Introducing Stringlifier – an Open Source String Detector

With the rise in identity-based attacks due to the very distributed and remote workforce of 2020, how can your organization identify whether or not it’s the actual user who is attempting the authentication, or an attacker?

Security analytics can provide crucial data to help identify potential issues that require investigation. In a large or distributed environment, however, these logs of novel IPs and devices, unusual logins, and access attempts by high-risk users can quickly become too much of a good thing. Swimming through this ocean of data is like looking for treasure on the Great Pacific garbage patch. But what if you had a historical profile of user and device behavior that would allow you to surface unusual activities and create a baseline for action?

This idea isn’t new -- adaptive authentication and user behavioral analytics have become more popular, because understanding the story behind an anomaly can help inform and prioritize your response. Identifying anomalous logins that could indicate account takeover attempts before they’re breached based on unusual activity around the user, cohort, and the organization’s behavioral norms allows you to respond, adjust your policies, and protect users in real-time.

Join Duo’s Ted Kietzman on August 13 at 1:00 p.m. ET for a dive into how collecting security analytics data is an important first step that will shape your ability to effectively handle potential attacks.