
Enhanced User Activity Monitoring
When risk, product, and customer teams work together to prevent unwanted users from using their service, they usually lack the
When risk, product, and customer teams work together to prevent unwanted users from using their service, they usually lack the
Feeling like doing some quick online shopping through an attractive ad or signing up for a lucrative deal with a
Background Online businesses connect with their customers over the internet through a device, like a laptop or phone, using a
Today, Castle is releasing the Event Explorer, giving security and fraud teams a new way to discover and investigate malicious activity.
With multi-accounting detection, you are better able to protect against account takeovers involving a single device. Also, you can now catch users who are abusing marketing incentives, such as coupons, new-account rewards or new customer referral bonuses.
We're excited to introduce Risk Signals! While Risk signals have always been a part of Castle's risk assessment engine, these signals are now available for your direct use with this release. This allows you to enrich your own data sets with a wealth of new information.
We are excited to announce the addition of the React Native SDK to our SDK stack. The React Native SDK lets you integrate Castle with your Android and iOS applications with a few lines of code.
Learn about two layers in user and account defense, and how deploying Castle gives you a single solution that improves security and reduces user friction.
Does reducing friction help a business grow? Can security teams take friction away from users and make authentication seamless? “High-grade security” coupled with “low to no friction” is the future of successful online engagement between companies and their users. This post explores those topics.
This post covers strategies for adding Castle's layer of bot detection and ATO prevention to your OIDC authentication flow, getting the best of both worlds. This is relevant for apps using an external identity provider, like Okta, Auth0, Amazon Cognito, Google, or Facebook.
Whether it's human intuition or machine learning, how do we go about discovering key insights when flooded with data? This post introduces some fundamental techniques of AI & machine learning to non-data scientists.
In this post, we'll take a look at three types of bot-generated mouse interactions and we'll discuss how these can be automatically detected. See if you can pick out the bot mouse movements from the human ones!