PYSEC-2026-1654
Vulnerability from pysec - Published: 2026-07-07 11:45 - Updated: 2026-07-07 17:24
VLAI
Details
Deserialization of untrusted data can occur in versions of the MLflow platform running version 2.0.0rc0 or newer, enabling a maliciously uploaded Tensorflow model to run arbitrary code on an end user’s system when interacted with.
Severity
8.8 (High)
Impacted products
| Name | purl | mlflow | pkg:pypi/mlflow |
|---|
Aliases
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "mlflow",
"purl": "pkg:pypi/mlflow"
},
"ranges": [
{
"events": [
{
"introduced": "2.0.0rc0"
},
{
"last_affected": "2.14.1"
}
],
"type": "ECOSYSTEM"
}
],
"versions": [
"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",
"2.2.0",
"2.2.1",
"2.2.2",
"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"
]
}
],
"aliases": [
"CVE-2024-37057",
"GHSA-j8mg-pqc5-x9gj"
],
"details": "Deserialization of untrusted data can occur in versions of the MLflow platform running version 2.0.0rc0 or newer, enabling a maliciously uploaded Tensorflow model to run arbitrary code on an end user\u2019s system when interacted with.",
"id": "PYSEC-2026-1654",
"modified": "2026-07-07T17:24:42.912350Z",
"published": "2026-07-07T11:45:45.008758Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2024-37057"
},
{
"type": "PACKAGE",
"url": "https://github.com/mlflow/mlflow"
},
{
"type": "WEB",
"url": "https://hiddenlayer.com/sai-security-advisory/mlflow-june2024"
},
{
"type": "PACKAGE",
"url": "https://pypi.org/project/mlflow"
},
{
"type": "ADVISORY",
"url": "https://github.com/advisories/GHSA-j8mg-pqc5-x9gj"
}
],
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H",
"type": "CVSS_V3"
}
],
"summary": "MLFlow unsafe deserialization"
}
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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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