What is a Carding Attack and How to Prevent it?

Carding attacks terrorize the e-commerce industry because of the excessive costs it brings to the targeted organizations. Organizations reported an average loss of USD 4.5 million per annum due to fraudulent transactions! Further, its low-risk, high-reward, and easy-to-execute nature makes carding attacks attractive to threat actors and has led to its growing prevalence and persistence today.

Find more about carding attacks in this blog.

What is a Carding Attack?

Carding, also known as credit card stuffing, is a website security threat wherein attackers (carders) acquire stolen credit card numbers and leverage bots to perform multiple, parallel attempts to authorize stolen credit card credentials. Carding attacks are used not just for payment cards but also for gift cards and vouchers.

Carding Forums and Websites

Carding forums and websites are illegitimate websites that attackers leverage to share stolen card credentials, carding methods, results of carding exploits, and so on.

Carding forums and sites remain hidden using TOR routing. The users use hidden identities to avoid detection. Even payments for buying validated card credentials are done using cryptocurrency.

How Does a Carding Attack Work?

Acquiring Stolen Card Data:

Attackers obtain stolen card data through diverse methods, including card phishing, gift card scams, email phishing, and other social engineering tactics. Alternatively, they may purchase stolen card information from the dark web.

The Validation Process:

Given the uncertainty about the quality of the acquired card data, attackers initiate carding attacks to validate its usability. Bots play a crucial role in this process by conducting numerous small transactions across various e-commerce and payment platforms. The objective is to test the validity of card details and determine if the card has been reported stolen or if transactions go through.

Bots for Speed and Anonymity:

Attackers deploy bots to ensure greater speed, agility, and cost-effectiveness in the validation process. These automated tools also facilitate the rapid alteration of IP addresses, preventing detection by traditional credit card fraud prevention techniques.

Low-Profile Transactions:

Transactions during carding attacks are deliberately kept small and inconspicuous to avoid drawing attention. This covert approach aims to fly under the radar of carding fraud detection mechanisms.

Compilation of Valid Card Information:

Upon successful validation, carders compile a separate list of valid card information. This information can be sold on the black market to other cybercriminals for substantial sums or leveraged by the carder for various criminal activities, including purchasing high-value goods, acquiring gift cards, or extracting funds from associated accounts.

Impact of Carding Attacks 

For merchants and e-commerce businesses leveraging websites to validate stolen card data, severe consequences could damage the business forever.

Chargebacks: When card owners detect fraudulent transactions and report them to their bank, they reverse the transactions and refund the money. This results in financial losses for merchants and incurs chargeback penalties. Chargebacks can be particularly damaging, impacting the business’s revenue and profitability.

Processing Fees: Besides chargeback penalties, merchants face additional financial burdens such as carding fraud reversal charges and higher authentication costs as part of their service agreements. These processing fees further contribute to the economic strain on the business, impacting its overall financial health.

Blocked Transactions: If a merchant is flagged as high risk due to ongoing carding attacks, payment processors may decide to block transactions until the issue is resolved. This can lead to a significant loss of legitimate transactions, negatively affecting the revenue stream of the e-commerce business. The impact is financial and operational, disrupting regular business activities.

Reputational Damage: Card phishing and carding attacks can severely damage the trust and credibility of e-commerce brands with customers and payment processors. Customers may lose confidence in the platform’s security, leading to a decline in sales and potential long-term reputational damage that is challenging to repair.

Product Loss: Even if fraudulent activities are detected, recovering the products carders purchase is often challenging. This results in a direct loss of inventory and further contributes to the financial impact of the carding attack. The inability to retrieve products compounds the overall negative consequences for the merchant.

Detecting Carding Fraud: Tell-tale Signs

Watch out for these indicators to identify potential carding activities:

  • Unusually High Shopping Cart Abandonment Rates: A significant increase in shopping cart abandonment rates may signal fraudulent activities.
  • Lower Shopping Cart Size on Average: If the average size of shopping carts is lower than usual, it could indicate potential carding attempts.
  • Disproportionately High Use of Payment Steps: An unusually high number of interactions with payment steps in the shopping cart may suggest fraudulent behavior.
  • Unusually High Failed Payment Authorization Rates: Elevated rates of failed payment authorizations could be a red flag for carding activities.
  • Increased Chargebacks: A sudden rise in chargebacks, indicating disputed transactions, may indicate fraudulent card usage.
  • Multiple Failed Payment Authorization Attempts: Watch for repeated failed attempts from the same user, IP address, session, user agent, or device ID/fingerprint.

Preventing Carding Fraud with Bot Protection Solution

A robust bot mitigation solution is crucial in preventing carding attacks by implementing various proactive measures and adaptive strategies. Here’s how such solutions contribute to the prevention of carding attacks:

Behavioral Analysis

Bot mitigation solutions often employ advanced behavioral analysis, including machine learning algorithms, to scrutinize user behavior on the website. This enables the system to distinguish between legitimate users and automated bots engaged in carding activities. Unusual patterns, such as rapid and repetitive actions, trigger alerts for further investigation.

Reputation Analysis

These solutions leverage global threat intelligence and maintain known bot behavior patterns databases. By comparing user activities against this threat intelligence, the system can identify, and block bots engaged in carding attacks based on their reputational profile.

Device Fingerprinting

Device fingerprinting is a technique that helps to create unique identifiers for devices, cookies, and browsers. By analyzing shared attributes between sessions, the solution can detect patterns associated with carding activities, enhancing the accuracy of bot identification.

Progressive Challenges

When suspicious behavior is detected, bot protection solutions implement progressive challenges, such as CAPTCHA, cookie, or JavaScript challenges. Since bots struggle to complete these challenges, it effectively helps distinguish between human users and automated scripts attempting carding.

Real-time Monitoring

Continuous monitoring in real-time is a key feature of bot mitigation solutions. These solutions can promptly detect anomalies associated with carding attacks and take immediate preventive actions by analyzing user interactions and transactional data.

Rate Limiting and Velocity Checks

Anit bot solutions often incorporate rate limiting and velocity checks to monitor the frequency of transactions. Unusual spikes in transaction rates trigger alerts or temporary blocks, preventing carding attempts from overwhelming the system.

IP Geolocation Checks

Checking the geolocation of IP addresses is another preventive measure. If discrepancies or multiple transactions originate from suspicious locations, the bot mitigation tool can proactively block or investigate these activities.

Combining these features, a comprehensive bot detection and mitigation solution creates a robust defense against carding attacks. The adaptive nature of these solutions ensures that they can evolve and respond effectively to emerging threats in real-time, providing a dynamic and resilient shield for online platforms.