PYSEC-2026-2220
Vulnerability from pysec - Published: 2026-05-25 07:16 - Updated: 2026-07-13 05:49
VLAI
Details
A vulnerability in MLflow versions <=3.10.1.dev0 allows unauthorized access to multipart upload (MPU) endpoints when the --serve-artifacts mode is enabled. The authorization logic does not enforce resource-level permission checks for /mlflow-artifacts/mpu/* endpoints, enabling attackers to overwrite artifacts belonging to other users. This can lead to unauthorized cross-user writes, model supply chain poisoning, and arbitrary code execution when compromised models are loaded. The issue is resolved in version 3.10.0.
Severity
9.0 (Critical)
Impacted products
| Name | purl | mlflow | pkg:pypi/mlflow |
|---|
Aliases
{
"affected": [
{
"ecosystem_specific": {},
"package": {
"ecosystem": "PyPI",
"name": "mlflow",
"purl": "pkg:pypi/mlflow"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "3.11.0rc0"
}
],
"type": "ECOSYSTEM"
}
],
"versions": [
"0.0.1",
"0.1.0",
"0.2.0",
"0.2.1",
"0.3.0",
"0.4.0",
"0.4.1",
"0.4.2",
"0.5.0",
"0.5.1",
"0.5.2",
"0.6.0",
"0.7.0",
"0.8.0",
"0.8.1",
"0.8.2",
"0.9.0",
"0.9.0.1",
"0.9.1",
"1.0.0",
"1.1.0",
"1.1.1.dev0",
"1.10.0",
"1.11.0",
"1.12.0",
"1.12.1",
"1.13",
"1.13.1",
"1.14.0",
"1.14.1",
"1.15.0",
"1.16.0",
"1.17.0",
"1.18.0",
"1.19.0",
"1.2.0",
"1.20.0",
"1.20.1",
"1.20.2",
"1.21.0",
"1.22.0",
"1.23.0",
"1.23.1",
"1.24.0",
"1.25.0",
"1.25.1",
"1.26.0",
"1.26.1",
"1.27.0",
"1.28.0",
"1.29.0",
"1.3.0",
"1.30.0",
"1.30.1",
"1.4.0",
"1.5.0",
"1.6.0",
"1.7.0",
"1.7.1",
"1.7.2",
"1.8.0",
"1.9.0",
"1.9.1",
"2.0.0",
"2.0.0rc0",
"2.0.1",
"2.1.0",
"2.1.1",
"2.10.0",
"2.10.1",
"2.10.2",
"2.11.0",
"2.11.1",
"2.11.2",
"2.11.3",
"2.11.4",
"2.12.0",
"2.12.1",
"2.12.2",
"2.13.0",
"2.13.1",
"2.13.2",
"2.14.0",
"2.14.0rc0",
"2.14.1",
"2.14.2",
"2.14.2.dev0",
"2.14.3",
"2.15.0",
"2.15.0rc0",
"2.15.1",
"2.16.0",
"2.16.1",
"2.16.2",
"2.17.0",
"2.17.0rc0",
"2.17.1",
"2.17.2",
"2.18.0",
"2.18.0rc0",
"2.19.0",
"2.19.0rc0",
"2.2.0",
"2.2.1",
"2.2.2",
"2.20.0",
"2.20.0rc0",
"2.20.1",
"2.20.2",
"2.20.3",
"2.20.4",
"2.21.0",
"2.21.0rc0",
"2.21.1",
"2.21.2",
"2.21.3",
"2.22.0",
"2.22.0rc0",
"2.22.1",
"2.22.2",
"2.22.3",
"2.22.4",
"2.22.5",
"2.3.0",
"2.3.1",
"2.3.2",
"2.4.0",
"2.4.1",
"2.4.2",
"2.5.0",
"2.6.0",
"2.7.0",
"2.7.1",
"2.8.0",
"2.8.1",
"2.9.0",
"2.9.1",
"2.9.2",
"3.0.0",
"3.0.0rc0",
"3.0.0rc1",
"3.0.0rc2",
"3.0.0rc3",
"3.0.1",
"3.1.0",
"3.1.0rc0",
"3.1.1",
"3.1.2",
"3.1.3",
"3.1.4",
"3.10.0",
"3.10.0rc0",
"3.10.1",
"3.2.0",
"3.2.0rc0",
"3.3.0",
"3.3.0rc0",
"3.3.1",
"3.3.2",
"3.4.0",
"3.4.0rc0",
"3.5.0",
"3.5.0rc0",
"3.5.1",
"3.6.0",
"3.6.0rc0",
"3.7.0",
"3.7.0rc0",
"3.8.0",
"3.8.0rc0",
"3.8.1",
"3.9.0",
"3.9.0rc0"
]
}
],
"aliases": [
"CVE-2026-2651",
"GHSA-8c7q-86fq-vvmh"
],
"details": "A vulnerability in MLflow versions \u003c=3.10.1.dev0 allows unauthorized access to multipart upload (MPU) endpoints when the `--serve-artifacts` mode is enabled. The authorization logic does not enforce resource-level permission checks for `/mlflow-artifacts/mpu/*` endpoints, enabling attackers to overwrite artifacts belonging to other users. This can lead to unauthorized cross-user writes, model supply chain poisoning, and arbitrary code execution when compromised models are loaded. The issue is resolved in version 3.10.0.",
"id": "PYSEC-2026-2220",
"modified": "2026-07-13T05:49:59.205895Z",
"published": "2026-05-25T07:16:15.100Z",
"references": [
{
"type": "WEB",
"url": "https://access.redhat.com/security/cve/CVE-2026-2651"
},
{
"type": "WEB",
"url": "https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-2651.json"
},
{
"type": "REPORT",
"url": "https://bugzilla.redhat.com/show_bug.cgi?id=2481117"
},
{
"type": "FIX",
"url": "https://github.com/mlflow/mlflow/commit/d7290811d8f3c95366d80109424edc1fb1ad966f"
},
{
"type": "EVIDENCE",
"url": "https://huntr.com/bounties/65beb119-d3e0-4e03-af2f-fa98f78f83dc"
},
{
"type": "ADVISORY",
"url": "https://github.com/advisories/GHSA-8c7q-86fq-vvmh"
}
],
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:C/C:H/I:H/A:H",
"type": "CVSS_V3"
}
]
}
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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