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Kubernetes, also known as K8s, is a very complex open-source platform that requires detailed attention to security. Despite previous efforts to increase its security, Kubernetes remains insecure by default and requires different security tools to protect the cluster.

We examine the automotive data ecosystem and take a closer look at privacy and security concerns arising from how data is generated, consumed, and transmitted by connected vehicles.

In today’s rapidly evolving digital landscape, the risk of personal and professional data being stolen by nefarious actors looms larger than ever. This report lays bare the stark reality of this threat, with a specific focus on the unequal risks associated with data theft and its subsequent misuse.

This report explores the aspects and considerations required to properly perform threat modeling within a Kubernetes environment, a piece of technology that many organizations worldwide rely on and a leading container orchestration platform.

We discuss proof-of-concept rootkits and malware used by cybercriminals in conjunction with Berkeley Packet Filtering (BPF), a piece of technology that allows programs to execute code in the operating systems of popular cloud-computing platforms. We also show how to detect such threats.

In our research, we demonstrate how easy it is to discover insecure deployments of MQTT, how to identify customers of these insecure deployments, what data is being transmitted, and explore how an attacker can potentially misuse the data or abuse the insecurity of MQTT brokers.

In this entry, we continue delving into an investigation of exposed registries and look at the types of files and information that malicious actors can access and compromise from these.

This report spotlights Akira, a novel ransomware family with highly experienced and skilled operators at its helm.

In this entry, we will discuss publicly exposed registries, which are repositories or databases containing information accessible to the public without the need for authentication.