuse, data extraction, and automated transactions.

cURL / wget
Postman scripting
Custom API clients
📱
Emulators & SpoofingHigh

Virtual devices and environment spoofing tools designed to mimic real mobile devices and desktops, often used in ad fraud and fake installs.

Android emulators
iOS simulators
User-agent spoofing
Canvas/WebGL spoofing
Detection Engine

Six layers. Zero blind spots.

Every request passes through six independent detection layers. A bot must evade all six simultaneously to pass — and we haven't seen one that can.

🔍
L1
JavaScript Environment Analysis
Probes for automation artifacts left by browser drivers. Detects navigator.webdriver, phantom properties, __selenium_unwrapped, and 200+ other telltale signs that frameworks forget to clean up.
navigator.webdriverwindow.phantomchrome.runtimePermissions APIPlugin array
🎨
L2
Rendering Consistency Checks
Compares Canvas, WebGL, and font rendering against expected outputs for the claimed device/OS combination. Emulators and headless browsers produce rendering anomalies that real hardware doesn't.
Canvas anomaliesWebGL mismatchesGPU/renderer mismatchFont inconsistency
⏱️
L3
Timing & Execution Fingerprinting
Measures JavaScript execution timing, API call latencies, and event loop characteristics. Automation frameworks introduce measurable timing patterns that differ from real browser execution.
Execution timingEvent loop profilingAPI latency patternsMicrotask ordering
🌐
L4
Network & Protocol Analysis
Inspects TLS fingerprint (JA3/JA4), HTTP/2 settings, header ordering, and TCP characteristics. Bots using HTTP libraries have distinct network signatures even when they spoof user agents.
TLS fingerprint (JA4)HTTP/2 settingsHeader orderTCP window sizeALPN negotiation
📊
L5
Behavioral Pattern Recognition
Analyzes request velocity, session patterns, and navigation behavior. Bots exhibit non-human patterns — uniform timing intervals, no scroll events, no mouse movement, and impossibly fast form completion.
Velocity anomaliesNavigation patternsSession behaviorInput cadence
🧠
L6
ML Ensemble Classification
All signals from layers 1–5 are fed into an ensemble of ML models trained on billions of real-world requests. The ensemble produces a final bot probability score and classification label.
Gradient boostingNeural networkAnomaly detectionWeekly retraining
Detection Result
Detected
🤖 Bot Detected
Puppeteer
Automation Framework · Chrome 121
Bot probability
99.8%
JS environment
Fail
Rendering
Anomaly
Timing
Fail
Network
Suspect
Behavior
Fail
Webdriver
true
Plugins
0 (spoofed)
Canvas Hash
Mismatch
TLS (JA4)
Non-browser
Mouse Events
None
Latency
12ms
Evasion Resistance

They adapt. We're already ahead.

Bot operators use sophisticated evasion techniques. Prynt detects them all — because we don't rely on any single signal.

🥷

Stealth Plugins

Tools like puppeteer-extra-plugin-stealth patch common detection flags. Prynt catches stealth users through deeper signals they can't fake.

Attack: Override navigator.webdriver to false
Prynt: Detect via prototype chain analysis, timing side-channels, and rendering artifacts that stealth plugins can't modify
🏠

Residential Proxies

Bot traffic routed through real residential IPs to bypass IP-based blocking. Prynt doesn't depend on IP reputation alone.

Attack: Route through Bright Data, Oxylabs residential pools
Prynt: Identify via device fingerprint, TLS signature, and behavioral analysis — IP is just one of 100+ signals
🎭

User Agent Spoofing

Bots present fake user agents claiming to be real browsers. Prynt cross-validates the claimed UA against actual browser capabilities.

Attack: Set User-Agent to Chrome 121 on macOS
Prynt: Cross-check JS APIs, rendering output, and TLS fingerprint against claimed browser — inconsistencies reveal the spoof
🖱️

Fake Human Behavior

Advanced bots inject synthetic mouse movements and scroll events. Prynt's ML models detect the subtle statistical differences from real humans.

Attack: Inject bezier-curve mouse movements and random delays
Prynt: Analyze micro-timing distributions, acceleration patterns, and jitter entropy — synthetic movement has detectable uniformity
🔄

Browser Fingerprint Rotation

Bots that randomize their fingerprint on every request to avoid tracking. Prynt detects the impossibility of rapid hardware changes.

Attack: Randomize Canvas, WebGL, and fonts per session
Prynt: Flag rapid fingerprint changes from the same network — real hardware doesn't change 40 times per hour
☁️

Cloud VM / Container

Bots running from AWS, GCP, or Azure instances with real Chrome installed. Prynt detects cloud-hosted browsers through hardware signals.

Attack: Run real Chrome in an EC2 instance or Docker container
Prynt: Detect virtualized GPU, missing audio hardware, uniform screen dimensions, and datacenter IP ranges
API Response

Classification data you can act on.

Every identification request returns a structured bot detection result — type, framework, confidence, and the evidence that triggered the classification.

bot.detectedboolean
Whether this request was classified as bot traffic. true for bots, false for humans. Use as the primary gating signal.
bot.typeenum
High-level bot classification. Values: automation, headless, scraper, credential_stuffing, api_abuse, emulator, none.
bot.frameworkstring | null
Specific automation framework identified, when detectable. Examples: "Puppeteer", "Playwright", "Selenium", "PhantomJS", "Scrapy". Null for humans or unidentified frameworks.
bot.confidencefloat
Detection confidence from 0 to 1. Bots typically score 0.95+. Use lower thresholds for stricter enforcement. Values below 0.5 are classified as human.
bot.evidenceobject
Detailed evidence from each detection layer — JS environment flags, rendering mismatches, timing anomalies, and network signatures. Use for forensic investigation and rule tuning.
bot.layersobject
Per-layer pass/fail status for all six detection layers. Shows which layers triggered and which were inconclusive. Useful for understanding detection coverage.
Bot detection responseBOT SIGNAL
{
  "bot": {
    "detected": true,
    "type": "automation",
    "framework": "Puppeteer",
    "confidence": 0.998,
    "evidence": {
      "jsEnvironment": {
        "webdriverPresent": true,
        "pluginArrayEmpty": true,
        "chromeRuntimeMissing": true,
        "permissionsInconsistent": true
      },
      "rendering": {
        "canvasMismatch": true,
        "webglAnomaly": false
      },
      "timing": {
        "executionDrift": 0.87,
        "eventLoopAnomaly": true
      },
      "network": {
        "ja4": "t13d1516h2_...",
        "browserMatch": false,
        "h2Settings": "non_standard"
      }
    },
    "layers": {
      "jsEnvironment": "fail",
      "rendering": "anomaly",
      "timing": "fail",
      "network": "suspect",
      "behavior": "fail",
      "mlEnsemble": "fail"
    }
  }
}
Use Cases

Stop bots everywhere they attack.

Bot detection is included in every Prynt plan. Use it to protect any interaction — registration, login, checkout, API, or content.

📝

Registration Spam

Block bots from creating fake accounts that pollute your user base, abuse onboarding incentives, and waste support resources.

AutomationHeadlessEmulator
🔑

Credential Stuffing

Detect and block automated login attempts using stolen credentials. Protect accounts without forcing MFA on every legitimate user.

CredentialAutomationAPI Abuse
🎟️

Scalping & Sniping

Stop bots from grabbing limited inventory — concert tickets, sneakers, GPU drops — before real customers have a chance.

AutomationAPI AbuseHeadless
💳

Card Testing

Detect automated payment attempts that test stolen credit card numbers against your checkout. Block before chargebacks hit.

AutomationAPI Abuse
📊

Content & Price Scraping

Prevent competitors and aggregators from scraping your product listings, pricing data, and proprietary content at scale.

ScraperHeadlessAPI Abuse

Fake Reviews & Engagement

Block bots that submit fake reviews, inflate vote counts, spam comments, or manipulate engagement metrics on your platform.

AutomationEmulator
Comparison

Prynt vs. traditional bot defense.

See how Prynt's invisible, ML-powered approach compares to legacy solutions that rely on CAPTCHAs and rate limiting.

CapabilityPryntreCAPTCHACloudflare Bot MgmtRate Limiting
Zero user friction✓ Invisible✗ Challenges~ JS Challenge✓ Invisible
Headless browser detection✓ 99.7%~ Partial✓ Good✗ None
Framework classification✓ Named✗ Binary only~ Partial✗ None
Stealth plugin resistance✓ 6 layers✗ Bypassed~ Some✗ None
Residential proxy handling✓ Device-based~ Score-based~ IP reputation✗ None
Per-layer evidence✓ Full breakdown✗ Score only✗ Binary✗ None
API abuse detection✓ TLS + behavior✗ Client-only✓ Good~ Threshold only
Custom rules on bot type✓ Full engine✗ None~ Limited✗ None
False positive rate✓ 0.01%~ 1-3%~ 0.1%~ High
Privacy compliant (no PII)✗ Tracks users

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