Case Study: Zoosk achieves robust bot detection and reduced AWS costs with Cequence Security

How Zoosk Detects and Mitigates Malicious Bots

Zoosk, a leading online dating service with 35+ million members, faced widespread automated fraud that threatened user safety and drove up infrastructure costs. Bad actors used fake account creation and credential‑stuffing account takeover (ATO) attacks against Zoosk’s web and mobile APIs, producing an estimated 80–90% synthetic traffic on an average week and creating heavy AWS spend. After client‑side JavaScript and mobile SDK defenses were reverse‑engineered and became operationally burdensome, Zoosk turned to Cequence Security and its Cequence Application Security Platform (ASP).

Cequence Security deployed its ASP to analyze every interaction with machine learning, behavioral and statistical models to track multi‑step attack behaviors and distinguish bots from legitimate users. Cequence ASP enabled Zoosk to detect and mitigate waves of ATO activity (including spikes from the 2018 Facebook token reuse) and tighten policies against fake account creation, resulting in reduced AWS spend, improved user experience and a more future‑proof application security posture. Cequence Security also provided ongoing support that Zoosk cited as delivering a strong customer experience.

Zoosk