Stop fraud and abuse at the root
Keep repeat abusers and fraud rings off your promos, trials, and payouts
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 99.9% identification accuracy
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
300+ signals across the device, OS, browser, IP, and network fuse into one persistent and accurate identifier
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
Risk Signals
Detection of VPN, proxy, Tor, anti-detect browser, IP reputation and other risk signals on every visit, with 99.9% risk signal detection accuracy
Risk Score
A ready-to-use score reflecting the risk of each visit, with the weight of every signal behind it
High-Risk Events
Direct detection of Multi-accounting, Account sharing, Impossible travel, and Account takeover, each with Medium or High confidence
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 risk 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
Act on the risk score and risk signals in your backend to stop fraud and abuse
api.shieldlabs.ai/v1/visits/latest
{
"request_id": "0c284695-cf0b-4755-8beb-0a2e9536595e",
"visitor_id": "aa8c616a-8a25-4a5e-bee2-a9a08e5128a4",
"device_id": "6a45967d-1371-9652-ba99-b01ea3992208",
"user_hid": "u_9f2a41c7",
"public_ip": { "ip": "62.197.149.124", "country": "United States" },
"local_ip": { "ip": "45.83.91.7", "country": "United States" },
"connection_type": "vpn",
"os": "Windows",
"browser": "Chrome",
"device_type": "desktop",
"risk_score": 85,
"signals": [
{ "name": "os_mismatch", "weight": 60 },
{ "name": "vpn", "weight": 15 },
{ "name": "timezone_mismatch", "weight": 10 }
]
}See the device behind every account
Get persistent identifiers, risk signals, and High-Risk Events running on your site in 5 minutes
Frequently asked questions
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 300+ signals across the device, OS, browser, and network into a persistent identifier with a risk score.
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 combines these device and browser signals with the network and connection layer, 300+ signals in total, so no single attribute has to carry the match.
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.
Device identification reaches 99.9% 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.
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.
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 links repeated evasion across accounts to detect High-Risk Events such as Multi-accounting and Account takeover.
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.
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.