Card Testing

Imagine you are conducting a routine check of the transaction activities on your site, only to find a deluge of tens to hundreds of thousands of authorizations flooding your screen. At first, a surge of satisfaction courses through you—a testament to the success of your strategy, or so you think. Yet, upon closer scrutiny, a disconcerting pattern emerges: a multitude of minuscule transactions, each emanating from a single source. Your initial thrill quickly dissipates into the sobering realization that an orchestrated effort of fraud has taken place on your site. This is what card testing feels like.

As we delve into this multifaceted challenge, the evolution of card testing underscores the urgency for robust security protocols. Safeguarding both enterprises and consumers from the impacts of these subversive activities now stands not only as a prudent practice but also as an essential strategic imperative.

The Adverse Effects of Card Testing

Card testing has a wide-reaching impact on businesses that use card-not-present (CNP) transactions, along with the consumers whose accounts are compromised or whose card information is stolen.

Whether transactions are approved, businesses are saddled with transaction fees, chargebacks, and associated costs from disputed transactions. Moreover, higher decline rates can lead to businesses being seen as high-risk, which means they end up paying more to payment processors and could even be subject to dispute monitoring programs, or–in the worst cases–lose their ability to process payments. And that doesn’t even address the damage card testing can do to their brand, making it tough to keep existing customers and attract new ones. With the notable increase in digital transaction volumes over recent years, the issue of card testing has evolved into a substantial challenge.

Put a Halt to Card Testing with Arkose Labs

Businesses use multiple techniques to protect against card testing, such as transaction monitoring, address verification systems, and IP geolocation. But because virtually all of today’s digital attacks are automated, the most effective way to stop card testing is to implement an effective bot detection and mitigation system.

Bot detection systems employ various methods to thwart card testing, including:

• Behavioral analysis: Bot detection systems analyze user behavior patterns to differentiate between human users and bots. Bots often exhibit distinctive behavior, such as rapid and consistent interactions, which can be flagged and blocked.
• Pattern recognition: These systems can identify repetitive patterns that are indicative of bot behavior, such as making multiple small transactions within a short time frame.
• CAPTCHA and other challenges: Many bot detection systems employ CAPTCHA tests or other challenges that are easy for humans to solve but difficult for automated bots. Some systems incorporate challenges that require user interaction, such as clicking a button or dragging a slider, which bots find challenging to emulate accurately.
• IP reputation: Bot detection systems maintain databases of known malicious IP addresses associated with bot activity. They can block or impose additional scrutiny on transactions originating from these IPs.
• Device fingerprinting: These systems use device fingerprinting techniques to identify the unique characteristics of devices used for transactions. If a device's fingerprint matches that of a known bot, the system can take preventive measures.
• Rate limiting: Bot detection systems can enforce rate limits on the number of transactions or requests from a single IP address within a given time period. This helps prevent bots from overwhelming the system with rapid requests.
• Machine learning and AI: Many bot detection systems utilize machine learning and artificial intelligence to continuously learn and adapt to new bot behaviors. This allows them to detect even previously unseen bot patterns.
• Browser fingerprinting: Bot detection systems analyze browser attributes, such as user agent strings and screen resolutions, to identify unusual or automated behaviors.
• User-agent and real-time analysis: Bot detection systems scrutinize user-agent information provided by web browsers to identify deviations from expected patterns. They analyze transactions in real time, allowing them to detect and block suspicious activity as it happens.

The most effective defense against card testing attacks is a comprehensive bot management solution, such as the Arkose Bot Manager platform by Arkose Labs. This solution incorporates device fingerprinting, IP reputation checks, behavior biometrics, and Arkose MatchKey Challenges—widely recognized as the most potent CAPTCHA type available. Arkose Labs' platform covers all consumer flows and dynamically responds to each attack pattern.

Arkose Bot Manager: Snare Bots, Spare Legitimate Customers

Through a fusion of sophisticated attack detection strategies and tailor-made response mechanisms, Arkose Bot Manager adeptly exposes illicit activities while minimizing potential disruption to authentic users.

Swift, Real-Time Attack Recognition

Stay ahead of evolving threats

In today's landscape, bad actors wield sophisticated tools that mimic genuine user behavior, eluding traditional security measures. Our all-encompassing solution scrutinizes real-time device, network, and behavioral signals across the customer journey to detect subtle telltale signs of both bot-driven and human-driven assaults.

• Multi-layered detection using device, IP, and behavioral biometrics analysis
• Access to a wealth of over 70 risk attributes for refining existing models
• Machine learning decision-making based on numerous global attack patterns
• Round-the-clock analysis by our SOC team to pinpoint and optimize threat responses

A Smooth Customer Experience

Frustrate attackers, not users

Our tailored response mechanism makes sure genuine customers glide through smoothly, while suspicious traffic encounters intricate challenges that effectively halt bots and frustrate human fraud farms.

• Resilient challenges designed to outsmart advanced bots
• Protection against attacks carried out by humans
• Optimized user experience surpassing traditional CAPTCHAs and multi-factor authentication (MFA)
• Continuous SOC monitoring with guaranteed mitigation service level agreement (SLA)