Questions and Answers: Mistakes and Ban Protection 🚫

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Questions:
  • Why does the site see my IP even if I'm on VPN?
  • How to avoid being included in fraud detection lists?
  • How to avoid behavioral analysis?
  • Why am I being blocked after several orders?
  • How not to lose your account after 2-3 spikes?
  • How do you know if your account is on fire?
  • How to restore a blocked account?
  • How to avoid repeated use of cookies?
  • Why do some BINs no longer work?
  • How to determine that the card is already in the databases?

Below you will find a detailed technical analysis of the reasons for blocking, methods for bypassing checks and protecting accounts - all this can be used for training cybersecurity specialists, security testing and vulnerability analysis.

1. Why does the site see my IP even if I'm on VPN?​

Possible reasons:​

  • WebRTC Leak: Browser may reveal your real IP via API.
  • DNS Leak: Some DNS servers may send requests outside the VPN.
  • IPv6 is not disabled: Many sites can identify you via IPv6 if it is not disabled.
  • Poor VPN: Untrustworthy services may leak your IP to third parties.
  • Caching cookies: The site remembers you from previous visits.
  • Geolocation data (GPS, geo-IP): Determined by the browser or device.

Solution:
  • Test yourself on ipleak.net
  • Disable WebRTC via plugins
  • Use private DNS (Cloudflare 1.1.1.1, Quad9)
  • Disable IPv6

Objective: Study of vulnerabilities in anonymization, development of protection protocols.

2. How to avoid being included in fraud detection lists?​

Fraud detection systems analyze many factors.

Tip:​

  • Use residential proxy instead of datacenter.
  • Don't repeat behavior (click rate, time between actions).
  • Data matches: name, address, phone, email, map.
  • Do not use the same User-Agent/Cookie/Canvas.
  • Work with clean accounts and burner data.

Objective: Analysis of fraud detection algorithms, development of masking protocols.

3. How to avoid behavioral analysis?​

Modern systems use behavioral analytics to identify bots and attackers.

How to get around:​

  • Use human behavior:
    • Delays between actions
    • Different text input speeds
    • Random mouse movement
  • Use real devices or VPS
  • Don't use the same click path
  • Avoid automated scripting without randomization
  • Use antidetect browsers (Octo, Dolphin Anty)

Objective: To study machine learning in anti-fraud, to develop countermeasure protocols.

4. Why am I blocked after several orders?​

Reasons for blocking:​

  • Suspicious activity (frequent orders from one account/IP).
  • Data mismatch (IP ≠ card address ≠ delivery address).
  • Reusing the same card.
  • Activate multiple accounts from one device.
  • Testing cards → high chargeback level.
  • Suspicious geolocation (for example, an order from the USA, but the IP is from Russia).

Solution:
  • Use unique IPs and accounts.
  • Take breaks between orders.
  • Use new cards and burner accounts.

Objective: Research of detection systems, development of masking protocols.

5. How not to lose your account after 2-3 spikes?​

Reasons for losing an account:​

  • Amazon, eBay, etc. systems remember your device/browser.
  • Frequent changes of IP or location raise suspicion.
  • Frequent changes in payment information.
  • Activation via different devices.
  • Violation of the terms of use (eg dropshipping).

Recommendations:
  • Use anti-detect browsers (Octo Browser, Dolphin Anty).
  • Don't jump between IPs/devices.
  • Data match (login, password, email, IP).
  • Make sure cookies and localStorage are cleared when changing accounts.

Objective: Study of verification mechanisms, development of protocols for working with accounts.

6. How to understand that the account is "on fire"?​

A "hot" account is one that has already been noticed as suspicious.

Signs:​

  • The introduction of reCAPTCHA v2/v3.
  • Request for phone/email verification.
  • Account blocked without explanation.
  • Unusual questions at the entrance.
  • Request for photo ID or document.
  • Limited functionality (for example, you cannot place an order).

Solution:
  • Do not use the account any further.
  • Switch to a new burner account.
  • Check through other IPs and browsers.

Objective: Analysis of suspicious activity signals, development of early detection protocols.

7. How to restore a blocked account?​

Recovery options:​

  • Contact support with a legitimate history.
  • Use old email or phone for recovery.
  • Send a photo ID (if the system requires it).
  • Try to log in from a different IP and device.
  • If the account is "clean", you can try resetting cookies and proxies.

  • If the account is already blacklisted, recovery is impossible.
  • Hacking attempts may result in a ban.

Objective: Research of recovery systems, development of protection protocols.

8. How to avoid repeated use of cookies?​

Cookies can link multiple accounts and lead to a ban.

Methods:​

  • Using anti-detect browsers (Octo, Dolphin).
  • Clearing cookies between sessions.
  • Using incognito mode.
  • Separate accounts into different browser profiles.
  • Using different VPS/VM for each account.

  • Cookie AutoDelete (Firefox/Chrome extension)
  • Clear Cache Button
  • Incognito mode

Objective: Study of tracking mechanisms, development of anonymity protocols.

9. Why do some BINs no longer work?​

BIN (Bank Identification Number) may be added to blacklists for several reasons.

Reasons:​

  • High level of chargeback.
  • Often used in fraud.
  • Compromise in mass leaks.
  • Blocked by the bank.
  • Decrease in the quality of the BIN (for example, a change in the bank's policy).

How to check:
  • Use Checker API
  • BIN-checker
  • Test purchase with a small check

Objective: Analysis of vulnerabilities in payment systems, development of verification protocols.

10. How to determine that the card is already in the databases?​

If the card is already on the list, its use will result in a refusal.

Signs:​

  • Refusal on first purchase.
  • Message: “Card Declined”, “Fraud Detected”.
  • Request for phone/email verification.
  • Automatically log out of your account.
  • Suspicious activity has been recorded.

How to check:​

  • Try buying something for $1–$5.
  • Use Checker API.
  • Check that the data matches (IP, address, email).
  • Check your card usage history via Fullz.

Objective: Leak analysis, development of verification protocols.

Conclusion:​

These topics are at the intersection of fraud, security and behavioral analysis. Studying them allows you to:
  • Develop more resilient security systems.
  • Create behavioral analytics models.
  • Test existing solutions for vulnerabilities.
  • Train cybersecurity professionals.
 
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