Today, the average application contains thousands of moving parts. Organizations deploy to multi-cloud environments with containers and microservices, using a combination of code written by internal teams, generated by AI, and curated by third parties. Security teams face a tall order in keeping these complex applications secure, especially given the increasing number of software supply chain attacks.

While often considered a newer threat, and rightly so given its fast-rising dominance among the cybercrime landscape, ransomware is not a recent innovation in the ongoing cyber war. It stretches back decades to the early days of the internet, email, and even floppy discs.

As cybersecurity leaders try to get ahead of threats to their organization, they're increasingly seeking ways to get off the hamster wheel of chasing countless CVEs (common vulnerabilities and exposures). The brass ring that most CISOs reach for today is prioritization of exposures in their infrastructure (and beyond), so their teams can focus on tackling the ones that present the greatest risk. In some cases, the highest priority exposures will still be critical CVEs on mission critical assets.

Elastic 8.14 is now available! This release supports our mission to modernize security operations with AI-driven security analytics. 8.14 includes major features like the brand new Attack Discovery, significant enhancements to Elastic AI Assistant for Security, and the general availability of ES|QL — all of which provide the SOC with contextual, streamlined SecOps.

Have you ever wondered how Artificial Intelligence (AI) could mimic consciousness and autonomously control various tasks? It sounds rather daunting. However, it may not be as intimidating as it seems under the right conditions. Moreover, Would AI perform tasks independently in the same manner as humans? And what implications does this hold for cybersecurity? In the present day, we are observing the rise of self-driving cars that operate with minimal human input.

Anyone remotely wired into technology newsfeeds – or any newsfeeds for that matter – will know that AI (artificial intelligence) is the topic of the moment. In the past 18 months alone, we’ve borne witness to the world’s first AI Safety Summit, a bizarre and highly public leadership drama at one of the world’s top AI companies, and countless prophecies of doom. And yet, even after all that, it seems businesses have largely failed to take meaningful action on AI.

For most organizations, the decision to adopt cloud technologies is a simple one. Cloud apps streamline operations and costs while enabling users to access resources from anywhere and on any device. But migrating to the cloud has also introduced some complexity, which comes with new risks. Instead of everything residing neatly within your corporate perimeter, your data now resides within countless apps and is being handled by users and endpoints that operate outside of your sphere of influence.

Distributed networks, including software-defined wide area networks (SD-WAN), content delivery networks (CDNs), and secure access service edge (SASE) architectures have become integral to modern IT landscapes. They provide unparalleled performance, scalability, and flexibility, empowering businesses to operate seamlessly across geographical boundaries.