{"document":{"aggregate_severity":{"namespace":"https://access.redhat.com/security/updates/classification/","text":"Important"},"category":"csaf_vex","csaf_version":"2.0","distribution":{"text":"Copyright © Red Hat, Inc. All rights reserved.","tlp":{"label":"WHITE","url":"https://www.first.org/tlp/"}},"lang":"en","notes":[{"category":"legal_disclaimer","text":"This content is licensed under the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/). If you distribute this content, or a modified version of it, you must provide attribution to Red Hat Inc. and provide a link to the original.","title":"Terms of Use"}],"publisher":{"category":"vendor","contact_details":"https://access.redhat.com/security/team/contact/","issuing_authority":"Red Hat Product Security is responsible for vulnerability handling across all Red Hat products and services.","name":"Red Hat Product Security","namespace":"https://www.redhat.com"},"references":[{"category":"self","summary":"Canonical URL","url":"https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-4035.json"}],"title":"python-mlflow: MLflow: Sensitive credential exfiltration via environment variable resolution in AI Gateway secrets","tracking":{"current_release_date":"2026-08-13T17:09:37+00:00","generator":{"date":"2026-08-13T17:09:37+00:00","engine":{"name":"Red Hat 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Hat Bugzilla ID","text":"2484318"}],"notes":[{"category":"description","text":"A flaw was found in MLflow. This vulnerability allows an attacker to exfiltrate sensitive server-side environment credentials. It occurs because the AI Gateway secrets can resolve environment variables, which are then sent to an attacker-controlled endpoint. This could lead to unauthorized access to cloud resources and potentially enable cross-boundary code execution.","title":"Vulnerability description"},{"category":"summary","text":"python-mlflow: MLflow: Sensitive credential exfiltration via environment variable resolution in AI Gateway secrets","title":"Vulnerability summary"},{"category":"other","text":"This is a flaw in MLflow Server’s AI Gateway: if a gateway secret’s api_key uses a $ENV_VAR form, the server resolves it from pod environment variables and can send those values to a configured upstream api_base. The primary impact is credential disclosure (CWE-201), not direct remote code execution on the platform.\n\nFor OpenShift AI, most affected Konflux images embed the mlflow package (notebooks, pipelines, training runtimes) but do not run MLflow Server + AI Gateway in their default role. The clearest product exposure is odh-mlflow-rhel9, where the server component is actually shipped and operated. Exploitation requires Gateway configuration reachability and, in typical deployments, authenticated access (PR:L); unauthenticated abuse applies only where MLflow is deployed without basic-auth. Downstream artifact abuse depends on secondary use of leaked credentials, not a standalone RCE primitive in OpenShift AI itself. Hence, the impact is set to Important.","title":"Statement"},{"category":"general","text":"The CVSS score(s) listed for this vulnerability do not reflect the associated product's status, and are included for informational purposes to better understand the severity of this vulnerability.","title":"CVSS score applicability"}],"product_status":{"known_not_affected":["red_hat_openshift_ai_(rhoai):rhoai/odh-mlflow-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-pipeline-runtime-datascience-cpu-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-pipeline-runtime-pytorch-cuda-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-pipeline-runtime-pytorch-llmcompressor-cuda-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-pipeline-runtime-pytorch-rocm-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-pipeline-runtime-tensorflow-cuda-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-pipeline-runtime-tensorflow-rocm-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-th06-cpu-torch210-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-th06-cuda130-torch210-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-th06-rocm64-torch291-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-training-cuda128-torch29-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-workbench-codeserver-datascience-cpu-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-workbench-jupyter-pytorch-cuda-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-workbench-jupyter-pytorch-llmcompressor-cuda-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-workbench-jupyter-pytorch-rocm-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-workbench-jupyter-tensorflow-cuda-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-workbench-jupyter-tensorflow-rocm-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-workbench-jupyter-trustyai-cpu-py312-rhel9"]},"references":[{"category":"self","summary":"Canonical URL","url":"https://access.redhat.com/security/cve/CVE-2026-4035"},{"category":"external","summary":"RHBZ#2484318","url":"https://bugzilla.redhat.com/show_bug.cgi?id=2484318"},{"category":"external","summary":"https://www.cve.org/CVERecord?id=CVE-2026-4035","url":"https://www.cve.org/CVERecord?id=CVE-2026-4035"},{"category":"external","summary":"https://nvd.nist.gov/vuln/detail/CVE-2026-4035","url":"https://nvd.nist.gov/vuln/detail/CVE-2026-4035"},{"category":"external","summary":"https://github.com/mlflow/mlflow/commit/4a3f2f720cb4f058c9e0c5b883e0acc9ab64a7f3","url":"https://github.com/mlflow/mlflow/commit/4a3f2f720cb4f058c9e0c5b883e0acc9ab64a7f3"},{"category":"external","summary":"https://huntr.com/bounties/f8e591a0-0f19-4910-b82e-16c9956f2233","url":"https://huntr.com/bounties/f8e591a0-0f19-4910-b82e-16c9956f2233"}],"release_date":"2026-06-03T07:18:08.512000+00:00","scores":[{"cvss_v3":{"attackComplexity":"LOW","attackVector":"NETWORK","availabilityImpact":"NONE","baseScore":7.7,"baseSeverity":"HIGH","confidentialityImpact":"HIGH","integrityImpact":"NONE","privilegesRequired":"LOW","scope":"CHANGED","userInteraction":"NONE","vectorString":"CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:N/A:N","version":"3.1"},"products":["red_hat_openshift_ai_(rhoai):rhoai/odh-mlflow-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-pipeline-runtime-datascience-cpu-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-pipeline-runtime-pytorch-cuda-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-pipeline-runtime-pytorch-llmcompressor-cuda-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-pipeline-runtime-pytorch-rocm-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-pipeline-runtime-tensorflow-cuda-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-pipeline-runtime-tensorflow-rocm-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-th06-cpu-torch210-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-th06-cuda130-torch210-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-th06-rocm64-torch291-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-training-cuda128-torch29-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-workbench-codeserver-datascience-cpu-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-workbench-jupyter-pytorch-cuda-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-workbench-jupyter-pytorch-llmcompressor-cuda-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-workbench-jupyter-pytorch-rocm-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-workbench-jupyter-tensorflow-cuda-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-workbench-jupyter-tensorflow-rocm-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-workbench-jupyter-trustyai-cpu-py312-rhel9"]}],"threats":[{"category":"impact","details":"Important","product_ids":["red_hat_openshift_ai_(rhoai):rhoai/odh-mlflow-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-pipeline-runtime-datascience-cpu-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-pipeline-runtime-pytorch-cuda-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-pipeline-runtime-pytorch-llmcompressor-cuda-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-pipeline-runtime-pytorch-rocm-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-pipeline-runtime-tensorflow-cuda-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-pipeline-runtime-tensorflow-rocm-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-th06-cpu-torch210-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-th06-cuda130-torch210-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-th06-rocm64-torch291-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-training-cuda128-torch29-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-workbench-codeserver-datascience-cpu-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-workbench-jupyter-pytorch-cuda-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-workbench-jupyter-pytorch-llmcompressor-cuda-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-workbench-jupyter-pytorch-rocm-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-workbench-jupyter-tensorflow-cuda-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-workbench-jupyter-tensorflow-rocm-py312-rhel9","red_hat_openshift_ai_(rhoai):rhoai/odh-workbench-jupyter-trustyai-cpu-py312-rhel9"]}],"title":"python-mlflow: MLflow: Sensitive credential exfiltration via environment variable resolution in AI Gateway secrets"}]}