CVV attack log analysis is the work of reading authorization, gateway, and web server logs to find card-testing traffic before it turns into chargebacks. A CVV attack, often called card enumeration or a BIN attack, appears as many small authorization attempts spread across many card numbers but coming from a small set of IPs and devices. The point of the analysis is to confirm the pattern, measure its size, and cut it off.
Prerequisites
- Gateway and processor authorization logs with timestamps normalized to UTC
- Web server or WAF logs covering the same time window
- Order and account records for the same period
- A query tool or spreadsheet that can group by IP, BIN, and email domain
- Authority to pause payment endpoints and contact your acquirer
How to Analyze the Logs
- Pull the window. Export authorization logs for the last 30 days plus the 7 days before the earliest suspected attempt so you have a baseline for comparison.
- Normalize the fields. Keep timestamp, IP, card BIN, response code, order value, email, and user agent. Remove full card data from the working copy.
- Group by response code. Count declines by code. A spike in CVV mismatch or do-not-honor responses inside a short window is the first sign.
- Rank IPs by attempt count. Sort by the number of distinct card numbers per IP. Automated attacks push many cards through few addresses.
- Rank BINs. Count attempts per BIN. One BIN or a narrow BIN range holding most of the traffic points to an enumeration run.
- Check timing. Plot requests per minute. Scripted traffic holds a steady rate while real shoppers arrive in irregular bursts.
- Compare order values. Card testing leans on small or minimum amounts. Flag clusters of identical low values.
- Cross-check account data. Look for disposable email domains, sequential addresses, and accounts created within the same hour.
- Match against web logs. Confirm the source IPs hit the checkout or payment endpoint directly without browsing product pages first.
- Size the exposure. Count approved attempts as well as declines. Approved attempts are the ones that become chargebacks.
Signals That Separate an Attack From Normal Traffic
- Many card numbers, few IPs or devices
- High decline rate inside a narrow window
- Uniform intervals between requests
- Low and repeated order values
- No session history before the checkout step
- Traffic that ignores site navigation entirely
What to Do After Triage
- Block or rate-limit the source IPs and ASNs at the edge.
- Add a CAPTCHA or device check to the payment step.
- Tighten velocity rules on attempts per IP, per email, and per device.
- Require CVV and AVS checks on every attempt.
- Notify your acquirer and processor with the timestamps and counts.
- Void or refund approved test orders before shipment.
- Preserve the raw logs and hash them as evidence.
- File a complaint with the FBI Internet Crime Complaint Center.
- Review PCI DSS log retention requirements and confirm 12 months of history is available.
- Re-run the analysis weekly for a month to confirm the traffic has stopped.