Unbotify vs. ShieldLabs

The rise of bot fraud within apps poses a serious risk to businesses, as the mobile environment struggles to contend with a surge of automated bots that can wreak havoc on applications. Numerous app categories are at risk of having their entire user interactions hijacked for fraudulent purposes; for example, gaming apps might experience turmoil in their in-game economies, while e-commerce sites could endure significant financial data breaches. The advancement of bots has resulted in the development of highly refined versions that can imitate real user actions with astonishing accuracy, allowing them to circumvent traditional detection methods. With these sophisticated bots at their disposal, fraudsters can disrupt the user experience and reduce retention rates through tactics such as automated gameplay, account takeovers, credit card fraud, spam, and various other malicious activities. To combat this escalating issue, Unbotify has introduced the first patented machine learning solution specifically engineered to differentiate between real users and bots. Our cutting-edge technology utilizes a deep understanding of human behavioral patterns to accurately detect and eradicate advanced bot fraud that might otherwise go unnoticed, all while achieving a remarkably low false-positive rate. By adopting this groundbreaking solution, businesses can safeguard their app integrity while simultaneously fostering greater user trust and engagement, creating a more secure digital environment for everyone involved.

ShieldLabs excels in identifying and preventing fraudulent activities while simultaneously assessing traffic quality through advanced scoring techniques. The company effectively addresses challenges like multi-accounting, account sharing, account takeovers, fake registrations, and advertising fraud. Utilizing a single JavaScript snippet, ShieldLabs captures over 100 unique signals from devices and networks with every visit, enabling thorough cross-verification that uncovers complex masking strategies and achieves an impressive detection accuracy of up to 99%. It can effortlessly recognize returning users, even when they have cleared their cookies, used incognito modes, or connected via different IP addresses, while also tracking linked users across various accounts and devices. Instead of merely applying a binary flag, the system categorizes a range of elements such as VPNs, proxies, Tor, Apple Private Relay, datacenter IPs, anti-detect browsers, browser automation tools, bots, and AI agents as distinct signals. Each visitor, user, device, and IP is assigned a unique risk score, with established patterns addressing prevalent fraud scenarios like multi-accounting, account sharing, account takeovers, and impossible travel incidents, and traffic quality is assessed based on its origin, channel, and campaign. Setting up this solution is a quick process, taking only five minutes and including client and server SDKs, public APIs, and signed webhooks, which makes it an appealing choice for businesses eager to bolster their security quickly. Consequently, organizations can effectively establish strong defenses against fraud while ensuring a smooth and uninterrupted user experience for their customers. Additionally, this comprehensive approach allows businesses to adapt and respond to emerging threats in real time, further enhancing their protective measures.