Описание
A high-severity remote code execution vulnerability exists in feast-dev/feast version 0.53.0, specifically in the Kubernetes materializer job located at feast/sdk/python/feast/infra/compute_engines/kubernetes/main.py. The vulnerability arises from the use of yaml.load(..., Loader=yaml.Loader) to deserialize /var/feast/feature_store.yaml and /var/feast/materialization_config.yaml. This method allows for the instantiation of arbitrary Python objects, enabling an attacker with the ability to modify these YAML files to execute OS commands on the worker pod. This vulnerability can be exploited before the configuration is validated, potentially leading to cluster takeover, data poisoning, and supply-chain sabotage.
A flaw was found in Feast, specifically in the Kubernetes materializer job. An attacker with the ability to modify specific YAML configuration files can exploit an insecure deserialization vulnerability. This allows for the instantiation of arbitrary Python objects, leading to remote code execution on the worker pod. Successful exploitation could result in cluster takeover, data poisoning, and supply-chain sabotage.
Отчет
This vulnerability is rated Important for Red Hat OpenShift AI because an attacker with low privileges and local access to the worker pod can modify specific YAML configuration files. This insecure deserialization allows for remote code execution, potentially leading to cluster takeover, data poisoning, and supply-chain sabotage. This affects Red Hat OpenShift AI versions 2.22, 2.25, and 3.0.
Меры по смягчению последствий
Implement strict access controls and least privilege principles for the Feast Kubernetes materializer job. Ensure that only authorized users and processes have write access to the /var/feast/feature_store.yaml and /var/feast/materialization_config.yaml files on the worker pods. This can be achieved through Kubernetes Role-Based Access Control (RBAC) policies and appropriate OpenShift security context constraints to limit file system access.
Затронутые пакеты
| Платформа | Пакет | Состояние | Рекомендация | Релиз |
|---|---|---|---|---|
| Red Hat OpenShift AI (RHOAI) | rhoai/odh-pipeline-runtime-datascience-cpu-py312-rhel9 | Affected | ||
| Red Hat OpenShift AI (RHOAI) | rhoai/odh-pipeline-runtime-pytorch-cuda-py312-rhel9 | Affected | ||
| Red Hat OpenShift AI (RHOAI) | rhoai/odh-pipeline-runtime-pytorch-llmcompressor-cuda-py312-rhel9 | Affected | ||
| Red Hat OpenShift AI (RHOAI) | rhoai/odh-pipeline-runtime-pytorch-rocm-py312-rhel9 | Affected | ||
| Red Hat OpenShift AI (RHOAI) | rhoai/odh-pipeline-runtime-tensorflow-cuda-py312-rhel9 | Affected | ||
| Red Hat OpenShift AI (RHOAI) | rhoai/odh-pipeline-runtime-tensorflow-rocm-py312-rhel9 | Affected | ||
| Red Hat OpenShift AI (RHOAI) | rhoai/odh-workbench-codeserver-datascience-cpu-py312-rhel9 | Affected | ||
| Red Hat OpenShift AI (RHOAI) | rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9 | Affected | ||
| Red Hat OpenShift AI (RHOAI) | rhoai/odh-workbench-jupyter-pytorch-cuda-py312-rhel9 | Affected | ||
| Red Hat OpenShift AI (RHOAI) | rhoai/odh-workbench-jupyter-pytorch-llmcompressor-cuda-py312-rhel9 | Affected |
Показывать по
Дополнительная информация
Статус:
7.8 High
CVSS3
Связанные уязвимости
A high-severity remote code execution vulnerability exists in feast-dev/feast version 0.53.0, specifically in the Kubernetes materializer job located at `feast/sdk/python/feast/infra/compute_engines/kubernetes/main.py`. The vulnerability arises from the use of `yaml.load(..., Loader=yaml.Loader)` to deserialize `/var/feast/feature_store.yaml` and `/var/feast/materialization_config.yaml`. This method allows for the instantiation of arbitrary Python objects, enabling an attacker with the ability to modify these YAML files to execute OS commands on the worker pod. This vulnerability can be exploited before the configuration is validated, potentially leading to cluster takeover, data poisoning, and supply-chain sabotage.
Feast vulnerable to Deserialization of Untrusted Data
7.8 High
CVSS3