CVE-2025-11157

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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."}, {"lang": "es", "value": "Hay una vulnerabilidad muy grave de ejecuci\u00f3n remota de c\u00f3digo en feast-dev/feast versi\u00f3n 0.53.0, espec\u00edficamente en el trabajo de materializaci\u00f3n de Kubernetes ubicado en 'feast/sdk/python/feast/infra/compute_engines/kubernetes/main.py'. La vulnerabilidad surge del uso de 'yaml.load(..., Loader=yaml.Loader)' para deserializar '/var/feast/feature_store.yaml' y '/var/feast/materialization_config.yaml'. Este m\u00e9todo permite instanciar objetos Python arbitrarios, lo que permite a un atacante con capacidad de modificar estos archivos YAML, ejecutar comandos del sistema operativo en el pod de trabajo. Esta vulnerabilidad puede ser explotada antes de que la configuraci\u00f3n sea validada, lo que podr\u00eda llevar a la toma de control del cl\u00faster, envenenamiento de datos y sabotaje de la cadena de suministro."}], "id": "CVE-2025-11157", "lastModified": "2026-07-15T02:17:11.167", "metrics": {"cvssMetricV30": [{"cvssData": {"attackComplexity": "LOW", "attackVector": "LOCAL", "availabilityImpact": "HIGH", "baseScore": 7.8, "baseSeverity": "HIGH", "confidentialityImpact": "HIGH", "integrityImpact": "HIGH", "privilegesRequired": "LOW", "scope": "UNCHANGED", "userInteraction": "NONE", "vectorString": "CVSS:3.0/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H", "version": "3.0"}, "exploitabilityScore": 1.8, "impactScore": 5.9, "source": "security@huntr.dev", "type": "Secondary"}], "cvssMetricV31": [{"cvssData": {"attackComplexity": "LOW", "attackVector": "LOCAL", "availabilityImpact": "HIGH", "baseScore": 7.8, "baseSeverity": "HIGH", "confidentialityImpact": "HIGH", "integrityImpact": "HIGH", "privilegesRequired": "LOW", "scope": "UNCHANGED", "userInteraction": "NONE", "vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H", "version": "3.1"}, "exploitabilityScore": 1.8, "impactScore": 5.9, "source": "0b0ca135-0b70-47e7-9f44-1890c2a1c46c", "type": "Secondary"}], "ssvcV203": [{"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0", "ssvcData": {"id": "CVE-2025-11157", "options": [{"exploitation": "poc"}, {"automatable": "no"}, {"technicalImpact": "total"}], "role": "CISA Coordinator", "timestamp": "2026-01-05T19:58:18.282855Z", "version": "2.0.3"}}]}, "published": "2026-01-01T07:16:00.487", "references": [{"source": "security@huntr.dev", "url": "https://github.com/feast-dev/feast/commit/b2e37ff37953b68ae833f6874ab5bc510a4ca5fb"}, {"source": "security@huntr.dev", "url": "https://huntr.com/bounties/46d4d585-b968-4a76-80ce-872bc5525564"}, {"source": "0b0ca135-0b70-47e7-9f44-1890c2a1c46c", "url": "https://access.redhat.com/errata/RHSA-2026:10184"}, {"source": "0b0ca135-0b70-47e7-9f44-1890c2a1c46c", "url": "https://access.redhat.com/security/cve/CVE-2025-11157"}, {"source": "0b0ca135-0b70-47e7-9f44-1890c2a1c46c", "url": "https://bugzilla.redhat.com/show_bug.cgi?id=2426574"}, {"source": "0b0ca135-0b70-47e7-9f44-1890c2a1c46c", "url": "https://security.access.redhat.com/data/csaf/v2/vex/2025/cve-2025-11157.json"}], "sourceIdentifier": "security@huntr.dev", "vulnStatus": "Deferred", "weaknesses": [{"description": [{"lang": "en", "value": "CWE-502"}], "source": "security@huntr.dev", "type": "Secondary"}, {"description": [{"lang": "en", "value": "CWE-502"}], "source": "0b0ca135-0b70-47e7-9f44-1890c2a1c46c", "type": "Secondary"}]}

{"bugzilla": {"description": "feast: Feast: Remote Code Execution via insecure YAML deserialization", "id": "2426574", "url": "https://bugzilla.redhat.com/show_bug.cgi?id=2426574"}, "csaw": false, "cvss3": {"cvss3_base_score": "7.8", "cvss3_scoring_vector": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H", "status": "draft"}, "cwe": "CWE-502", "details": ["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."], "mitigation": {"lang": "en:us", "value": "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."}, "name": "CVE-2025-11157", "package_state": [{"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Affected", "package_name": "rhoai/odh-feature-server-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Affected", "package_name": "rhoai/odh-pipeline-runtime-datascience-cpu-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Affected", "package_name": "rhoai/odh-pipeline-runtime-pytorch-cuda-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Affected", "package_name": "rhoai/odh-pipeline-runtime-pytorch-llmcompressor-cuda-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Affected", "package_name": "rhoai/odh-pipeline-runtime-pytorch-rocm-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Affected", "package_name": "rhoai/odh-pipeline-runtime-tensorflow-cuda-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Affected", "package_name": "rhoai/odh-pipeline-runtime-tensorflow-rocm-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Affected", "package_name": "rhoai/odh-workbench-codeserver-datascience-cpu-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Affected", "package_name": "rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Affected", "package_name": "rhoai/odh-workbench-jupyter-pytorch-cuda-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Affected", "package_name": "rhoai/odh-workbench-jupyter-pytorch-llmcompressor-cuda-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Affected", "package_name": "rhoai/odh-workbench-jupyter-pytorch-rocm-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Affected", "package_name": "rhoai/odh-workbench-jupyter-tensorflow-cuda-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Affected", "package_name": "rhoai/odh-workbench-jupyter-tensorflow-rocm-py312-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}], "public_date": "2026-01-01T07:03:57Z", "references": ["https://www.cve.org/CVERecord?id=CVE-2025-11157\nhttps://nvd.nist.gov/vuln/detail/CVE-2025-11157\nhttps://github.com/feast-dev/feast/commit/b2e37ff37953b68ae833f6874ab5bc510a4ca5fb\nhttps://huntr.com/bounties/46d4d585-b968-4a76-80ce-872bc5525564"], "statement": "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.", "threat_severity": "Important"}

{}