Securing a $2B Crypto Exchange Against Automated Threats with GeeTest

The Challenge

With the rapid surge in cryptocurrency values and popularity in 2017, the leading exchange experienced a marked rise in bot activity targeting sensitive entry points like login and signup gateways. Malicious automation powered account takeover attacks, where bots used stolen credentials to seize control of user accounts, alongside efforts to exploit promotional subsidies through mass creation of fake profiles. These sophisticated threats overwhelmed existing defenses, as the platform’s CAPTCHA system failed to identify advanced bots specifically designed to infiltrate the site, leaving high-value assets vulnerable and eroding user confidence.

Further complicating matters, the CAPTCHA’s high-friction responses such as complex puzzles and multi-step verifications generated significant user dissatisfaction, slowing access during peak times and prompting widespread complaints about disrupted trading experiences. Legitimate users faced unnecessary barriers that hindered seamless interactions, while the inability to balance security with convenience amplified frustration across the user base, ultimately impacting engagement and retention on the platform.

The Solution

Strategic Gateway Deployment & Threat Mapping

To address the surge in unauthorized access attempts, GeeTest introduced a dynamic risk evaluation system at core entry points, from account logins to deposit verifications. This engine processes over 50 behavioral and contextual indicators, such as session frequency and device inconsistencies, in real time to assign precise threat levels. Low-risk sessions, like a routine trade from a verified mobile app, proceed undetected, whereas suspicious patterns trigger tailored, low-effort validations. Implemented swiftly through plug-and-play APIs, it reduced erroneous blocks by 70% relative to uniform checks, allowing the vast majority of daily operations to maintain uninterrupted momentum.

Behavioral Analysis for AI-Enhanced Bots

At the heart of GeeTest’s defense is ML-powered behavioral verification with 7-layer analysis, scrutinizing interaction nuances like cursor trajectories and input cadences alongside device fingerprints to unmask AI-disguised automation. Early post-deployment reviews pinpointed 99.2% of gateway traffic as bots, including evasion tactics from frameworks like Selenium, validated against global threat intelligence. Continuous self-learning on site-specific patterns, such as promo-timed infiltrations, enables minute-level risk detection, outpacing attackers and minimizing impacts on authentic users in volatile trading environments.

Frictionless Experience for Legitimate Users

GeeTest’s lightweight verification framework ensured smooth integration with the brand’s global e-commerce platform. Verification was triggered only when necessary, enabling genuine customers to complete challenges with minimal friction. During peak traffic events, this adaptive approach preserved high conversion rates and maintained website stability across web and mobile experiences. The solution also aligned seamlessly with the company’s internal fraud-detection workflows, ensuring rapid response to emerging threats without disrupting purchasing behavior.

The Result