CVE-2026-4035

A vulnerability in mlflow/mlflow versions prior to 3.11.0 allows for the resolution of environment variables in AI Gateway secrets, which can be exploited to exfiltrate sensitive server-side environment credentials to an attacker-controlled endpoint. This issue arises because the `api_key` field in gateway secrets can accept `$ENV_VAR` references, which are resolved against the MLflow server's environment during runtime. The resolved secrets are then sent in provider authentication headers to the configured upstream `api_base`. This vulnerability can be exploited by low-privileged authenticated users in basic-auth deployments or by unauthenticated users in default deployments without `basic-auth`. The impact includes potential leakage of sensitive credentials such as cloud artifact credentials (`AWS_ACCESS_KEY_ID`, `AWS_SECRET_ACCESS_KEY`), which could lead to artifact poisoning and cross-boundary code execution in downstream environments. The issue is fixed in version 3.11.0.

CVSS v3 7.7 HIGH

7.7^/10

CVSS v3 : HIGH

Vector :

Exploitability : 3.1 / Impact : 4.0

Attack Vector NETWORK

Attack Complexity LOW

Privileges Required LOW

User Interaction NONE

Confidentiality Impact HIGH

Integrity Impact NONE

Availability Impact NONE

Scope CHANGED

References

Link	Resource
https://github.com/mlflow/mlflow/commit/4a3f2f720cb4f058c9e0c5b883e0acc9ab64a7f3	Patch
https://huntr.com/bounties/f8e591a0-0f19-4910-b82e-16c9956f2233	Exploit Third Party Advisory
https://access.redhat.com/security/cve/CVE-2026-4035
https://bugzilla.redhat.com/show_bug.cgi?id=2484318
https://huntr.com/bounties/f8e591a0-0f19-4910-b82e-16c9956f2233	Exploit Third Party Advisory
https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-4035.json

Configurations

Configuration 1 (hide)

cpe:2.3:a:lfprojects:mlflow:*:*:*:*:*:*:*:*

History

No history.

Information

Published : 2026-06-03 09:16

Updated : 2026-08-14 13:19

NVD link : CVE-2026-4035

Mitre link : CVE-2026-4035

CVE.ORG link : CVE-2026-4035

JSON object : View

Products Affected

lfprojects

mlflow

CWE

CWE-201

Insertion of Sensitive Information Into Sent Data

{"id": "CVE-2026-4035", "cveTags": [], "metrics": {"ssvcV203": [{"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0", "ssvcData": {"id": "CVE-2026-4035", "role": "CISA Coordinator", "options": [{"exploitation": "poc"}, {"automatable": "no"}, {"technicalImpact": "partial"}], "version": "2.0.3", "timestamp": "2026-06-03T13:10:20.303201Z"}}], "cvssMetricV30": [{"type": "Secondary", "source": "security@huntr.dev", "cvssData": {"scope": "CHANGED", "version": "3.0", "baseScore": 9.1, "attackVector": "NETWORK", "baseSeverity": "CRITICAL", "vectorString": "CVSS:3.0/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:L/A:L", "integrityImpact": "LOW", "userInteraction": "NONE", "attackComplexity": "LOW", "availabilityImpact": "LOW", "privilegesRequired": "LOW", "confidentialityImpact": "HIGH"}, "impactScore": 5.3, "exploitabilityScore": 3.1}], "cvssMetricV31": [{"type": "Primary", "source": "nvd@nist.gov", "cvssData": {"scope": "CHANGED", "version": "3.1", "baseScore": 7.7, "attackVector": "NETWORK", "baseSeverity": "HIGH", "vectorString": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:N/A:N", "integrityImpact": "NONE", "userInteraction": "NONE", "attackComplexity": "LOW", "availabilityImpact": "NONE", "privilegesRequired": "LOW", "confidentialityImpact": "HIGH"}, "impactScore": 4.0, "exploitabilityScore": 3.1}, {"type": "Secondary", "source": "0b0ca135-0b70-47e7-9f44-1890c2a1c46c", "cvssData": {"scope": "CHANGED", "version": "3.1", "baseScore": 7.7, "attackVector": "NETWORK", "baseSeverity": "HIGH", "vectorString": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:N/A:N", "integrityImpact": "NONE", "userInteraction": "NONE", "attackComplexity": "LOW", "availabilityImpact": "NONE", "privilegesRequired": "LOW", "confidentialityImpact": "HIGH"}, "impactScore": 4.0, "exploitabilityScore": 3.1}]}, "affected": [{"source": "security@huntr.dev", "affectedData": [{"vendor": "mlflow", "product": "mlflow/mlflow", "versions": [{"status": "affected", "version": "unspecified", "lessThan": "3.11.0", "versionType": "custom"}]}]}, {"source": "0b0ca135-0b70-47e7-9f44-1890c2a1c46c", "affectedData": [{"cpes": ["cpe:/a:redhat:openshift_ai"], "vendor": "Red Hat", "product": "Red Hat OpenShift AI (RHOAI)", "packageName": "rhoai/odh-mlflow-rhel9", "collectionURL": "https://access.redhat.com/downloads/content/package-browser/", "defaultStatus": "unaffected"}, {"cpes": ["cpe:/a:redhat:openshift_ai"], "vendor": "Red Hat", "product": "Red Hat OpenShift AI (RHOAI)", "packageName": "rhoai/odh-pipeline-runtime-datascience-cpu-py312-rhel9", "collectionURL": "https://access.redhat.com/downloads/content/package-browser/", "defaultStatus": "unaffected"}, {"cpes": ["cpe:/a:redhat:openshift_ai"], "vendor": "Red Hat", "product": "Red Hat OpenShift AI (RHOAI)", "packageName": "rhoai/odh-pipeline-runtime-pytorch-cuda-py312-rhel9", "collectionURL": "https://access.redhat.com/downloads/content/package-browser/", "defaultStatus": "unaffected"}, {"cpes": ["cpe:/a:redhat:openshift_ai"], "vendor": "Red Hat", "product": "Red Hat OpenShift AI (RHOAI)", "packageName": "rhoai/odh-pipeline-runtime-pytorch-llmcompressor-cuda-py312-rhel9", "collectionURL": "https://access.redhat.com/downloads/content/package-browser/", "defaultStatus": "unaffected"}, {"cpes": ["cpe:/a:redhat:openshift_ai"], "vendor": "Red Hat", "product": "Red Hat OpenShift AI (RHOAI)", "packageName": "rhoai/odh-pipeline-runtime-pytorch-rocm-py312-rhel9", "collectionURL": "https://access.redhat.com/downloads/content/package-browser/", "defaultStatus": "unaffected"}, {"cpes": ["cpe:/a:redhat:openshift_ai"], "vendor": "Red Hat", "product": "Red Hat OpenShift AI (RHOAI)", "packageName": "rhoai/odh-pipeline-runtime-tensorflow-cuda-py312-rhel9", "collectionURL": "https://access.redhat.com/downloads/content/package-browser/", "defaultStatus": "unaffected"}, {"cpes": ["cpe:/a:redhat:openshift_ai"], "vendor": "Red Hat", "product": "Red Hat OpenShift AI (RHOAI)", "packageName": "rhoai/odh-pipeline-runtime-tensorflow-rocm-py312-rhel9", "collectionURL": "https://access.redhat.com/downloads/content/package-browser/", "defaultStatus": "unaffected"}, {"cpes": ["cpe:/a:redhat:openshift_ai"], "vendor": "Red Hat", "product": "Red Hat OpenShift AI (RHOAI)", "packageName": "rhoai/odh-th06-cpu-torch210-py312-rhel9", "collectionURL": "https://access.redhat.com/downloads/content/package-browser/", "defaultStatus": "unaffected"}, {"cpes": ["cpe:/a:redhat:openshift_ai"], "vendor": "Red Hat", "product": "Red Hat OpenShift AI (RHOAI)", "packageName": "rhoai/odh-th06-cuda130-torch210-py312-rhel9", "collectionURL": "https://access.redhat.com/downloads/content/package-browser/", "defaultStatus": "unaffected"}, {"cpes": ["cpe:/a:redhat:openshift_ai"], "vendor": "Red Hat", "product": "Red Hat OpenShift AI (RHOAI)", "packageName": "rhoai/odh-th06-rocm64-torch291-py312-rhel9", "collectionURL": "https://access.redhat.com/downloads/content/package-browser/", "defaultStatus": "unaffected"}, {"cpes": ["cpe:/a:redhat:openshift_ai"], "vendor": "Red Hat", "product": "Red Hat OpenShift AI (RHOAI)", "packageName": "rhoai/odh-training-cuda128-torch29-py312-rhel9", "collectionURL": "https://access.redhat.com/downloads/content/package-browser/", "defaultStatus": "unaffected"}, {"cpes": ["cpe:/a:redhat:openshift_ai"], "vendor": "Red Hat", "product": "Red Hat OpenShift AI (RHOAI)", "packageName": "rhoai/odh-workbench-codeserver-datascience-cpu-py312-rhel9", "collectionURL": "https://access.redhat.com/downloads/content/package-browser/", "defaultStatus": "unaffected"}, {"cpes": ["cpe:/a:redhat:openshift_ai"], "vendor": "Red Hat", "product": "Red Hat OpenShift AI (RHOAI)", "packageName": "rhoai/odh-workbench-jupyter-datascience-cpu-py312-rhel9", "collectionURL": "https://access.redhat.com/downloads/content/package-browser/", "defaultStatus": "unaffected"}, {"cpes": ["cpe:/a:redhat:openshift_ai"], "vendor": "Red Hat", "product": "Red Hat OpenShift AI (RHOAI)", "packageName": "rhoai/odh-workbench-jupyter-pytorch-cuda-py312-rhel9", "collectionURL": "https://access.redhat.com/downloads/content/package-browser/", "defaultStatus": "unaffected"}, {"cpes": ["cpe:/a:redhat:openshift_ai"], "vendor": "Red Hat", "product": "Red Hat OpenShift AI (RHOAI)", "packageName": "rhoai/odh-workbench-jupyter-pytorch-llmcompressor-cuda-py312-rhel9", "collectionURL": "https://access.redhat.com/downloads/content/package-browser/", "defaultStatus": "unaffected"}, {"cpes": ["cpe:/a:redhat:openshift_ai"], "vendor": "Red Hat", "product": "Red Hat OpenShift AI (RHOAI)", "packageName": "rhoai/odh-workbench-jupyter-pytorch-rocm-py312-rhel9", "collectionURL": "https://access.redhat.com/downloads/content/package-browser/", "defaultStatus": "unaffected"}, {"cpes": ["cpe:/a:redhat:openshift_ai"], "vendor": "Red Hat", "product": "Red Hat OpenShift AI (RHOAI)", "packageName": "rhoai/odh-workbench-jupyter-tensorflow-cuda-py312-rhel9", "collectionURL": "https://access.redhat.com/downloads/content/package-browser/", "defaultStatus": "unaffected"}, {"cpes": ["cpe:/a:redhat:openshift_ai"], "vendor": "Red Hat", "product": "Red Hat OpenShift AI (RHOAI)", "packageName": "rhoai/odh-workbench-jupyter-tensorflow-rocm-py312-rhel9", "collectionURL": "https://access.redhat.com/downloads/content/package-browser/", "defaultStatus": "unaffected"}, {"cpes": ["cpe:/a:redhat:openshift_ai"], "vendor": "Red Hat", "product": "Red Hat OpenShift AI (RHOAI)", "packageName": "rhoai/odh-workbench-jupyter-trustyai-cpu-py312-rhel9", "collectionURL": "https://access.redhat.com/downloads/content/package-browser/", "defaultStatus": "unaffected"}]}], "published": "2026-06-03T09:16:13.083", "references": [{"url": "https://github.com/mlflow/mlflow/commit/4a3f2f720cb4f058c9e0c5b883e0acc9ab64a7f3", "tags": ["Patch"], "source": "security@huntr.dev"}, {"url": "https://huntr.com/bounties/f8e591a0-0f19-4910-b82e-16c9956f2233", "tags": ["Exploit", "Third Party Advisory"], "source": "security@huntr.dev"}, {"url": "https://access.redhat.com/security/cve/CVE-2026-4035", "source": "0b0ca135-0b70-47e7-9f44-1890c2a1c46c"}, {"url": "https://bugzilla.redhat.com/show_bug.cgi?id=2484318", "source": "0b0ca135-0b70-47e7-9f44-1890c2a1c46c"}, {"url": "https://huntr.com/bounties/f8e591a0-0f19-4910-b82e-16c9956f2233", "tags": ["Exploit", "Third Party Advisory"], "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0"}, {"url": "https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-4035.json", "source": "0b0ca135-0b70-47e7-9f44-1890c2a1c46c"}], "vulnStatus": "Modified", "weaknesses": [{"type": "Secondary", "source": "security@huntr.dev", "description": [{"lang": "en", "value": "CWE-201"}]}, {"type": "Secondary", "source": "0b0ca135-0b70-47e7-9f44-1890c2a1c46c", "description": [{"lang": "en", "value": "CWE-201"}]}], "descriptions": [{"lang": "en", "value": "A vulnerability in mlflow/mlflow versions prior to 3.11.0 allows for the resolution of environment variables in AI Gateway secrets, which can be exploited to exfiltrate sensitive server-side environment credentials to an attacker-controlled endpoint. This issue arises because the `api_key` field in gateway secrets can accept `$ENV_VAR` references, which are resolved against the MLflow server's environment during runtime. The resolved secrets are then sent in provider authentication headers to the configured upstream `api_base`. This vulnerability can be exploited by low-privileged authenticated users in basic-auth deployments or by unauthenticated users in default deployments without `basic-auth`. The impact includes potential leakage of sensitive credentials such as cloud artifact credentials (`AWS_ACCESS_KEY_ID`, `AWS_SECRET_ACCESS_KEY`), which could lead to artifact poisoning and cross-boundary code execution in downstream environments. The issue is fixed in version 3.11.0."}, {"lang": "es", "value": "Una vulnerabilidad en las versiones de mlflow/mlflow anteriores a la 3.11.0 permite la resoluci\u00f3n de variables de entorno en secretos de AI Gateway, lo que puede ser explotado para exfiltrar credenciales de entorno sensibles del lado del servidor a un punto final controlado por un atacante. Este problema surge porque el campo 'api_key' en los secretos del gateway puede aceptar referencias a '$ENV_VAR', que se resuelven contra el entorno del servidor de MLflow durante el tiempo de ejecuci\u00f3n. Los secretos resueltos se env\u00edan entonces en los encabezados de autenticaci\u00f3n del proveedor al 'api_base' ascendente configurado. Esta vulnerabilidad puede ser explotada por usuarios autenticados con bajos privilegios en implementaciones con 'basic-auth' o por usuarios no autenticados en implementaciones predeterminadas sin 'basic-auth'. El impacto incluye la posible fuga de credenciales sensibles, como credenciales de artefactos en la nube ('AWS_ACCESS_KEY_ID', 'AWS_SECRET_ACCESS_KEY'), lo que podr\u00eda llevar al envenenamiento de artefactos y a la ejecuci\u00f3n de c\u00f3digo transfronteriza en entornos descendentes. El problema est\u00e1 solucionado en la versi\u00f3n 3.11.0."}], "lastModified": "2026-08-14T13:19:00.193", "configurations": [{"nodes": [{"negate": false, "cpeMatch": [{"criteria": "cpe:2.3:a:lfprojects:mlflow:*:*:*:*:*:*:*:*", "vulnerable": true, "matchCriteriaId": "6EFB4C88-58E2-416A-95A7-FA6C4CDF4288", "versionEndExcluding": "3.11.0"}], "operator": "OR"}]}], "sourceIdentifier": "security@huntr.dev"}