https://cve.radiocsirt.org Contains only the most 10 recent entries. http://www.rssboard.org/rss-specification python-feedgen en Sat, 03 Oct 2026 11:46:15 +0000 https://cve.radiocsirt.org/vuln/cve-2025-15379 <p><strong>Affected:</strong> mlflow/mlflow, Red Hat OpenShift AI (RHOAI)</p> <p>A command injection vulnerability exists in MLflow&#39;s model serving container initialization code, specifically in the `_install_model_dependencies_to_env()` function. When deploying a model with `env_manager=LOCAL`, MLflow reads dependency specifications from the model artifact&#39;s `python_env.yaml` file and directly interpolates them into a shell command without sanitization. This allows an attacker to supply a malicious model artifact and achieve arbitrary command execution on systems that deploy the model. The vulnerability affects versions 3.8.0 and is fixed in version 3.8.2.</p> <p><strong>Affected:</strong> mlflow/mlflow, Red Hat OpenShift AI (RHOAI)</p> <p>A command injection vulnerability exists in MLflow&#39;s model serving container initialization code, specifically in the `_install_model_dependencies_to_env()` function. When deploying a model with `env_manager=LOCAL`, MLflow reads dependency specifications from the model artifact&#39;s `python_env.yaml` file and directly interpolates them into a shell command without sanitization. This allows an attacker to supply a malicious model artifact and achieve arbitrary command execution on systems that deploy the model. The vulnerability affects versions 3.8.0 and is fixed in version 3.8.2.</p> https://cve.radiocsirt.org/vuln/cve-2025-15379 https://cve.radiocsirt.org/vuln/ghsa-r23q-823p-vmf7 <p><strong>Affected:</strong> PyPI: mlflow</p> <p>A command injection vulnerability exists in MLflow&#39;s model serving container initialization code, specifically in the `_install_model_dependencies_to_env()` function. When deploying a model with `env_manager=LOCAL`, MLflow reads dependency specifications from the model artifact&#39;s `python_env.yaml` file and directly interpolates them into a shell command without sanitization. This allows an attacker to supply a malicious model artifact and achieve arbitrary command execution on systems that deploy the model. The vulnerability affects versions 3.8.0 and is fixed in version 3.8.1.</p> <p><strong>Affected:</strong> PyPI: mlflow</p> <p>A command injection vulnerability exists in MLflow&#39;s model serving container initialization code, specifically in the `_install_model_dependencies_to_env()` function. When deploying a model with `env_manager=LOCAL`, MLflow reads dependency specifications from the model artifact&#39;s `python_env.yaml` file and directly interpolates them into a shell command without sanitization. This allows an attacker to supply a malicious model artifact and achieve arbitrary command execution on systems that deploy the model. The vulnerability affects versions 3.8.0 and is fixed in version 3.8.1.</p> https://cve.radiocsirt.org/vuln/ghsa-r23q-823p-vmf7