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The concept of "passwordless" authentication has been gaining significant industry and media attention. And for a good reason. Our digital lives are demanding an ever-increasing number of online accounts and services, with security best practices dictating that each requires a strong, unique password in order to ensure data stays safe. Who wouldn't want an easier way? That's the premise behind one-time passwords (OTP), biometrics, pin codes, and other authentication methods presented as passwordless security. Rather than remembering cumbersome passwords, users can authenticate themselves using something they own, know, or are. Some examples include a smartphone, OTP, hardware token, or biometric marker like a fingerprint. While this sounds appealing on the surface, the problem is that, when you dig deeper, these passwordless solutions are still reliant on passwords. This happens in two primary ways: Passwordless Solutions Rely on Passwords as a Fallback If you ha...

One of the many features of an Active Directory Password Policy is the  maximum password age . Traditional Active Directory environments have long using password aging as a means to bolster password security. Native password aging in the default Active Directory Password Policy is relatively limited in configuration settings. Let's take a look at a few best practices that have changed in regards to password aging. What controls can you enforce in regards to password aging using the default Active Directory Password Policy? Are there better tools that organizations can use regarding controlling the maximum password age for Active Directory user accounts? What password aging best practices have changed? Password aging for Active Directory user accounts has long been a controversial topic in security best practices. While many organizations still apply more traditional password aging rules, noted security organizations have provided updated password aging guidance. Microsoft has...

As SaaS providers race to integrate AI into their product offerings to stay competitive and relevant, a new challenge has emerged in the world of AI: shadow AI.  Shadow AI refers to the unauthorized use of AI tools and copilots at organizations. For example, a developer using ChatGPT to assist with writing code, a salesperson downloading an AI-powered meeting transcription tool, or a customer support person using Agentic AI to automate tasks – without going through the proper channels. When these tools are used without IT or the Security team's knowledge, they often lack sufficient security controls, putting company data at risk. Shadow AI Detection Challenges Because shadow AI tools often embed themselves in approved business applications via AI assistants, copilots, and agents they are even more tricky to discover than traditional shadow IT. While traditional shadow apps can be identified through network monitoring methodologies that scan for unauthorized connections based on...