OS Command Injection

github.com/rancher/rancher is vulnerable to OS Command Injection. The vulnerability is due to unsanitized YAML parameters in the /v3/import/tokenclusterId.yaml import endpoint, which allows a remote attacker to inject commands, break out of a container image, and execute malicious containers...

CVE-2026-44939

A command injection vulnerability in the Rancher Manager cluster before 2.14.2 import endpoint /v3/import/tokenclusterId.yaml through unsanitized YAML parameters could allow remote attackers to break out of an image, and execute e.g. malicious containers...

CVE-2026-44939

A command injection vulnerability in the Rancher Manager cluster before 2.14.2 import endpoint /v3/import/tokenclusterId.yaml through unsanitized YAML parameters could allow remote attackers to break out of an image, and execute e.g. malicious containers...

CVE-2026-44939 Command injection through unsanitized YAML parameter in Rancher

A command injection vulnerability in the Rancher Manager cluster before 2.14.2 import endpoint /v3/import/tokenclusterId.yaml through unsanitized YAML parameters could allow remote attackers to break out of an image, and execute e.g. malicious containers...

CVE-2026-44939 Command injection through unsanitized YAML parameter in Rancher

A command injection vulnerability in the Rancher Manager cluster before 2.14.2 import endpoint /v3/import/tokenclusterId.yaml through unsanitized YAML parameters could allow remote attackers to break out of an image, and execute e.g. malicious containers...

CVE-2026-44939 Command injection through unsanitized YAML parameter in Rancher

A command injection vulnerability in the Rancher Manager cluster before 2.14.2 import endpoint /v3/import/tokenclusterId.yaml through unsanitized YAML parameters could allow remote attackers to break out of an image, and execute e.g. malicious containers...

CVE-2025-15379 Command Injection in mlflow/mlflow

A command injection vulnerability exists in MLflow's model serving container initialization code, specifically in the installmodeldependenciestoenv function. When deploying a model with envmanager=LOCAL, MLflow reads dependency specifications from the model artifact's pythonenv.yaml file and...