vex8s is an open source tool that analyzes Kubernetes workloads and generates VEX documents based on their SecurityContext.
The idea is to distinguish vulnerabilities that are actually exploitable in a given deployment from those mitigated by Kubernetes security settings (for example, readOnlyRootFilesystem, dropped capabilities, non-root users, and read-only volume mounts).
vex8s embeds a ML model trained on CVE data to predict vulnerability classes, then combines those predictions with the workload's security configuration to determine whether a vulnerability can be mitigated.
I'm particularly interested in feedback on the decision logic and on whether this approach could be useful as part of a vulnerability scanning pipeline.
vex8s is an open source tool that analyzes Kubernetes workloads and generates VEX documents based on their SecurityContext.
The idea is to distinguish vulnerabilities that are actually exploitable in a given deployment from those mitigated by Kubernetes security settings (for example, readOnlyRootFilesystem, dropped capabilities, non-root users, and read-only volume mounts).
vex8s embeds a ML model trained on CVE data to predict vulnerability classes, then combines those predictions with the workload's security configuration to determine whether a vulnerability can be mitigated.
I'm particularly interested in feedback on the decision logic and on whether this approach could be useful as part of a vulnerability scanning pipeline.
GitHub: https://github.com/alegrey91/vex8s