The power of artificial intelligence (AI) and machine learning (ML) is a double-edged sword — empowering cybercriminals and cybersecurity professionals alike. AI, particularly generative AI’s ability to automate tasks, extract information from vast amounts of data, and generate communications and media indistinguishable from the real thing, can all be used to enhance cyberattacks and campaigns.

It seems as though responders cannot catch a break when it comes to 0-day vulnerabilities and supply chain compromise avenues. On March 29th, 2024, the Cybersecurity & Infrastructure Security Agency published an alert regarding a supply chain compromise of the XZ Utils package. At time of writing, there is no information regarding exploitation of the vulnerability and follow-on post-compromise activity.

In today’s cloud-native world, systems are usually accessed by users from multiple devices and in various geographic locations. Anyone who has tried to operationalize an impossible travel type alert for cloud resources will understand the myriad nuances and gotchas involved in such an endeavor. A user may be accessing a cloud resource from a mobile device that is tied to a carrier network well away from their normal geographic location.

Imagine needing to stop a playoff game because viewers were actively impacting the sport, helping players catch impossible passes or score points they never should have gotten. That’s the equivalent of what happened when an Apex Legends hack during the North American finals interrupted the tournament and raised cybersecurity concerns for everyone involved. With global esports a billion-dollar industry, and competitive video gaming in general worth much more than that, this has a serious impact.

We’ve been talking about digital transformation for years (or even decades?), but the pace of evolution is now being catapulted forward by AI. This rapid change and innovation creates and relies upon exponential data sets. And while technology is rapidly evolving to manage and maintain these massive data sets, legacy pricing models based on data ingest volume are lagging behind, making it economically unsustainable.

We recently spoke to a focus group of security professionals, software engineers and developers for a discussion on DevSecOps. We’ve quoted a few of them throughout this article.

Data protection principles are the same whether your data sits in a traditional on-premises data center or a cloud environment. However, the way you apply those principles is quite different when it comes to cloud security vs. traditional security. Moving data to the cloud – whether it's a public cloud like AWS, a private cloud or hybrid cloud — introduces new attack surfaces, threats and challenges, so you need to approach security in a new way.