ShieldLabs
ShieldLabs is a fraud detection and prevention service for web applications. It builds a persistent identifier from 300+ device, network, browser, and OS signals collected on the first page load, so the same visitor can remain recognized across cleared cookies, rotated IPs, and incognito sessions. It turns anonymous traffic into a risk score for each visitor and links visitors, devices, and accounts into a single identity graph. The platform provides out-of-the-box detection for account takeover, account sharing, multi-accounting, promo and bonus abuse, free trial abuse, ad and traffic fraud, and traffic quality checks. It also recognizes returning trusted visitors to reduce repeated checks and friction. Risk signals include country, IP address, proxy/VPN, datacenter IP, anti-detect browser, abuser, incognito, suspicious paid click, device fingerprint, geolocation, and returning visitor signals. ShieldLabs is offered as a hosted web service with a free tier of 5,000 identifications, a 5-minute setup, and no credit card required. It targets industries such as AI, iGaming, cryptocurrency, SaaS, fintech, e-commerce, travel, marketplaces, media and streaming, ticketing, and gaming. Pricing beyond the free tier is not specified on the homepage.
- Category
- AI API
- Pricing
- Unknown
Problem solved
ShieldLabs solves the problem of anonymous and masked abuse in web applications by turning device, network, and browser signals into a persistent visitor identity and risk score. It helps teams detect multi-accounting, account sharing, account takeovers, promo abuse, free-trial abuse, and bot-driven ad fraud before they impact revenue, ad spend, and business metrics.
Use cases
- Detect multi-accounting and duplicate signups from the same device or user.
- Identify account sharing beyond a single household for subscription or paid accounts.
- Prevent account takeover by spotting logins with stolen credentials, proxy/VPN use, or anti-detect browsers.
- Stop promo, referral, and sign-up bonus abuse across throwaway accounts.
- Detect free trial abuse from users cycling through fresh emails on the same device.
- Filter bot clicks, datacenter traffic, and click farms from paid ad campaigns.
- Score traffic quality and separate real signups from fake ones.
- Recognize returning trusted visitors on first request to reduce friction.
Audience
- Developers
- Business Users
- Enterprise
- Startups
- Product Managers
Pros
- Combines 300+ device, network, and browser signals into a persistent visitor identity.
- Detects multiple fraud categories out of the box, including multi-accounting, account sharing, account takeover, promo abuse, free trial abuse, and ad fraud.
- Provides explainable risk signals and a single risk score for each visitor.
- Free tier includes 5,000 identifications, 5-minute setup, and no credit card required.
- Recognizes returning trusted visitors to reduce friction and repeated checks.
Cons
- Pricing beyond the free tier is not publicly specified on the homepage.
- No public GitHub repository or open-source code is available for inspection.
- Exact technical implementation, data retention, and compliance details are not fully documented on the homepage.
- Requires integration into a web application to collect client-side signals.
- Risk scoring may produce false positives that need manual review or tuning.
Official website: https://shieldlabs.ai/
Canonical LambdaBase page: https://www.lambdabase.com/tools/shieldlabs