Block automated bot attacks with smart detection

Whether it’s scraper bots stealing content or credential stuffing attackers trying to hack user accounts, dealing with malicious bot traffic can slow site performance and make resources unavailable for real customers. Successful bot attacks can result in financial losses due to refunds, chargebacks, lawsuits, and regulatory fines, as well as damage to brand reputation that can hurt long-term growth and profits.

Block automated bot attacks with smart detection are many different kinds of bots, they all have one thing in common: they can be either good or bad. The difference is their motives and the technologies they use to achieve them. Good bots, for example, are automated software applications that can be used to perform a variety of useful tasks like search engine indexing, site monitoring, and chatbots. Malicious bots, on the other hand, can wreak havoc by creating fake accounts to post fake reviews, manipulate video votes, or even rig election results.

Blacklist Lookup: How to Filter Dangerous IP Addresses Automatically

Sophisticated bots can be difficult to detect, especially when they target peripheral customer touchpoints and operate over a long period of time, “low and slow.” To identify these attacks, security teams need to utilize the latest technology to keep up with changing attack patterns. This includes the ability to recognize sophisticated bots by using proof of work (PoW), which requires a device to solve a computational challenge before performing an action, such as logging in or making a purchase. It’s also necessary to incorporate AI/ML into the mix, which can identify complex patterns that indicate bot activity, such as recurring login failures and password resets or abnormally high volume of new account creations.