Scammers use psychology to create some of the most convincing internet cons – here's how to advise your customers on what to watch out for.

The risk both to and from AI models is a topic so hot it’s left the confines of security conferences and now dominates the headlines of major news sites. Indeed, the deluge of frightening hypotheticals can make AI feel like we are navigating an entirely new frontier with no compass. And to be sure, AI poses a lot of unique challenges to security, but remember: Both the media and AI companies have a vested interest in upping the fright hype to keep people talking.

In celebration of its 10th anniversary, the National Institute of Standards and Technology (NIST) has finally updated its cybersecurity framework, now known as the NIST Cybersecurity Framework 2.0. This isn’t a minor facelift. It's a substantial revamp further improving what's already regarded as the gold standard of cyber risk management frameworks. To learn about the key changes in NIST CSF 2.0, and how they could impact your cybersecurity posture improvement efforts, read on.

In the rapidly evolving AI landscape, the principle of least privilege is a crucial security and compliance consideration. Least privilege dictates that any entity—user or system—should have only the minimum level of access permissions necessary to perform its intended functions. This principle is especially vital when it comes to AI models, as it applies to both the training and inference phases.

In recent years, there's only been a handful of data breaches within public companies that could be considered financially "material." These breaches include those often pointed to as examples in cybersecurity presentations: the 2013 Target breach, the 2017 Equifax breach, the 2019 Capital One breach, and most recently, the Colonial Pipeline incident.

Granting privileged access to an end user’s device is a common practice in organizations. Admins do it to give end users the ability to manage administrative tasks such as downloading applications and accessing resources on their devices. It can be done manually, which is cumbersome and introduces risks. Or it can be managed to improve user productivity without requiring additional IT help or intervention, so that IT can focus on higher priority tasks.

Threat hunting is a massive commitment of time, resources, team members, and technology. Any investment that impactful would normally be one that was carefully measured to ensure it was driving sufficient value for the team. The thing is, there’s no established benchmark of “success” in threat hunting.

Major shifts in application development are creating new and significant security risks. Continuous integration/continuous delivery (CI/CD) pipelines and technology advances like automation and AI mean the development process is now so complicated and fast-moving that corporations, DevOps directors, and security groups struggle to understand and manage it, let alone defend it from assaults.

The best way to securely manage database access for remote users is by using a Privileged Access Management (PAM) solution. PAM solutions provide full visibility and control over database access to prevent privilege misuse, reducing the likelihood of an insider threat harming your organization.

Note: This post is co-authored by JFrog and Sean Wright and has also been published on Sean Wright’s blog. DevOps engineers and Security professionals are passionate about their responsibilities, with the first mostly dedicated to ensuring the fast release and the latter responsible for the security of their company’s software applications.