CreepJS

https://abrahamjuliot.github.io/creepjs

The purpose of this project is to shed light on weaknesses and privacy leaks among modern anti-fingerprinting extensions and browsers.

1. Detect and ignore API tampering (API lies)
2. Fingerprint lie types
3. Fingerprint extension code
4. Fingerprint browser privacy settings
5. Employ large-scale validation, but allow possible inconsistencies
6. Feature detect and fingerprint new APIs that reveal high entropy
7. Rely only on APIs that are the most difficult to spoof when generating a pure fingerprint

Tests are focused on:

• Tor Browser (SL 1 & 2)
• Firefox (RFP)
• ungoogled-chromium (fingerprint deception)
• Brave Browser (Standard/Strict)
• puppeteer-extra
• Bromite
• uBlock Origin (aopr)
• NoScript
• DuckDuckGo Privacy Essentials
• JShelter (JavaScript Restrictor)
• Privacy Badger
• Privacy Possom
• Random User-Agent
• User Agent Switcher and Manager
• CanvasBlocker
• Trace
• CyDec
• Chameleon
• ScriptSafe
• Windscribe

Rules

Data

• data collected: worker scope user agent, webgl gpu renderer, js runtime engine, hashed browser fingerprints (stable, loose, fuzzy, & shadow), encrypted ip, encrypted system location, dates, and boolean metrics
• data retention: auto deletes 30 days after last visit
• visit tracking: limited to data retention and new feature scaling

Example Data Models

Metric Samples

Purpose: learn and predict browser engine and platform version, device, and gpu

{
	cleanup: false,
	decrypted: "Blink",
	devicePrimary: "Windows 10 (64-bit)",
	deviceTrust: `{
		"Windows 10 (64-bit)": ["6a9","fe3","bb7"],
		"Windows 7 (64-bit)": ["8a3"],
		"Windows 11 (64-bit)": ["e4a"]
	}`,
	devices: [
		"Windows 10 (64-bit)",
		"Windows 7 (64-bit)",
		"Windows 11 (64-bit)"
	],
	gpus: [],
	healEvents: [],
	highEntropyLossYield: false,
	highEntropyLost: true,
	id: "01aa0cc74cd124b8985d7e386e5499b34770353cab321e214a2aae122b4c1995",
	lock: false,
	logger: [
		"8eff_75d6295c_345026a9: Blink (12/5/2021, 2:54:02 AM)"
	],
	reporter: `{
		"dates": ["12/5/2021","12/10/2021","12/17/2021","12/22/2021"],
		"ips": ["8eff","66fa","6ac2","5887"]
	}`,
	reporterTrustScore: 100,
	reviewed: true,
	suggested: "no change",
	systemCore: "unknown",
	systems: [
		"Windows"
	],
	timestamp: "2022-01-15T16:34:23.807Z",
	trash: false,
	type: "Canvas System",
	userAgents: [
		"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/96.0.4664.45 Safari/537.36"
	]
}

Fingerprints

Purpose: identify browser visit history and activity

{
	bot: 0.125,
	botHash: "00000001",
	botLevel: "stranger:csl",
	crowdBlendingScore: 36,
	fingerprint: "18ce59ae1e65397c81b38da98e6eed23a8f6d4bd3a2a349ed800f7daebd6f9dc",
	firstVisit: "2022-01-17T15:39:21.964Z",
	fuzzyInit: "1879e559e5de22c3dceb603775ff8062bb274c41547f9fc0b38e919fc4000000",
	fuzzyLast: "1879e559e5de22c3dceb603775ff8062bb274c41547f9fc0b38e919fc4000000",
	lastVisit: "2022-01-17T15:39:21.964Z",
	lastVisitEpoch: 1642433961964,
	looseFingerprints: [
		"f331fd21a4f8dec8054ffaec88c32723f840f6a6174303cd787fb676a513bbf6"
	],
	looseSwitchCount: 0,
	maxErrors: 0,
	maxLies: 0,
	maxTrash: 0,
	score: 100,
	scoreData: `{
		"switchCountPointGain": 5,
		"errorsPointGain": 0,
		"trashPointGain": 0,
		"liesPointGain": 0,
		"shadowBitsPointGain": 10,
		"grade": "A+"
	}`,
	shadow: "0000000000000000000000000000000000000000000000000000000000000000",
	shadowBits: 0,
	signature: "",
	timeHoursAlive: 0,
	timeHoursFromLastVisit: 0,
	timeHoursIdleMax: 0,
	timeHoursIdleMin: 0,
	visits: 1,
	benchmark: 565.4,
	resistance: ''
}

New feature scaling

• scaling should occur no more than once per week
• new weekly features may render fingerprints anew
• view deploy history

Signatures

• you may optionally sign your fingerprint with 4-64 characters
• signatures can be memorable descriptors
• in low entropy browsers, a signature can signal to others that the fingerprint is shared

Fingerprint Tracing Formulas

Fingerprint Hashing

• FP-ID: SHA-256 hashing of stable fingerprint (Creep)
• Fuzzy: fuzzy hashing of first loose fingerprint
• Diffs: fuzzy hashing of current loose fingerprint
• Shadow: fuzzy hashing diffs history

FP-ID...: 9368a2b8913acba5633aa8f353bfd546aaaf77fd57c1416580e90fc41666feb2
Fuzzy...: 98fcf569e50680c3dcfb8e53e34874e2b2075c415208a1c05292119ec4000000
Diffs...: 50ed3569e50680c3dcfb8e00e3387c5fb2075c415408a2006292119ec4000000
Shadow..: 1111100000000000000000110010011100000000010001101000000000000000

Trust Score

A failing trust score is unique

• start at 100
• less than 2 loose fingerprints: reward 5 extra credit
• 0 shadow bits (session metric revisions): reward 10 extra credit
• 2 - 10 loose fingerprints: subtract total*0.1
• 11+ loose fingerprints: subtract total*0.2
• shadow bits: subtract (total/64)*31
• trash: subtract total*5.5
• lies: subtract total*31
• errors: subtract total*3.5

Crowd-Blending Score

A metric with only 1 reporter is unique

• Metric scores decline by metric uniqueness
• Final score is the minimum of all metrics scores
• Blocked or openly poisoned metrics collectively reduce the final score by 25%
• Scoring formula: 100-(numberOfRequiredReporters ** (numberOfRequiredReporters - numberOfReporters))
• Where the number of required reporters is 4:
  • Blocked/Openly Poisoned -100
  • 1 reporter -64
  • 2 reporters -16
  • 3 reporters -4
  • 4+ reporters is considered a perfect score
• Unique metrics get 2 weeks to improve their score before auto-deletion

Bot Detection

Bots leak unusual behavior and can be denied services

• Excessive loose fingerprints
• User agent version or platform does not match features
• worker scope tampering

bot hash/level

• 10000000:smart-enemy:lws (lied worker scope)
• 01000000:crafty-attacker:lpv (lied platform version)
• 00100000:stealth-hacker:ftp (function toString proxy)
• 00010000:clumsy-spy:ofv (ua outside features version)
• 00001000:bold-fraud:elc (extreme lie count)
• 00000100:hyper-client:elf (excessive loose fingerprints)
• 00000010:locked-down:wsb (worker scope blocked)
• 00000001:stranger:csl (crowd-blending score low)
• 00000000:friend (none of the above)

Shadow

Loose metric revision patterns can follow stable fingerprints like a shadow

• Shadow: a string of 64 characters used to capture the history of fuzzy fingerprint diffs
• Diffs or revisions may include browser updates, user settings and/or API tampering

Browser Prediction

• A prediction is made to decrypt the browser vendor, version, renderer, engine, system, device and gpu
• This prediction does not affect the fingerprint
• Data is auto matched to fingerprint ids gathered from WorkerNavigator.userAgent and other stable metrics
• Decoded samples from the server are auto computed or manually reviewed
• Each sample goes through a number of client and server checks before it is considered trustworthy
• Samples that are poisoned can self learn and heal themselves
• Samples aging 45 days since last timestamp visit are auto discarded (random samples that never return are eventually auto removed)
• If the worker scope is blocked and the fingerprint ids exist in the database, the prediction can still be made

Tests

1. contentWindow (Self) object
2. CSS System Styles
3. CSS Computed Styles
4. HTMLElement
5. JS Runtime (Math)
6. JS Engine (Console Errors)
7. Emojis (DomRect)
8. DomRect
9. SVG
10. Audio
11. MimeTypes
12. Canvas
13. TextMetrics
14. WebGL
15. GPU Params (WebGL Parameters)
16. GPU Model (WebGL Renderer)
17. Fonts
18. Voices
19. Screen
20. Resistance (Known Patterns)

Supported

• layout rendering engines: Gecko, Goanna, Blink, WebKit
• JS runtime engines: SpiderMonkey, JavaScriptCore, V8

Definitions

Trash

• unusual results
• forgivable lies (invalid metrics capable of being restored)
• failed calculations that may reasonably occur at random (loose fingerprint metrics)

Lies

• prototype tampering
• mismatch in worker scope or iframe
• failed math calculations

Errors

• ungracefully blocked features that break the web
• failed executions

Interact with the fingerprint objects

• window.Fingerprint
• window.Creep

Fingerprint

• collects as much entropy as possible
• permits loose metrics

Creep

• adapts to browsers and distrusts known noise vectors
• aims to ignore entropy unique to a browser version release
• gathers compressed and static entropy

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Contributions are welcome.