What Is SaaS Card Tester Blocking?

SaaS card tester blocking represents a number of measures that SaaS companies take to prevent card testing fraud.  

SaaS card tester blocking includes blocking repeated payment attempts from the same payment card, IP address, or device within a short timeframe.  

Other measures are:  

• CAPTCHAs 
• rate limiting 
• monitoring rules to stop automated scripts.  

It is important to note that basic firewalls are no longer sufficient to protect SaaS businesses against card testing.  For this reason, SaaS companies need to consider integrating processes such as transaction velocity controls, identity verification, and high-risk payment monitoring. 

Credit card testing fraud is a process where stolen payment information may be used to make small purchases in order to verify the credit card details.  

Upon verification, the credit card details can be utilized for high-value transactions or offered for sale on illicit marketplaces.  Credit card testing is automated, which is why it can be difficult to identify and prevent in the absence of structured monitoring.  Pro Tip:  

SaaS businesses can focus on specific patterns, including low-value transactions or bot-driven behaviour.  Integrating with fraud prevention solutions that can identify these patterns should be considered. 

In SaaS, fraud prevention includes technology, data analysis, and pre-defined rules to detect and stop fraudulent activities such as: 

• fake signups 
• payment abuse 
• card testing.  

The use of real-time transaction monitoring by SaaS companies can affect responses to suspicious activities and revenue protection efforts.  Tools such as risk scoring, alerts, and chargeback prevention can assist in the identification of payments that may be high-risk. 

In a card testing attack, SaaS companies notice:  

• strange payment patterns  
• fast sequences of declined payments  
• multiple authorization attempts within a short timeframe 
• small-value transactions, often under $1, from the same IP 
• geographic mismatches between billing addresses and IP locations 

Consider the following steps: 

1. Understand your audience and the potential risks to their security.  
2. Integrate various tools for fraud detection, which look at the behavior of a card during the transaction and identify any unusual activities, such as high volume or too many attempts to charge the card.  
3. Add CAPTCHA, rate limits, and firewalls in the areas of the website where the card is used, or the payment process.  These methods tend to be sufficient in discouraging bots and preventing manual attacks.

When looking for a card testing solution, consider one that is flexible enough to adjust to changing fraud methods and uses machine learning for rapid analysis.  

This type of solution should have flexible workflows and be easily integrated with your existing systems, providing a complete overview of the transaction data.  Functions such as risk scoring, automation, review queues, and alerts are necessary.  

When looking for a card testing solution, consider one that is flexible enough to adjust to changing fraud methods and uses machine learning for rapid analysis.  

This type of solution should have flexible workflows and be easily integrated with your existing systems, providing a complete overview of the transaction data.  Functions such as risk scoring, automation, review queues, and alerts are necessary.  

In the last few years, payment gateways have become effective at recognizing and stopping card testing through a combination of methods that include velocity verifications, IP and device monitoring, machine learning algorithms, and CAPTCHAs.  

Through this strategy, payment gateways can protect SaaS businesses from repeated testing attempts.  

Card testing cannot be linked to specific countries and IP addresses.  Generally, fraudsters employ VPNs and proxies to keep their location secret.  SaaS businesses should not rely on geolocation signals, but rather on behavioural indicators, like:  

• transaction speed 
• multiple payment declines  
• transaction value 
• inconsistency between billing addresses and IP

SaaS companies find it difficult to identify card testing attempts, especially during peak sales.  In those periods, the high number of valid SaaS transactions can hide fraudulent patterns.  

Another issue with high transaction volumes is faced by SaaS companies that typically have low-value transactions.  This makes it even harder to quickly spot patterns.  

SaaS companies can address card testing through analytics, rule adjustments, and updated fraud detection procedures.