The JFrog Security research team has recently discovered two security vulnerabilities in X.Org libX11, the widely popular graphics library – CVE-2023-43786 and CVE-2023-43787 (with a high NVD severity CVSS 7.8). These vulnerabilities cause a denial-of-service and remote code execution. X11’s latest versions contain fixes for these vulnerabilities.

Today, we’re excited to announce a new integration with Amazon SageMaker! SageMaker helps companies build, train, and deploy machine learning (ML) models for any use case with fully managed infrastructure, tools, and workflows. By leveraging JFrog Artifactory and Amazon SageMaker together, ML models can be delivered alongside all other software development components in a modern DevSecOps workflow, making each model immutable, traceable, secure, and validated as it matures for release.

TL;DR: JFrog’s ML Model Management capabilities, which help bridge the gap between AI/ML model development and DevSecOps, are now Generally Available and come with a new approach to versioning models that benefit Data Scientists and DevOps Engineers alike. Model versioning can be a frustrating process with many considerations when taking models from Data Science to Production.

The security of the software supply chain is rapidly becoming a paramount concern for organizations — and for good reason. With the increasing number of published Common Vulnerabilities and Exposures (CVEs), developers face the challenge of delivering software faster than ever before. However, in their quest for speed, many dev and security teams have resorted to fragmented security solutions, inadvertently leaving critical gaps in coverage and compromising their competitive advantage.