Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

MITRE ATT&CK and D3FEND for Cloud and Containers

MITRE ATT&CK and MITRE D3FEND are both frameworks developed by the non-profit organization MITRE, but they serve different purposes. If you are new to the MITRE ATT&CK framework and would like to brush up on some of the concepts first, we created a Learn Cloud Native article to help you on your journey. If you want to go further, here’s how Falco’s Cloudtrail rules align with MITRE ATT&CK.

Testing the actual security of the most insecure Docker application

Our previous research on CVE exploitability in the top DockerHub images discovered that 78% of the reported CVEs were actually not exploitable. This time, the JFrog Security Research team used JFrog Xray’s Contextual Analysis feature, automatically analyzing the applicability of reported CVEs, to scan OWASP WebGoat – a deliberately insecure application. The results identified that out of 60 CVEs reported with a Critical CVSS score, only 10 are actually applicable.

SCARLETEEL: Operation leveraging Terraform, Kubernetes, and AWS for data theft

The Sysdig Threat Research Team recently discovered a sophisticated cloud operation in a customer environment, dubbed SCARLETEEL, that resulted in stolen proprietary data. The attacker exploited a containerized workload and then leveraged it to perform privilege escalation into an AWS account in order to steal proprietary software and credentials. They also attempted to pivot using a Terraform state file to other connected AWS accounts to spread their reach throughout the organization.

3 Ways To Address Your Kubernetes Data Protection Challenges

Kubernetes is an open-source container orchestration tool originally developed by Google for managing microservices or containerized applications across a distributed cluster of nodes. It is widely thought that “Kubernetes is key” to cloud-native application strategies. Kubernetes (K8s) runs over several nodes, and the collection of nodes is called a cluster. K8s clusters allow application developers to orchestrate and monitor containers across multiple physical, virtual, or cloud servers.

ChatGPT as your Falco Consultant

Can OpenAI ChatGPT become a contributor for an open source project like Falco? Is this the end of GitHub Copilot? ChatGPT is SO trendy that I overheard my grandma talking about it to her friends the other day. We’re seeing more and more uses of this AI for real world applications. That made us think… Falco, the first runtime security project to join CNCF as an incubation-level project, needs contributors.

Navigating the security challenges of multi-tenancy in a cloud environment

Multi-tenancy can maximize the number of resources that are utilized in a cluster by sharing these resources between different groups, teams, or customers. However, boundaries must be placed to avoid problems associated with resource-sharing. On top of that, in a multi-tenant cluster, the number of security policies might gradually grow to the point where a slight misconfiguration could cause major security problems, performance issues, and service disruptions.

What Is Kubernetes Observability and Why It's Critical for Securing Your Clusters

Kubernetes observability refers to the ability to monitor and diagnose the performance and behavior of a Kubernetes cluster and its applications. This includes monitoring resource usage, tracking the status of pods and deployments, and identifying and troubleshooting errors. Observability tools for Kubernetes typically include metrics, logging, and tracing capabilities.

Secure your Kubernetes clusters with the Kubescape Docker extension

Container adoption in enterprises continues to grow, and Kubernetes has become the de facto standard for deploying and operating containerized applications. At the same time, security is shifting left and should be addressed earlier in the software development lifecycle (SDLC). Security has morphed from being a static gateway at the end of the development process to something that (ideally) is embedded every step of the way. This can potentially increase the effort for engineering and DevOps teams.