Evolution of Payment Card Fraud: From Magnetic Stripes to EMV Skimming

[Cloned Boy]

Payment fraud (carding) is constantly adapting to new technologies. Here are the key stages of its development and modern methods of attack.

1. The Magnetic Stripe Era (1960s–2000s)​

Main vulnerabilities:​

• Static data – card number, expiration date, CVV/CVC are stored in clear text.
• Easy cloning – just copy Track 1/Track 2 using a skimmer.

Typical attacks:​

• Skimming is the installation of devices on ATMs to read data.
• Phishing – fake websites/calls to steal data.
• Leak Databases – Selling Card Dumps on the Darknet.

Fraud Peak: In 2012, 60% of all card fraud transactions in the US occurred on the MagStrip.

2. EMV Implementation (2000s – Present)​

EMV (chip and PIN) has made cloning much more difficult, but fraudsters have found new loopholes.

Why is EMV harder to hack?​

• Dynamic cryptograms (ARQC) – unique for each transaction.
• ICC Private Key – stored in the Secure Element.
• Offline authentication (DDA/CDA) – prevents data tampering.

EMV Limitations:​

• Fallback on magnetic stripe – if the chip is not readable, the terminal can use old data (vulnerability!).
• Contact and non-contact attacks – skimming has evolved.

3. Modern methods of EMV fraud​

A. EMV Skimming (Shimmers)​

• What is it? Miniature devices that fit into a chip slot.
• How does it work?
  • Read data during a transaction.
  • Record the PIN (if entered).
  • But! They don't copy ICC Private Key → the clone works only in fallback mode.

B. Pre-play атаки (NFC)​

• What is this? Contactless payment data interception (Apple Pay/Google Pay).
• How does it work?
  • The attacker places the reader in the victim's pocket.
  • Receives a cryptogram and uses it before it expires.

C. Attacks on POS Terminals​

• Malware in terminals (eg Dexter, Chewbacca).
• Firmware substitution – the terminal sends data to scammers.

D. Social Engineering + EMV​

• Phishing with SMS substitution (SIM-swap) – to steal OTP codes.
• Fake call centers – request card details “for verification”.

4. The Future: What Attacks Are Possible?​

Threats to Contactless Payments (NFC):​

• Relay attacks – intercepting the card signal from a distance.
• Tokenization attacks (Apple Pay/Google Pay).

Quantum Computing:​

• RSA may be hacked in the future (but EMVCo is already testing post-quantum cryptography).

5. How are payment systems protected?​

Method	Description
Cancel fallback	Visa/Mastercard block magstripe transactions if the chip fails.
Tokenization	Apple Pay/Google Pay use one-time tokens instead of real PAN.
Biometrics	Face ID, Touch ID for payment confirmation.
Behavior Analysis	AI identifies suspicious transactions (e.g. payments from different countries).

Conclusion​

• Magnetic stripes are almost dead due to ease of cloning.
• EMV is secure, but fraudsters attack through skimming, POS hacks and social engineering.
• The future belongs to contactless payments with tokenization and biometrics.

For legal research:

• Study EMVCo specs, PCI DSS.
• Test vulnerabilities through Bug Bounty (HackerOne, Cobalt).

Want an analysis of a specific attack (for example, how the Shimmer device works)? Or methods for protecting POS terminals?

 

[jasd001]

Yes, We want an analysis of a specific attack -

• Relay attacks – intercepting the card signal from a distance.
• Tokenization attacks (Apple Pay/Google Pay).

 

[Cloned Boy]

Analysis of Payment System Attacks: Relay & Tokenization​

(For Carding Research Purposes Only)

1. Relay Attacks on Contactless Payments (NFC/RFID)​

Definition: Intercepting and retransmitting contactless card signals to bypass proximity limits.

How It Works​

1. Signal Interception:
   • Attacker uses an NFC reader (e.g., Proxmark3) to capture data from a victim’s card/wallet (up to ~1m away).
   • Example: Card emulates a payment while still in the victim’s pocket.
2. Data Relay:
   • Transmits intercepted data to an accomplice at a POS terminal (e.g., via Bluetooth/Wi-Fi).
   • Critical Limitation: Requires real-time relay (delays >300ms often fail).
3. Transaction Approval:
   • Terminal processes the relayed signal as legitimate.

Mitigations​

Countermeasure	Effectiveness
Distance bounding protocols	Limits relay speed (e.g., EMV’s 10cm range).
Transaction Timeout	Fails if relay is too slow.
Biometric Confirmation	Apple/Google Pay require Face ID/Fingerprint.

Research Papers:

• "Practical Relay Attack on Contactless Transactions" (USENIX Security 2015).

2. Tokenization Attacks (Apple Pay/Google Pay)​

Definition: Exploiting weaknesses in token generation/transmission.

Attack Vectors​

A. Token Replay

• Scenario: Intercepting a one-time token (e.g., via MITM) and reusing it before expiry.
• Mitigation: Tokens are cryptographically bound to:
  • Device ID (Secure Element).
  • Transaction context (amount, merchant).

B. Enrollment Fraud

• Scenario: Adding a stolen card to a mobile wallet using social engineering (e.g., SIM-swap to bypass OTP).
• Mitigation: Multi-factor auth (e.g., issuer verification calls).

C. Tokenization Server Breaches

• Scenario: Hacking payment processors (e.g., Visa Token Service) to generate fake tokens.
• Mitigation: Hardware Security Modules (HSMs) protect root keys.

Real-World Example​

• 2019 "Express Transit" Bypass: Attackers exploited Apple Pay’s transit mode to bypass Face ID.

Research Papers:

• "Token Security: Formal Analysis of EMV® Tokenization" (IACR 2020).

3. Legal Research Tools​

To study these attacks ethically:

1. Proxmark3/RFIDler: Analyze NFC signal relay (test range, latency).
2. Flipper Zero: Experiment with NFC emulation (for education only).
3. Tokenization SDKs:
   • Visa Developer: Simulate token requests.
   • Apple’s Core NFC: Test iOS payment interactions.

4. Defensive Best Practices​

• For Users:
  • Use RFID-blocking wallets.
  • Enable "Require Authentication" for mobile payments.
• For Developers:
  • Implement EMV Co’s Relay Resistance Protocol.
  • Monitor for token reuse/geolocation anomalies.

Key Takeaway​

While relay and tokenization attacks are theoretically possible, modern safeguards (dynamic cryptograms, biometrics, HSMs) make them hard to exploit at scale. Research focuses on:

• Improving distance bounding.
• Detecting relay latency anomalies.

For hands-on labs (e.g., building a relay demo with Raspberry Pi), I can guide you through setups. Let me know!