Anatomy of a Carding Bot: Understanding the Code and Logic of a Typical Telegram Bot for Checks and Drops

[Professor]

Abstract: In the shadows of complex carding schemes, an equally interesting but far more technical world often lurks — the world of automation. Telegram bots have become the digital stewards of this shadow economy, organizing data flows, checking product quality, and managing the logistics of "drops." This article offers a non-judgmental, but rather exploratory, look at the architecture and logic of a typical such bot. We will examine it as a software product, highlighting its key modules, operating principles, and the digital footprint it leaves behind. This will allow us to understand how tools of astonishing effectiveness and convenience are born in an anonymous environment.

Introduction: From Chat Roulette to Data Exchange​

Imagine an interface where, instead of ordering a taxi or a pizza, you purchase bank card details or hire a dropshipper to deliver your goods. Everything happens in a familiar messenger, with buttons, menus, and automatic notifications. Such a bot is the frontend and backend of a shadow market, hidden behind a bot account. Its creation is an act of digital entrepreneurship, where criminal intent is not the primary focus, but rather UX/UI design, API reliability, and 24/7 operational stability.

1. Architecture and Environment: What is the Bot Built on?​

A typical carding bot is a server-side application written in popular languages.

• Language and frameworks: Most often, this is Python with the python-telegram-bot or aiogram libraries (for asynchronous work). Less commonly, it's Node.js with node-telegram-bot-api. This choice is based on its simplicity, the abundance of ready-made solutions for working with the Telegram API, and the ability to quickly prototype.
• Database: For storing users, products, orders, and transactions, we use lightweight SQLite (for simplicity) or the more powerful PostgreSQL. Data is often encrypted at the application level before being written to the database.
• Hosting: The bot resides on a rented VPS server (often in jurisdictions with liberal regulations) or, more interestingly, on a rented cloud service account (AWS, Google Cloud, DigitalOcean), paid for with cryptocurrency using fake credentials. This allows for quick deployment and just as quick "burndown" of the infrastructure.
• Security (paranoid level): The server can be configured to accept commands only from specific IP addresses (Telegram API), all internal communications are encrypted, logs are cleared, and SSH access is key-based. The bot is valuable property, and efforts are made to protect it.

2. Core Module: User and Access Management​

The logic of work begins with input control.

• Registration and verification: A new user can't simply type "/start." An invite link from a private channel or trusted contact is often required. Sometimes, an upfront "entry fee" must be paid to a crypto wallet. After that, the bot may request a username for identification.
• Role-Based Access Control (RBAT):
  • Administrator (Admin): Full access to the database, product management, viewing statistics, blocking users.
  • Moderator/Verifier: Verification of dropped photo evidence, dispute resolution.
  • Seller: The right to display the goods (“check”).
  • Buyer/Carder: The bulk of the trade. They can buy goods and hire droppers.
  • Drop: A separate role. Can only view drop tasks and report on their completion.
• Balance and internal currency: Each user has a "balance" field in the database. These are internal points, often linked to cryptocurrency (1 point = 1 USDT). Balance replenishment occurs by tracking transactions on the blockchain to the specified address. This is a fully automated process.

3. Marketplace Module: Product Catalog and Purchasing Mechanics​

This is the heart of the bot - the digital counter.

• Product structure ("Receipt"):In the database, a product record contains multiple fields:
  • type: "dump", "fulz", "dropshipping" (ready order for goods).
  • country: Country of the issuing bank.
  • bank: Name of the bank.
  • level: «Classic», «Gold», «Platinum».
  • balance: Declared balance/limit.
  • price: Price in local currency.
  • Data: MOST IMPORTANT. The card details (number, expiration date, CVV, name) or login/password. They are stored in encrypted form. The decryption key is issued only after payment.
  • sold: Flag, whether the cargo has been sold.
• Purchase process:
  1. The user selects a category through the menu (/shop), filters by country and bank.
  2. The bot shows a short description and price.
  3. When a purchase is confirmed, the bot checks the user's balance, debits the amount, decrypts the product data in the background, and sends it to the user via an encrypted private message (or a temporary one-time channel). After this, the "sold" flag changes to True.
  4. Automatic catalog update: The bot can have integration with an external data provider (another API), which supplies new "receipts", automatically adding them to the database.

4. Logistics Module: Drop Management​

The most difficult process in terms of organization.

• Job Creation: The seller or admin creates a task through the bot: "Buy an iPhone 15 Pro Max in Germany and ship to an address in Poland." The budget for the item, the drop fee, the deadline, and required proof (order screenshots, tracking number) are specified.
• Automatic matching: Drops with the drop role can view available tasks. Once a task is accepted, it is locked for others to work on.
• Evidence system and escrow: Funds for the task are reserved from the seller's budget. The drop must provide proof of each step (a screenshot of the cart, order confirmation, and tracking). The bot stores these media files. After the final recipient (the drop or reseller) confirms receipt of the item, the bot automatically unlocks and transfers the drop's commission to its internal balance. All of this is managed by a Finite State Machine (FSM) — a finite-state machine where each task status (created, assigned, ordered, shipped, delivered, completed) strictly defines the possible actions.

5. Security and anti-fraud module​

The bot protects not only from external threats, but also from fraud within the system.

• User Rating: Each user has a trust_score, which increases for successful trades and decreases for disputes or scams.
• Message auto-moderation: The bot ensures that users don't exchange contacts or try to take deals offline. Keyword triggers a warning or ban.
• Action logging: All key actions (purchases, logins, balance changes) are recorded in a log file with a timestamp and user ID. This is for incident analysis.
• Anti-DDoS and request limits: To prevent attempts to "overload" the bot, limits are set on the number of requests per second from one ID.

6. Financial Module: Integration with the Crypto World​

• Balance replenishment: The bot generates a unique crypto address (USDT TRC-20) for each user or uses a single address with a unique payment memo/ID. It connects to a blockchain explorer API (e.g., TronScan) and checks for incoming funds in a background cron job once per minute. Upon finding a transaction with the required amount and memo, the bot credits the points to the balance.
• Withdrawal: A seller or drop can request a withdrawal of internal points to an external crypto wallet. The request is moderated (manually or automatically if the trust_score is high), after which the bot initiates a real transaction to the blockchain using its hot crypto wallet.

Conclusion: Efficiency Born of Necessity​

Having analyzed the anatomy of a carding bot, we see not a simple script, but a complex business platform that solves classic e-commerce and logistics problems under extreme conditions:

1. Catalog and inventory management.
2. Payment integration and billing.
3. Supply chain management.
4. Quality control and reputation system.
5. User support (tickets).

The irony is that the tech stack and architectural solutions here often outpace legitimate small businesses in simplicity and automation.

This bot is a digital organism, perfectly adapted to its ecosystem. Its existence demonstrates that the driving force behind shadow markets is not only greed, but also the desire for order, efficiency, and reduced transaction costs in an environment without the rule of law. Understanding its logic is the key not to admiration, but to the realization that combating such phenomena requires equally sophisticated, systemic, and technologically savvy responses. It's a reminder that in the digital age, even the darkest corners of the economy acquire their own, ruthlessly rational, software-based logic.