Abnormal Blog

If an advanced attack finds its way into an employee’s inbox, you hope that they remember their security and awareness training and do not engage with it. However, there is always the risk that they engage with the message—clicking a...

To detect account takeovers, Abnormal Security’s machine learning algorithms utilize many factors related to location, devices, and applications. However, until now, much of that information was not exposed to users. In an effort to be as customer-centric as possible...

At Abnormal Security, we’re constantly exploring opportunities to improve our customer’s user experience. In this blog post, we’d like to share Abnormal’s process to design a framework to identify gaps and improve customer’s first-time user experience to onboard our platform.

Abnormal Security prides itself on its differentiated technology and superior efficacy when it comes to stopping advanced email attacks. Despite the overwhelming effectiveness of our platform, like all advanced AI systems...

The primary value that Abnormal brings to email security is an advanced, ML-based detection system that can extract and analyze thousands of signals, identify patterns, and adapt over time to detect important attacks–without relying exclusively on threat intel or...

For SOC analysts, managing an employee-reported phishing mailbox can be a double-edged sword. On one hand, legacy tools have made it easy for employees to report would-be business email compromise (BEC) and credential phishing emails. On the other hand...