What is device intelligence, and how is it different from device fingerprinting?

Device fingerprinting is the technique of collecting a device's hardware, OS, and browser attributes to build one unique device identifier. Device intelligence is the broader field built on top of that fingerprint: it analyzes the device's signals to turn the identifier into an actionable risk profile, so fingerprinting is the foundation and device intelligence is the risk-and-analysis layer above it. ShieldLabs Device Intelligence delivers both as one service, fusing 100+ signals across the device, OS, browser, and network into a persistent identifier with a risk score.

What signals does device fingerprinting use?

Device fingerprinting reads the device and browser attributes a machine exposes on every visit: hardware traits like screen, GPU, and device model; the operating system; and browser-level rendering and configuration signals. Together they form one device fingerprint. ShieldLabs fuses 100+ of these device and browser signals and adds the network and connection layer on top, so no single attribute has to carry the match.

How is a Device ID different from a cookie?

A Device ID is derived from the device, OS, browser, and network themselves, while a cookie is only a tag stored on the browser. A cookie disappears the moment someone clears it or opens an incognito window; a Device ID survives those resets because it's computed from the device itself, not from anything the browser stores. ShieldLabs returns the same Device ID for returning visitors and users even after cookies are cleared.

How accurate is device identification?

Device identification reaches up to 99% accuracy when it combines layers instead of trusting any single value, so a match holds even when one attribute is shared or spoofed and false positives stay low. ShieldLabs reaches that accuracy by corroborating device, OS, browser, and network signals against each other, never treating one signal as proof.

Does device intelligence work in incognito mode or when cookies are cleared?

Yes. Device intelligence keeps recognizing the same device after cookies are cleared or in incognito mode, because the identifier never depends on anything the browser stores. ShieldLabs builds it from device, OS, browser, and network attributes that don't depend on cookies, local storage, or session storage.

Can device intelligence be bypassed with proxies or anti-detect browsers?

Device intelligence is hard to bypass because evasion tools leave visible inconsistencies, so deep masking stays identifiable rather than invisible. ShieldLabs flags both the evasion tool itself and the cross-layer mismatches it creates, then correlates repeated evasion into patterns indicating coordinated abuse.

Is device fingerprinting legal and privacy-friendly?

Device fingerprinting for fraud prevention identifies devices as technical entities, not named individuals, and how you use that data is governed by your own privacy policy and the regulations you operate under. ShieldLabs collects device, OS, browser, and network signals, never names, emails, or payment data, and provides a technical signal rather than a legal determination.

How is ShieldLabs different from open-source fingerprinting libraries?

Open-source fingerprinting libraries give you a browser-only fingerprint that you host and maintain yourself, and it weakens against browser updates, anti-detect browsers, and spoofing. ShieldLabs combines device, browser, and network signals into a more stable, spoof-resistant identifier, and delivers it as a managed service you can run in 5 minutes instead of building and maintaining it in-house.

Device Intelligence Solution

Identify devices so you can prevent fraud

Spot the repeat offenders, multi-accounting, and fraud rings hiding in your traffic, with device fingerprinting and up to 99% accuracy

Start Free

ShieldLabs device intelligence recognizes one persistent Device ID across Windows, macOS, Chrome, Firefox, and mobile devices

Stop fraud and abuse at the root

Keep repeat abusers and fraud rings off your promos, trials, and payouts

Cut friction for real customers

Trusted customers convert without extra checks, so fewer drop off

Base decisions on real traffic

Conversion, CAC, and LTV reflect real users, not traffic padded with fakes

Skip the in-house build

Get fraud signals without building or maintaining detection yourself

Know the device behind every visit

100+ signals across the device, OS, browser, IP, and network fuse into one persistent and accurate identifier

Device fingerprinting flow: 100+ signals from browser, OS, and network fuse into one persistent Device ID with risk score

One device, one identity

One stable ID per device that recognizes returning visits

Sees through the disguise

Users trying to hide their device's true configuration get flagged, even when each detail looks clean

Connects every account behind a device

See every account, session, and visit that traces back to one device

Any device, browser, and OS

Identify the device type on web and mobile, including its browser and operating system

More than just device intelligence

Accurate Identification

Identify returning visitors and users across sessions, cleared cookies, incognito mode, and rotated IP

Anonymity Signals

Detection of VPN, proxy, Tor, anti-detect browser, IP reputation and other anonymity signals on every visit, with up to 99% accuracy

Risk Score

A ready-to-use score reflecting the risk of each visit, with the weight of every signal behind it

Ready-Made Patterns

Detection of the hidden connections between accounts that may signal multi-accounting, account farms, and more

Real-Time Analytics

See how much of your traffic is masked, with an overall quality score and a breakdown of the sources sending your visits

Catch the fraud hiding in every flow

Account takeover

Flag a login from a device the account has never used

Multi-accounting

Surface the accounts that all trace back to one device

Account sharing

See when one account is used from too many distinct devices

Payment fraud

Flag checkout sessions from devices hiding their real location

Start preventing fraud in 5 minutes

Easily integrate into any signup, login, or checkout flow

1
Create your account
Get 5,000 free identifications
2
Install the snippet
It identifies every visitor and returns their anonymity signals and a risk score
3
Check your traffic quality
See how much of your traffic is masked, with an overall traffic score
4
Use the API and Webhooks
Apply the risk score and anonymity signals in your rules to stop fraud and abuse