Hardening Kubeflow Security for Enterprise Environments

The presentation discusses security issues in Kubeflow pipelines and proposes solutions to address them.

• Rootless containers can solve the issue of containers running as root, but there is a limitation in building OCI containers rootless
• The controllers in Kubeflow pipelines run as cluster admin, which is a security risk
• Namespace sharing can also be a security risk as collaborators gain access to service accounts
• Solutions proposed include reducing the complexity of controllers and using reduced cluster roles
• The presentation highlights the progress made in Kubeflow security, such as authentication and machine-to-machine authentication

The presenter mentions a company affected by a denial of service attack, which could block the usage of the cluster for most users

Kubeflow is an open source Kubernetes-native Machine Learning Operation (MLOps) platform that enables building, scaling, and managing machine learning (ML) workflows at scale. With community support, the project is becoming the platform of choice for many users and continues to grow by taking the next big step towards joining CNCF landscape as an incubating project. With project growth, many aspects of Kubeflow are in the process of maturing, especially security. In this session, Diana and Julius will cover how Kubeflow architecture measures with Kubernetes security best practices and uncover the shortcomings. In practice, we will look at some of the main Kubeflow security breaches such as getting unauthorized access to other namespaces and the underlying cluster, impersonalizing other users, reading someone else data / artifacts, etc. Security is everyone's responsibility. Walk away with learning how you can join our efforts to achieve a robust and secure MLOps platform of trust.