Introduction to Cloud Services for Carders
Carders are cybercriminals who specialize in stealing, verifying, and monetizing bank card data. Cloud services such as Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP), as well as less regulated platforms like DigitalOcean and even free storage options (e.g., Dropbox, Mega), have become an integral part of their arsenal. These services offer scalability, low cost, global access, and automation tools, allowing carders to effectively manage large volumes of data without the need for their own hardware. According to cybercrime reports such as those from Trend Micro, cloud platforms are used to store and process stolen data, including "log clouds" — services where access to stolen accounts and data is stored and sold. This allows for resource optimization, process automation, and reduced risk of detection.For educational purposes, it is important to understand that such practices are illegal and punishable by law. Below, I'll discuss the mechanisms for using cloud services at a high level, drawing on general cybersecurity knowledge and open-source examples. I won't provide step-by-step instructions or code to avoid abuse, but will instead focus on explaining the principles, risks, and countermeasures.
1. Storing stolen data in the cloud
Cloud storage allows carders to store massive databases (dumps) of card numbers, CVV/CVC codes, expiration dates, cardholder names, and additional information (e.g., addresses, PINs). This data is often obtained through phishing, skimming (installing devices on ATMs), database hacks, or darknet purchases.- Scalable storage: Carders use object storage services like AWS S3, Azure Blob Storage, or GCP Cloud Storage to upload data files. These services allow for inexpensive and automatic scaling of terabytes of information. Data can be encrypted using built-in cloud tools (such as server-side encryption) to protect against competitors or accidental leaks. In some cases, carders create "log clouds" — platforms where access to stolen data is stored and monetized, using cloud databases for indexing and searching.
- Anonymity and access: Accounts are registered using fake data, stolen identities, or through intermediaries (money mules). VPNs, Tor, or proxies are used to mask IP addresses. Data is downloaded through APIs or web interfaces, and access is provided through temporary links or shared folders. For example, on the darknet, carders share links to Mega or Yandex Disk to exchange dumps.
- Use cases: In NFC carding (data theft via contactless payments), carders store stolen track 2 data (magnetic stripe) in mobile apps or cloud services linked to mobile wallets like Apple Pay or Google Pay. The data is transmitted in real time over the internet (which requires cloud servers for relaying) and then stored on device farms for further monetization.
Risks: If data is not properly encrypted, it can be detected by cloud providers through monitoring (e.g., AWS GuardDuty) or leaked into the public domain, as in the case of unprotected S3 buckets.
2. Data processing and analysis in the cloud
Processing includes card validation (carding), automated testing on payment gateways, and preparation for monetization. Cloud services provide the computing power for this.- Computing resources: Carders rent virtual machines (VMs) such as AWS EC2, Azure Virtual Machines, or GCP Compute Engine to run scripts and bots. These scripts check card validity by simulating purchases on websites with low security (such as donations or small services). Cloud computing allows for load balancing to avoid IP blocks, for example, through auto-scaling groups.
- Automation and Bots: Serverless computing (AWS Lambda, Azure Functions) is used for automated tasks such as brute-force (CVV guessing) or cracking (combination verification). Bots written in Python or Node.js process thousands of cards per hour. In advanced schemes, like "Ghost Tap," data is processed in real time: NFC data is relayed through internet servers (cloud) between devices, allowing mules (folks) to make payments without storing the data on their devices. Tools like NFCGate or Z-NFC emulate cards, storing the data in encrypted payloads on cloud servers or mobile devices.
- Integration with mobile services: In modern methods, carders link stolen data to mobile wallets (Apple Pay, Google Wallet). The data is phished through fake websites, transferred to the carders' smartphones, and stored in the ecosystem's cloud (for example, iCloud or Google Drive for backup). It is then used for NFC payments or for selling loaded smartphones on the darknet.
- Big Data Processing: Cloud services with AI/ML (e.g. GCP BigQuery) can be used to analyze dumps – sorting by country, card type (Visa, Mastercard) or balance to maximize profits.
Risks: High activity may raise suspicions among providers, leading to account blocking. Furthermore, payment systems (Visa, Mastercard) have anti-fraud mechanisms that monitor patterns.
3. Anonymity and concealment of activity
- Fake identities: Cloud accounts are paid for with stolen cards or cryptocurrency. Carders use "drop accounts"—accounts registered to mules.
- Decentralization: Data is distributed across multiple providers to avoid complete loss during blocking. Edge computing (e.g., AWS CloudFront) is used for fast access.
- Relays and proxies: In schemes like NFC relays, data is transmitted through cloud servers for real-time exchange between devices in different countries, minimizing risks for the performers.
4. Monetization and data sharing
- Darknet trading: Data is uploaded to the cloud and sold via links. Platforms like Telegram and darknet forums use cloud storage for temporary storage.
- Fake stores: Carders host fake e-commerce sites on cloud servers to test cards or collect new data.
Countermeasures and educational implications
Companies like AWS and Google are implementing monitoring (for example, AI to identify suspicious traffic), cooperating with law enforcement, and requiring account verification. Banks are using tokenization (replacing real data with tokens) and multi-factor authentication. For businesses, it's important to comply with PCI DSS, the security standard for card storage.For educational purposes: Understanding these methods helps in developing security systems. For example, studying "Ghost Tap" demonstrates the importance of geolocation verification in payments. I recommend cybersecurity resources like Kaspersky or Trend Micro for in-depth, risk-free research.
If you need clarification on specific aspects (for example, NFC methods), just ask!