Referral Fraud Prevention
Referral fraud prevention.
Reward real advocates.
Self-referrals and automated signups can turn customer acquisition into duplicate rewards. ShieldLabs detects multi-accounting and bots around referral claims so payouts follow genuine referrals.
Start FreeInvite a friend
Earn a reward when they join.
ProxyBrowser automation
Keep rewards for real advocates
Help stop one participant collecting both sides of a referral incentive.
Stop automated referral farming
Keep bots from inflating referred signups and reward claims.
Keep acquisition meaningful
Keep referral growth tied to newly acquired customers.
Protect reward actions
Help keep takeover and risky access from abusing referral rewards.
Self-referral detection
Stop self-referrals.
Reward real advocates.
ShieldLabs detects multi-accounting at referred signups to help stop self-referrals and keep rewards for genuine advocates.
Reward qualification
Protect referral rewards
beyond the signup.
Bots can reach the actions that qualify a referred user for rewards. ShieldLabs detects browser bots at activation and claims to help protect referral payouts and keep reported referral growth credible.
Protect referred accounts
Detect account takeover around referred customers and sensitive reward actions.
Expose masked reward activity
Detect proxies and anti-detect browsers at the action that earns a referral reward.
The ShieldLabs platform
More than an invitation.
The identities behind the reward.
Use account links, identification, bot detection, device and network evidence and risk assessments around referred signups. Traffic analytics helps explain the sources bringing those visits.
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.
Identification accuracy
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.
Bot & AI traffic detection
Detect bot activity from browser automation signals. Recognize useful crawler and AI traffic alongside abuse detections.
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.
203.0.113.42198.51.100.23Traffic quality scoring and risk analytics
Get one score for all your traffic and ready-made quality results by source, channel, referrer and UTM campaign.
Analytics dashboard
Investigate referred accounts.
Follow the relationships behind them.
Get linked-user detections, signup risk assessments and ready-made account abuse detections. Results can be integrated with the inviter, invitee and reward records in your referral program.
How it works
Start protecting your product.
Connect once and start receiving ready-made fraud and abuse detections.
- 01
Add the snippet or SDK
Connect your product and start identifying visitors and users.
- 02
Receive ready-made detections
Get detected fraud and account abuse in the dashboard or through API integrations.
- 03
Prevent fraud and abuse
Protect customer accounts, paid access and signup incentives in your product.
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.
Protect your users and product
Make abuse visible.
Keep genuine users moving.
Start Free FAQ
Understand the evidence.
Put it to work.
What is referral fraud?
Referral fraud is the misuse of a referral program to earn rewards without bringing genuine new customers, including self-referrals and automated participation.
How does ShieldLabs help prevent referral fraud?
ShieldLabs detects multi-accounting at referred signups, plus bots and risky account access at reward-qualifying actions. Protect referral rewards from repeated and automated participation.
What is self-referral fraud?
Self-referral fraud is referral program abuse: one participant creates or operates additional accounts to collect rewards intended for referring new customers. Multi-accounting detection exposes the relationship behind those registered accounts.
Can different email addresses hide a self-referral?
ShieldLabs detects multi-accounting across accounts with different names or email addresses. Invitation and reward records come from your referral program.
Does ShieldLabs track referral commissions?
Referral codes, conversion qualification, commissions and payout status are supplied by your product. ShieldLabs provides the identity and abuse context behind the participating accounts.
Can detection continue after the referred account signs up?
Yes. Add ShieldLabs to browser-based activation and reward-qualifying actions. Bot, masking and account takeover detections help protect the action that earns a referral payout.