BINs, Databases, and Automation: The Digital Arsenal of a Modern Carder (About Tools and Specialized Software)

[Professor]

Introduction: From a Craft to an Industry
Modern carding has long ceased to be the preserve of lone enthusiasts delving into networks. It's a highly organized digital industry with a clear division of labor, its own tools, and even forms of SaaS (Software as a Service). At the core of this industry is a triad: bins (BINs), databases (bases/dumps), and automation (bots and scripts). Understanding this arsenal is key to understanding the scale and complexity of countermeasures.

Chapter 1: BIN — Foundation and Guidance System​

BIN (Bank Identification Number) is the first 6-8 digits of the card number. This is not a random number, but a unique identifier for the issuing bank, card type (Visa/MasterCard/MIR), card level (Classic/Gold/Platinum), and country.

For a carder, the BIN is more than just a number; it's a strategic tool:

1. Targeted selection: Different banks and regions have different security policies. Some banks quickly block suspicious transactions, while others are more sluggish. Knowing the BIN, a carder can specifically target "weak" issuers in specific countries or regions.
2. Card validation: Before purchasing an expensive database of "dumps," a carder can verify their viability using BIN checker services . The script quickly "rings" small amounts (e.g., $0.01) through charities that accept payments without CVV to filter out invalid numbers.
3. Establishing legitimacy: When making a purchase online, the system checks the BIN against the IP address region and delivery address. Knowing the BIN, the carder can select appropriate proxies or VPNs (for example, if the card is from a Canadian bank, the IP must also be Canadian) and adjust the delivery address (a "drop-to-bank" scheme).

Entire online catalogs and BIN databases exist , regularly updated and traded on underground forums. This forms the basis for planning any major operation.

Chapter 2: Bases – The "Crude Oil" of the Shadow Market​

Stolen card data is a commodity. It is structured, classified, and sold as specialized databases.

The main types of databases are:

1. Dumps: Classic data from a card's magnetic stripe (Track1 & Track2). Contains the card number, cardholder name, expiration date, and service code. Used for cloning physical cards and payments at chip-less terminals (primarily abroad). Sold as "Fresh" (just skimmed) or "Verified" (already validated).
2. CVV/Fullz:Data for online payments.
   • CVV: Basic set: number, expiration date, CVV code, sometimes name.
   • Fullz (from "full information"): A complete set. In addition to the CVV, the cardholder's passport information, address, email, phone number, purchase history, and answers to security questions are added. This is the "premium" class, allowing you to pass even the strictest check (AVS — Address Verification System) and call the bank to unblock the payment. These are several times more expensive.
3. Databases of stores/hotels/airlines: Results of targeted hacks. Contain not only card details but also customer logins and passwords, making social engineering easier.
4. Logs: A new and extremely dangerous format. These aren't just card details, but also intercepted browser sessions (cookies, authorization tokens). Using such a "log," a fraudster can log into the victim's online store account (for example, Amazon) and make a purchase without entering any payment information , since the site sees them as the already authorized account holder.

Pricing depends on the card type (the higher the limit, the more expensive), the issuer's country (US/EU cards are more valuable), the freshness of the data, and the percentage of "live" cards in the database. Sales are often blind (without prior verification), but major sellers have a reputation.

Chapter 3: Automation – The Brains and Muscles of Operation​

Manually handling thousands of cards is inefficient. A modern carder is often an operator of automated systems .

Key automation tools:

1. Card Checkers: Specialized software or web services for mass card validation. A database is loaded, the checker sends micropayments to test sites (often charity sites) through a network of anonymous proxies, and determines whether the card is valid based on the payment gateway's response. Modern checkers can bypass complex CAPTCHAs and analyze specific bank error codes.
2. Sniffers and Grabbers:Software for intercepting data.
   • Web Injects: Modifying the payment page in the victim's browser to steal data directly as it is being typed.
   • Mobile Trojans: Disguise themselves as legitimate applications and intercept data from banking apps.
3. Proxy infrastructure and anti-detection browsers:To prevent a store or bank from seeing suspicious activity from a single IP.
   • SOCKS5 proxies, residential proxies (live IP addresses of real devices).
   • Anti-detect browsers (e.g. Dolphin{Anty}, AdsPower): Allow you to create unique browser fingerprints for each profile, emulating the work of a unique user.
4. Bots for online stores:Automate the purchasing process. The bot can:
   • Register accounts using disposable email addresses yourself.
   • Fill the cart with goods.
   • Enter card details from the database.
   • Select a delivery address compatible with the card's BIN.
   • Bypass complex anti-fraud systems by imitating human behavior (random delays, mouse movements).
5. Crypto tools: A mandatory final step. Automatic crypto mixers (tumblers), scripts for exchanging on decentralized exchanges (DEX), wallets that support privacy-oriented coins (Monero - XMR).

Chapter 4: Fraud-as-a-Service (FaaS) – Rent the Entire Arsenal​

The highest stage of industrialization is "Fraud as a Service". You don't need to understand the intricacies. You can rent the following on dark forums:

• Ready-made botnets for DDoS attacks or mailings.
• Card verification services with guaranteed results.
• Anonymous hosting and DNS servers for phishing sites.
• Services for customizing malware for a specific antivirus.
• Ready-made phishing panels (for example, disguised as Chase or PayPal online banking) with automatic collection and systematization of entered data.

This turns carding into a conveyor belt, where each participant is responsible for their own narrow segment, and the technical barrier to entry is reduced to a minimum.

Conclusion: A Race of Intelligence.
The carder's digital arsenal is a mirror image of the security of the financial world. Each new bank security system (3D-Secure, biometrics, behavioral analysis) gives rise to a new tool for bypassing it (session logs, soshing, bots that imitate behavior).

The battle today is no longer just about data protection, but also about algorithms . Banking AIs that search for anomalies versus fraudsters' AIs that train neural networks to imitate normal behavior. Understanding this arsenal is not a guide, but a prerequisite for recognizing the scale of the threat and developing adequate, proactive defenses that must be as dynamic, complex, and automated as the attack tools.