cve-2026-4035
HIGH CVSS 7.7 csaf_redhat
Description
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.
Timeline
- Published
- 2026-06-03 07:18 UTC
- Last Modified
- 2026-08-13
CVSS Details
CVSS details not available.
Affected Products
No product information available.
Weaknesses (CWE)
References
No references available.
Linked Vulnerabilities
No linked vulnerabilities found.
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"product_id": "red_hat_openshift_ai_(rhoai):rhoai/odh-workbench-jupyter-tensorflow-rocm-py312-rhel9"
},
"product_reference": "rhoai/odh-workbench-jupyter-tensorflow-rocm-py312-rhel9",
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{
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},
"vulnerabilities": [
{
"cve": "CVE-2026-4035",
"cwe": {
"id": "CWE-201",
"name": "Insertion of Sensitive Information Into Sent Data"
},
"discovery_date": "2026-06-03T09:00:55.993529+00:00",
"flags": [
{
"label": "inline_mitigations_already_exist",
"product_ids": [
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]
},
{
"label": "vulnerable_code_not_present",
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],
"ids": [
{
"system_name": "Red 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": {
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"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"
},
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}
],
"title": "python-mlflow: MLflow: Sensitive credential exfiltration via environment variable resolution in AI Gateway secrets"
}
]
}
Enrichment data
Aggregated bundle (all enrichments)