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Card Testing on a SaaS: How to Respond to Bots Using Distributed IPs

Card-testing bots probe signup, card-saving, and checkout flows with stolen payment details. Investigate behavior across the full payment path and layer defenses beyond IP blocking.
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Card-testing bots probe a SaaS checkout, payment setup, or card-saving flow with stolen payment details to find which cards still work. Respond with layered controls: limit sensitive actions, validate sessions, challenge suspicious traffic, apply payment-risk rules, and watch behavior across accounts, devices, and requests. A VPN or unfamiliar IP alone does not prove fraud, and no single control guarantees the attempts will stop.

The question’s wording does not establish which service, endpoints, or defenses were involved—or what outcome followed. Here is a practical response based on documented payment and network guidance.

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What card testing looks like

Stripe defines card testing as scripts or manual attempts to determine whether stolen card numbers remain active. It can show up as rapid low-value payment attempts, but probing may also happen when someone creates accounts or attaches payment methods without completing an ordinary purchase. Visa describes automated injection of payment-account details into checkout pages as an account-testing scheme.

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That means a dashboard showing only successful charges can miss relevant activity. Review the whole path from account creation through card attachment, setup or authorization, and payment—not just settled transactions.

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Sources: Stripe Support: How do I prevent card testing attacks?; Stripe, Radar: Rules 101; Visa guidance on enumeration attacks and account testing schemes.

How to investigate suspected attempts

Map the affected actions

Identify which endpoints and payment actions are receiving suspicious traffic: signup or customer creation, adding or saving a card, setup or authorization, and low-value charges. Correlate events across those steps; one request in isolation may look ordinary.

Compare behavior with your baseline

Look at request and transaction velocity, approvals and declines, cards attached per customer, customers created per source, account age, and any available device or session signals. Establish thresholds from your own normal traffic and customer journey. The sources do not establish a universal safe threshold.

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Distributed traffic makes IP-only detection incomplete: an attack can spread requests across many addresses. VPN use or an unfamiliar address can be a clue to investigate, not proof that a particular customer or request is fraudulent.

Account for changing patterns

In a January 15, 2025 engineering account, Stripe described verification attacks using higher-quality stolen-card datasets, which increased authorization rates and made low authorization rates a less dependable signal in that campaign. Treat this as a documented shift, not a pattern every attack will follow; use multiple signals rather than relying on declines alone.

Source: Stripe Engineering, How Stripe Radar responded to a new wave of card testing.

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Layer defenses across the payment flow

Limit account and payment actions

Apply rate limits to customer creation and payment-related actions, including cards attached per customer and customers created per IP. Tune limits against legitimate use so that a burst from a real customer does not automatically become a block.

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Validate sessions and add friction selectively

Require valid sessions where the flow calls for an authenticated user. Use CAPTCHA or adaptive verification when risk signals warrant a challenge, rather than assuming every visitor should face the same friction. Stripe’s guidance also recommends considering request attributes in addition to simple counts.

Use signals beyond the IP address

Combine endpoint-level behavior and rate limits with account history, device signals, and bot-management controls. Adaptive verification can add friction when a cluster looks suspicious, even when requests are distributed across many IPs. Stripe’s SaaS/API guidance recommends this layered approach for abuse prevention.

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  • WORKS WITH 1000+ ACCOUNTS: Compatible with Google, Microsoft, and Apple. A single Security Key NFC secures 100 of your favorite accounts, including email, password managers, and more.
  • FAST & CONVENIENT LOGIN: Plug in your Security Key NFC via USB-A and tap it, or tap it against your phone (NFC) to authenticate. No batteries, no internet connection, and no extra fees required.
  • TRUSTED PASSKEY TECHNOLOGY: Uses the latest passkey standards (FIDO2/WebAuthn & FIDO U2F) but does not support One-Time Passwords. For complex needs, check out the YubiKey 5 Series.
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Apply processor-level risk controls

Configure payment-risk rules for suspicious velocity and repeated card or customer patterns, and review processor and network alerts. Stripe Radar is one processor-level option documented for card-testing controls and SaaS fraud use cases; confirm compatibility with your processor, feature availability, pricing, and program terms for your geography and account before choosing it.

Sources: Stripe Support: How do I prevent card testing attacks?; Stripe, Real-time API abuse prevention for SaaS and AI platforms; Stripe Radar.

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Choose controls by where they act and what they see

There is no neutral head-to-head comparison in the cited guidance. Use these dimensions to assess any proposed defense against your existing architecture:

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  • FAST & CONVENIENT LOGIN: Plug in your YubiKey 5 via USB and tap it to authenticate. No batteries, no internet connection, and no extra fees required.
  • MOST SECURE PASSKEY: Supports FIDO2/WebAuthn, FIDO U2F, Yubico OTP, OATH-TOTP/HOTP, Smart card (PIV), and OpenPGP. That means it’s versatile, working almost anywhere you need it.
  • BUILT TO LAST: Made from tough, waterproof, and crush-resistant materials. Manufactured in Sweden and programmed in the USA with the highest security standards.
  • Control location: application, edge or bot-management layer, or payment processor.
  • Signals available: IP and request velocity only, or also payment, device, session, and account history.
  • Response: block, challenge, or queue for review—and what legitimate customers experience.
  • Operational cost: integration effort, false-positive handling, monitoring, and tuning burden.

Validate changes and keep monitoring

Use a payment sandbox to check how the integration handles simulated payment scenarios before changing live behavior. Stripe documents test card numbers and warns that test environments are rate-limited and should not be used for load testing.

After deployment, track both suspected attack activity and false positives, and keep reviewing processor or network alerts. Stripe explicitly cautions that mitigation does not guarantee card testing will cease on an account.

Sources: Stripe Documentation: Test card numbers; Stripe Support: How do I prevent card testing attacks?.

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What published results do—and do not—show

Stripe’s Radar: Rules 101 guide reports an 80% reduction in card testing for businesses using Stripe Checkout with Stripe-managed CAPTCHA, with less than a 2-basis-point (0.02%) authorization-rate impact in the described deployment. These are Stripe-published product results, not an independent guarantee or a prediction for another SaaS.

Separately, Stripe reported that more than 20 million card-testing attempts per day were blocked at the peak of a 2022 wave. That is a historical figure for that wave, not a current daily rate or a measure of the threat facing an individual business.

Sources: Stripe, Radar: Rules 101; Stripe Newsroom, How Stripe responded to a wave of card testing attacks.

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