What is ecommerce fraud?

Ecommerce fraud is any deceptive activity targeting online stores or their shoppers, and it splits into two layers that need different tools. Transaction layer: fraudulent payments and orders: chargeback fraud, friendly fraud, card-not-present fraud, card testing, and return or refund fraud. Covered by a chargeback-prevention or payment-fraud platform; Account layer: one person operating many accounts to claim discounts, coupons, welcome offers, referral credits, and loyalty rewards more than once (multi-accounting, account farms), plus account takeover of real customers' logins. Covered by an account-layer identification tool. ShieldLabs covers the account layer. It surfaces abuse patterns indicating one person behind many accounts and logins from unrecognized devices, using persistent visitor and user identification that holds across sessions regardless of email, IP, or browser.

How do I prevent ecommerce fraud?

You prevent ecommerce fraud by stacking a few layers, because no single tool covers all of it. Most stores run two or three of these together: Payment layer: a chargeback-prevention or payment-fraud platform screens transactions, cards, and card-not-present risk; Authentication layer: multi-factor authentication, strong password rules, and step-up checks on high-risk logins cut down account takeover; Policy layer: your store's own promo rules: limits per customer, device, payment card, or shipping address; rate-limits on coupon redemption; delayed reward payouts; Account layer: an identification tool surfaces patterns indicating one person operating many accounts and logins from unrecognized devices, so your code can hold or step up before a discount is issued. ShieldLabs is the account layer. It returns a risk score and a signal breakdown on the first visit, so your rules can act before a discount is claimed or a reward is paid.

How does ShieldLabs prevent ecommerce fraud and abuse?

ShieldLabs runs through a single JavaScript snippet on your signup, login, or account page and returns the signals your rules need to act on a high-risk account before a discount is issued. On every visit it returns: A 0-100 risk score with a per-signal breakdown; Persistent visitor and user identification that holds across cleared cookies, incognito mode, and rotated IP; Anonymity signals: VPN, proxy, Tor, anti-detect browser, and IP reputation; Abuse patterns in analytics, including multi-accounting and account farms; when many signups trace back to one device, browser, or identity, the multi-accounting pattern fires automatically. ShieldLabs delivers the risk score and signals via API and Webhook, so your code can flag, hold, or step up an account before a reward is paid, ShieldLabs scores and surfaces, your rules decide.

Does ShieldLabs stop promo and coupon abuse?

ShieldLabs surfaces the multi-accounting behind promo and coupon abuse, so your rules can hold or limit a discount before it is issued. Promo and coupon abuse is mostly one person creating many accounts to claim a first-order discount, a welcome offer, or a referral credit more than once. It links those accounts through accurate identification, even across cleared cookies and rotated IP; The multi-accounting pattern fires when many signups trace back to one device or identity, so you see the abuse in your own traffic analytics; It decides nothing automatically and blocks nothing on its own, it returns the score and the signal breakdown. ShieldLabs gives your rules the evidence to make the call before a discount is issued.

Does ShieldLabs work for any kind of online store?

Yes. The mechanism is the same wherever one person can profit by opening many accounts or by getting into an account that is not theirs, so the same signals apply across store types. ShieldLabs surfaces patterns indicating multi-accounting, account farms, and account-takeover logins at signup and login; your rules then act on the downstream abuse each store cares about: DTC brands and online retail: first-order-discount farming and coupon stacking; Subscription commerce: free-trial cycling and welcome-offer abuse; Loyalty and rewards programs: points inflation and referral-credit fraud; Any store with a login: account hijacking and the support cost of recovering compromised accounts. ShieldLabs identifies the visitor and user behind each account at the signup and login layer, so your rules decide whether to allow, hold, or step up.

Is ShieldLabs a good fit for small and mid-sized online stores?

Yes. ShieldLabs is self-serve and turns on without a sales call, so a lean team can act on a risk score instead of reviewing accounts by hand. A small or mid-sized store loses real money to the same account abuse a large one does, one person farming first-order discounts, stacking coupons, or cycling welcome offers under fresh accounts. Sign up, add one JavaScript snippet to your signup and login pages, and you are running in about 5 minutes; The free tier includes 5,000 one-time identifications, no credit card required; Pick a plan by your traffic rather than starting on an enterprise contract, so it fits a small store and grows with a mid-sized one. ShieldLabs surfaces abuse patterns at signup and login, giving a small team enterprise-grade detection at transparent pricing.

Is ShieldLabs ecommerce fraud prevention software?

Yes. ShieldLabs is ecommerce fraud prevention software for the account layer, a tool you integrate to surface fraud and abuse automatically rather than reviewing accounts by hand. It is software you integrate, not a managed review service or a chargeback-guarantee product. Installs as one JavaScript snippet on your signup, login, and account pages; Returns a risk score and anonymity signals through a REST API and Webhooks, with abuse patterns visible in analytics; Identifies the visitor and user, then surfaces anonymity signals and abuse patterns; your own rules decide whether to allow, hold, or step up an account; Pairs with a dedicated payment-fraud platform for the payment and chargeback side, which it does not cover. ShieldLabs is the software that covers the fake-account, promo-abuse, multi-accounting, and account-takeover layer.

How do I integrate ShieldLabs into an ecommerce store?

You integrate ShieldLabs by adding one JavaScript snippet to your signup, login, or account page; integration takes about 5 minutes. The steps: Install the snippet on your signup, login, or account page; Pass an optional UserHID (a hashed account or user identifier from your own system) once a shopper signs up or logs in; Read the risk score and anonymity signals via REST API and Webhooks for server-side flows; abuse patterns are visible in analytics. ShieldLabs returns the risk score and signals on the first visit, and the free tier includes 5,000 one-time identifications with no credit card, so you can test on real traffic before enabling production rules.

Will ShieldLabs block customers automatically?

No. ShieldLabs blocks nothing automatically, it returns a risk score and a full signal breakdown, and your code decides what to do with it. You set your own thresholds, for example: A mid-range score flags an account for review or a reduced discount; A high score holds a signup or a login for manual review; A low score lets a legitimate shopper through with no extra steps. ShieldLabs keeps the decision in your hands, and the free tier includes 5,000 identifications to test thresholds on real traffic before enabling rules in production.

Ecommerce Fraud Prevention Software

Stop ecommerce fraud
before it drains your revenue

Prevent first-order discount farming, coupon stacking, referral fraud,
loyalty abuse, and account-takeover logins at signup and login

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Keep fake accounts out

Stop one person opening many accounts to farm discounts and rewards

Protect promo and discount budgets

Keep welcome offers, coupons, referral credits, and loyalty rewards with real shoppers

Keep accounts in real hands

Catch account takeover logins from unrecognized devices and anonymized connections

Keep real shoppers moving

Legitimate customers sign up and log in without extra verification steps

How ShieldLabs prevents ecommerce fraud and abuse

ShieldLabs combines 100+ device, OS, browser, IP, and network signals, surfacing anonymity signals and abuse patterns

Accurate Identification

Identify returning visitors and users across sessions, cleared cookies, incognito mode, and rotated IP, even when they sign up as new shoppers

Anonymous Traffic Detection

VPN, proxy, Tor, anti-detect browser, IP reputation and other anonymity signals

Ready Risk Score

A ready-to-use risk model that scores every signup and login 0–100 with signal breakdown

Detect abuse with in-depth pattern analytics

Pre-built patterns indicating multi-accounting, account farms, account takeover, and other abuse patterns

Real-Time Analytics

Aggregate risk score, traffic source attribution, per-session signal breakdown, and active abuse patterns

Prevent ecommerce fraud and abuse in 5 minutes

Easily integrate into any signup, login, or account flow

1
Sign up
Sign up and get 5,000 free identifications.
2
Install snippet
Install one JavaScript snippet on your signup, login, or account page.
3
View analytics
View detailed analytics on anonymity signals, risk scores, and potential abuse in your traffic.
4
Use API & Webhooks
Use the API and Webhooks to prevent abuse.

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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",
  "ip": "62.197.149.124",
  "country": "Lithuania",
  "connection_type": "vpn",
  "os": "Windows",
  "browser": "Chrome",
  "device_type": "desktop",
  "risk_score": 85,
  "signals": [
    { "name": "antidetect_browser", "weight": 60 },
    { "name": "vpn", "weight": 15 },
    { "name": "timezone_mismatch", "weight": 10 }
  ]
}

Protect your store from fraud and abuse today

Free 5,000 one-time identifications, with transparent pricing that scales with your needs

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Stop ecommerce fraudbefore it drains your revenue