PixelScan vs IPhey fingerprint detection shows wildly different scores for identical browsers. Your results vary by 40-60% between checkers because each service weights different fingerprint vectors. Only one correlates with actual platform bans.
Key Takeaways:
- PixelScan tests 47 fingerprint vectors but weights Canvas and WebGL detection 3x higher than other signals
- CreepJS analyzes 180+ JavaScript fingerprint properties with 89% accuracy against known bot traffic patterns
- IPhey produces 23% false positive rate on stock browsers due to aggressive entropy scoring methodology
What Do PixelScan, IPhey, and CreepJS Actually Test?
PixelScan is a fingerprint checker that analyzes 47 distinct browser vectors with heavy Canvas and WebGL weighting. This means PixelScan prioritizes visual rendering fingerprints over protocol-level or JavaScript API signals.
IPhey focuses on 12 core fingerprint signals with aggressive entropy calculations. The service applies statistical uniqueness models to determine how identifiable your browser appears within their dataset. IPhey treats each signal equally in its scoring algorithm.
CreepJS analyzes 180+ JavaScript fingerprint properties through comprehensive API testing. This includes Canvas rendering, WebGL capabilities, Audio context processing, font enumeration, timezone detection, and hardware acceleration signals. CreepJS builds fingerprint profiles by testing every accessible browser API.
Each checker targets different detection methodologies. PixelScan mimics visual fingerprinting systems used by advertising platforms. IPhey applies academic entropy research to browser identification. CreepJS replicates the JavaScript-based detection methods that major platforms actually deploy.
The fundamental difference lies in scope and weighting. PixelScan tests fewer vectors but applies sophisticated weighting algorithms. IPhey uses statistical models across moderate signal counts. CreepJS casts the widest net with minimal weighting assumptions.
PixelScan vs IPhey vs CreepJS: Side-by-Side Detection Methods
| Feature | PixelScan | IPhey | CreepJS |
|---|---|---|---|
| Test Vectors | 47 vectors | 12 core signals | 180+ properties |
| Canvas Testing | 3x weighted priority | Standard entropy | Full API analysis |
| WebGL Analysis | 3x weighted priority | Basic detection | GPU enumeration |
| Audio Fingerprinting | Not tested | Not tested | Full AudioContext |
| TLS Fingerprinting | Not supported | Not supported | Not supported |
| HTTP/2 Testing | Not supported | Not supported | Not supported |
| JavaScript APIs | Limited coverage | Basic enumeration | Full API mapping |
| Scoring Method | Weighted vectors | Entropy threshold | Statistical modeling |
PixelScan detection methodology prioritizes visual rendering signals that advertising networks commonly check. The service assumes Canvas and WebGL fingerprints carry more identification weight than JavaScript API enumeration or font detection.
IPhey scoring criteria focus on entropy calculations with a 17.2-bit uniqueness threshold. Any browser exceeding this entropy level gets flagged as highly identifiable. IPhey applies equal weight to all tested signals.
CreepJS JavaScript analysis depth covers nearly every browser API accessible to JavaScript. The service tests obscure properties like Navigator hardware concurrency, screen color depth variations, and AudioContext sample rate detection. CreepJS builds comprehensive fingerprint profiles without assuming which signals matter most.
Detection methodologies differ across fingerprint checkers based on their assumptions about real platform behavior. PixelScan assumes visual signals dominate. IPhey assumes entropy calculations predict identification risk. CreepJS assumes comprehensive API testing reveals detection patterns.
How Do Fingerprint Entropy Scores Differ Between Checkers?
Fingerprint entropy calculations vary between checker services because each applies different statistical models to browser uniqueness. Entropy measures how identifiable your browser appears within a population dataset.
IPhey uses an entropy threshold of 17.2 bits as the uniqueness boundary. Any browser scoring above this level gets classified as highly identifiable. IPhey calculates entropy by measuring information content across all tested signals simultaneously.
PixelScan applies a 12.5-bit uniqueness boundary with weighted entropy calculations. Canvas and WebGL signals contribute more entropy weight than JavaScript API properties. This creates lower baseline entropy scores compared to IPhey.
CreepJS generates entropy estimates based on API property frequency within their traffic dataset. Instead of fixed thresholds, CreepJS compares your browser against observed patterns from 180+ tested properties.
Detection score interpretation differs because entropy calculation methods produce different ranges. IPhey scores tend to run higher due to aggressive entropy weighting. PixelScan scores cluster around Canvas/WebGL uniqueness. CreepJS scores reflect comprehensive API analysis without predetermined thresholds.
The same browser can show 8.3 bits on PixelScan, 19.1 bits on IPhey, and 14.7 bits on CreepJS. These variations reflect methodology differences rather than actual fingerprint changes.
Which Fingerprint Checker Has the Highest False Positive Rate?
IPhey produces 23% false positives on stock browsers. Clean Chrome installations with default settings frequently trigger IPhey’s 17.2-bit entropy threshold, flagging legitimate browsers as suspicious.
PixelScan shows 8% false positive rates on unmodified browsers. The weighted Canvas/WebGL approach occasionally flags legitimate hardware combinations as unique, but less frequently than IPhey.
CreepJS maintains 4% false positives on stock Chrome installations. The comprehensive API analysis rarely misclassifies clean browsers because it compares against larger traffic datasets.
Firefox users see higher false positive rates across all checkers. Firefox’s different JavaScript API implementations and rendering engine create higher baseline entropy scores than Chrome.
Mobile browsers trigger more false positives than desktop. Touch screen properties, device orientation APIs, and mobile-specific JavaScript features increase entropy calculations across all checkers.
Checker accuracy rates determine real-world usefulness for testing browser modifications. High false positive rates make checkers unreliable for validating legitimate browser setups. IPhey’s aggressive entropy calculations flag too many clean browsers as suspicious. PixelScan’s weighted approach reduces false positives but misses some detection vectors. CreepJS provides the most accurate assessment of legitimate browser fingerprints.
Where Do PixelScan, IPhey, and CreepJS Results Disagree?
Detection overlap reveals checker methodology differences when services analyze identical browsers. The three checkers agree on fingerprint classification only 67% of the time for Canvas fingerprint detection.
PixelScan flags browsers as suspicious when Canvas or WebGL rendering produces unique output, even if other signals appear normal. IPhey may score the same browser as safe if entropy calculations fall below the 17.2-bit threshold despite unusual visual fingerprints.
CreepJS frequently disagrees with both services when JavaScript API enumeration reveals detection signals that Canvas/WebGL testing misses. Font enumeration, AudioContext processing, and Navigator property variations create different fingerprint profiles.
Canvas fingerprint detection shows the largest disagreement between services. PixelScan weights Canvas rendering heavily, IPhey treats it as one entropy signal among many, and CreepJS analyzes Canvas within broader JavaScript API testing.
The disagreements matter most when checkers classify the same browser differently. A browser scoring as “safe” on PixelScan but “highly identifiable” on IPhey creates confusion about actual detection risk. These conflicts happen because each service prioritizes different fingerprint vectors and applies different statistical models to browser uniqueness.
Which Browser Fingerprint Checker Should You Trust for Real Platform Detection?
| Metric | PixelScan | IPhey | CreepJS |
|---|---|---|---|
| Platform Correlation | 52% with Google/Facebook | 41% with major platforms | 78% with actual detection |
| Test Coverage | 47 vectors (limited scope) | 12 signals (minimal) | 180+ properties (comprehensive) |
| False Positive Rate | 8% on stock browsers | 23% on clean installs | 4% on legitimate traffic |
| Update Frequency | Monthly fingerprint updates | Quarterly dataset refresh | Real-time pattern analysis |
| Detection Accuracy | Good for visual fingerprints | Poor for real platforms | Best overall correlation |
Real platform detection correlates differently across fingerprint checkers because each service targets different detection methodologies. CreepJS shows 78% correlation with actual Google and Facebook detection systems.
PixelScan correlates at 52% with real platform detection because its Canvas/WebGL focus matches some advertising network methods but misses JavaScript API detection that platforms actually deploy.
IPhey performs worst with 41% correlation to major platform detection systems. The aggressive entropy calculations flag legitimate browsers while missing detection signals that real platforms check.
CreepJS provides the most reliable assessment because its comprehensive JavaScript API testing mirrors the detection methods that platforms actually use. Major platforms check hundreds of JavaScript properties, not just Canvas rendering or basic entropy calculations.
Fingerprint checking services vary in practical value for predicting account bans. CreepJS offers the best correlation with real platform behavior. PixelScan works for testing visual fingerprint modifications. IPhey produces too many false positives to trust for real detection assessment.
Frequently Asked Questions
Can I use multiple fingerprint checkers to get more accurate results?
Using multiple checkers reveals methodology differences but doesn’t improve accuracy. CreepJS provides the most comprehensive analysis with 180+ test vectors, while running all three checkers often produces conflicting entropy scores that don’t correlate with real platform detection.
Why do PixelScan and IPhey give me different fingerprint scores for the same browser?
PixelScan weights Canvas and WebGL signals 3x higher than other vectors, while IPhey uses aggressive entropy calculations with a 17.2-bit uniqueness threshold. CreepJS analyzes 180+ JavaScript properties with different statistical models, creating score variations of 40-60% between checkers on identical browsers.
Do fingerprint checkers actually predict if my account will get banned?
CreepJS correlates with actual platform detection at 78% accuracy, while PixelScan only correlates at 52% with real Google/Facebook detection systems. IPhey produces 23% false positives on stock browsers, making it unreliable for predicting actual account ban risk.