Protect your revenue
Catch repeated trial signups, bonus abuse and account sharing before they eat into your margins.
Stop abuse of
your product.
Detect risky users, visitors and bots under any masking so you can stop multi-accounting, account sharing and takeovers before they start costing you money.
[email protected]Dangerous
[email protected]Dangerous
[email protected]Dangerous
[email protected]Dangerous
[email protected]Dangerous
Multi-accountingProtect your ad budget
Spot risky traffic and fake signups, so your acquisition spend goes toward real users.
Trust your metrics
See which users and traffic sources are trustworthy, so your growth decisions reflect reality.
Reduce manual review
Bring visitor history, linked users and named risk signals together, so reviews start with clear evidence.
Use cases
Different kinds of abuse.
One layer of intelligence.
Someone signs up again, shares a login or clicks your ad. See how ShieldLabs recognizes visitors, detects linked users and reveals risk in everyday activity.
Multi-accountingThree signups.
Three signups.
One person.
One user creates multiple accounts with different email addresses to claim the same benefit. ShieldLabs detects multi-accounting behind these signups out of the box.
See all use casesThe ShieldLabs platform
The intelligence behind
fraud and abuse prevention.
Get identification, risk signals, account abuse detection and traffic quality analytics in one ready-to-use platform to prevent fraud and abuse.
Enterprise-level functionality. Without enterprise pricing.
Accurate identification
Recognize returning visitors even when they clear cookies, use incognito mode or change their IP address. Detect linked users with different email addresses.
99.9%
Identification accuracy
UsersDevicesVisitorsPublic IPsLocal IPsCookiesSessions
High-Risk Event detection
Detect account abuse out of the box by automatically identifying linked users. No fraud model training is required.
Risk signals
Get ready-made detections of automation, masking and spoofing, with named risk signals behind each result.
VPNProxyPrivate RelayTor NetworkCheck IncompleteAnti-Detect BrowserBanned IPIncognito modeGood botTimezone MismatchBad bot
Bot & AI traffic detection
Detect bots, scripts and browser automation. Separate useful bot and AI traffic from abusive activity.
Risk scoring
Score every visit from 0 to 100 and classify it as trusted, suspicious or dangerous. See the signals behind each score.
Device fingerprinting
Recognize devices by their fingerprints. Identify the browser, operating system and device type. Detect headless browsers and tampering.
IP & Network Intelligence
Reveal the real IP address and geolocation behind masking. Detect VPNs, proxies and private relays.
Visible IPUnited States
203.0.113.42Real IPGermany
198.51.100.23Traffic quality scoring and risk analytics
Get one score for all your traffic and ready-made quality results by source, channel, referrer and UTM campaign.
13Trusted
0100
Trusted61.0%Suspicious24.5%Dangerous14.5%
Analytics dashboard
Explore your traffic.
Understand risk and behavior.
Start with an overview of traffic quality, then investigate individual users or visits. Explore risk signals, linked identities, visit history and source attribution in the dashboard.
Developers
Integrate in
5 minutes.
A single API to identify, detect and score. Receive risk data through API responses and webhooks. Integrate selected data points into your business logic to prevent fraud and abuse.
Recognize risk. Protect your growth.
Make abuse visible.
Keep your product moving.
Start Free Frequently asked questions
- What is ShieldLabs?
Fraud detection and prevention software helps digital products identify risky traffic and abusive account activity. ShieldLabs combines device, browser, operating-system, IP, and network signals to assess visits and surface ready-made detections.
ShieldLabs also scores traffic quality and makes results available in the dashboard, API, and webhooks.
- What does ShieldLabs detect?
Fraud and abuse detection covers masked connections, automated traffic, and suspicious account activity. ShieldLabs detects VPNs, proxies, Tor, Apple Private Relay, anti-detect browsers, browser automation, bots, AI agents, and risk signals such as operating-system and timezone mismatches.
ShieldLabs also detects multi-accounting, account sharing, account takeover, and impossible travel as ready-made High-Risk Events.
- How does ShieldLabs assess traffic risk?
Traffic risk assessment combines more than 300 signals from the device, browser, operating system, IP address, and network. Each detected risk signal is returned by name, and a Risk Score summarizes the visit on a 0–100 scale.
ShieldLabs reports 99.9% identification accuracy and 99.9% risk signal detection accuracy. The score remains explainable through the signals that contributed to it.
- How does ShieldLabs detect multi-accounting?
Multi-accounting is when one person operates multiple accounts on a product. ShieldLabs detects multi-accounting by correlating account activity with visitor, device, and network context, including activity across different email addresses.
The default detection threshold is three accounts per visitor and can be adjusted in the dashboard. The result is a multi-accounting finding, not a report of linked registrations.
- Does ShieldLabs detect bots and AI traffic?
Bot detection identifies automated traffic, including browser automation and AI agents, and helps distinguish useful bots from abusive automation.
ShieldLabs returns bot and AI traffic signals alongside device and network context, so a product can assess whether the visit is relevant to its own fraud and abuse workflow.
- Can I try ShieldLabs for free?
ShieldLabs offers 5,000 free identifications, with no credit card required. The free tier lets you integrate the product and review detection results before choosing a paid plan.
Start Free from the ShieldLabs site to create an account and connect your product.
Fraud detection and prevention software helps digital products identify risky traffic and abusive account activity. ShieldLabs combines device, browser, operating-system, IP, and network signals to assess visits and surface ready-made detections.
ShieldLabs also scores traffic quality and makes results available in the dashboard, API, and webhooks.
Fraud and abuse detection covers masked connections, automated traffic, and suspicious account activity. ShieldLabs detects VPNs, proxies, Tor, Apple Private Relay, anti-detect browsers, browser automation, bots, AI agents, and risk signals such as operating-system and timezone mismatches.
ShieldLabs also detects multi-accounting, account sharing, account takeover, and impossible travel as ready-made High-Risk Events.
Traffic risk assessment combines more than 300 signals from the device, browser, operating system, IP address, and network. Each detected risk signal is returned by name, and a Risk Score summarizes the visit on a 0–100 scale.
ShieldLabs reports 99.9% identification accuracy and 99.9% risk signal detection accuracy. The score remains explainable through the signals that contributed to it.
Multi-accounting is when one person operates multiple accounts on a product. ShieldLabs detects multi-accounting by correlating account activity with visitor, device, and network context, including activity across different email addresses.
The default detection threshold is three accounts per visitor and can be adjusted in the dashboard. The result is a multi-accounting finding, not a report of linked registrations.
Bot detection identifies automated traffic, including browser automation and AI agents, and helps distinguish useful bots from abusive automation.
ShieldLabs returns bot and AI traffic signals alongside device and network context, so a product can assess whether the visit is relevant to its own fraud and abuse workflow.
ShieldLabs offers 5,000 free identifications, with no credit card required. The free tier lets you integrate the product and review detection results before choosing a paid plan.
Start Free from the ShieldLabs site to create an account and connect your product.
