Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Artificial intelligence has taken over almost every aspect of our everyday lives. In cybersecurity, generative AI models with natural language processing are commonly being used to predict, detect, and respond to threats. But AI security assistants, although an upgrade from traditional machine learning, only provide very basic queries and summarization, which is insufficient to fully comprehend modern cloud attacks. As part of an ongoing effort to improve the cloud detection and response (CDR) experience,

Summer is here, bringing thoughts of the beach, travel, and relaxation. However, summer isn’t without its chores; gardens need work, and summer houses require maintenance. Sometimes these chores can be enjoyable and even therapeutic, but most importantly, they keep our projects in good condition, allowing us to unwind and enjoy the summer months.

Generative AI (GenAI) is a top priority for organizations looking to increase productivity and solve business problems faster. In cloud security, AI chatbots to aid security practitioners are becoming more common, but to date, most of these solutions offer only basic queries and summarization. Diverse cloud environments and evolving threats require more from an AI security analyst.

Last year, Sysdig outlined our vision for an AI-driven cloud security assistant. Today, we are excited to announce Sysdig Sage for cloud detection and response (CDR), our new release that embodies our vision. Built upon the core principles we introduced, Sysdig Sage offers actionable insights for cloud environments, with a focus on CDR.

As organizations continue to look for consolidated platforms to address their security needs, an important shift has happened. Customers have discovered that traditional tools focusing exclusively on static risks (such as misconfigurations, policy/control failures, and network exposure) are not enough to address today’s dynamic cloud threats.

Enterprises today face significant challenges in managing, governing, and securing corporate data. Data moves and is shared more ubiquitously than we likely recognize. Through the use of large language models (LLMs), shared with third-party vendors, or exposed on the dark web, there are blind spots that hinder the security and IT teams’ visibility into where data resides and how and by whom it’s accessed.

Kubernetes stands at the forefront of the container orchestration revolution by becoming most people’s go-to container orchestration platform. While looking at all the features that Kubernetes brings into the picture, you may notice that the platform does not manage its own users.

In the rapidly evolving landscape of containerized applications, robust data backup solutions are essential. This is particularly true in production Kubernetes environments, where data integrity and availability are paramount. This post explores the critical roles of CSI snapshots & Non-CSI snapshots in Kubernetes, and how CloudCasa by Catalogic enhances data protection and management capabilities across diverse Kubernetes deployments.

Containerized applications deliver exceptional speed and flexibility, but they also bring complex security challenges, particularly in managing and mitigating vulnerabilities within container images. To tackle these issues, we are excited to introduce Layered Analysis — an important enhancement that provides precise and actionable security insights.