GHSA-49M6-VRR9-2CQM
Vulnerability from github – Published: 2025-03-20 12:32 – Updated: 2025-03-21 23:50
VLAI
Summary
MLflow Uncontrolled Resource Consumption vulnerability
Details
In mlflow/mlflow version 2.17.2, the /graphql endpoint is vulnerable to a denial of service attack. An attacker can create large batches of queries that repeatedly request all runs from a given experiment. This can tie up all the workers allocated by MLFlow, rendering the application unable to respond to other requests. This vulnerability is due to uncontrolled resource consumption.
Severity
5.9 (Medium)
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "mlflow"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"last_affected": "2.17.2"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2025-0453"
],
"database_specific": {
"cwe_ids": [
"CWE-400",
"CWE-410"
],
"github_reviewed": true,
"github_reviewed_at": "2025-03-21T23:50:45Z",
"nvd_published_at": "2025-03-20T10:15:53Z",
"severity": "MODERATE"
},
"details": "In mlflow/mlflow version 2.17.2, the `/graphql` endpoint is vulnerable to a denial of service attack. An attacker can create large batches of queries that repeatedly request all runs from a given experiment. This can tie up all the workers allocated by MLFlow, rendering the application unable to respond to other requests. This vulnerability is due to uncontrolled resource consumption.",
"id": "GHSA-49m6-vrr9-2cqm",
"modified": "2025-03-21T23:50:45Z",
"published": "2025-03-20T12:32:52Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2025-0453"
},
{
"type": "PACKAGE",
"url": "https://github.com/mlflow/mlflow"
},
{
"type": "WEB",
"url": "https://huntr.com/bounties/788327ec-714a-4d5c-83aa-8df04dd7612b"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.0/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H",
"type": "CVSS_V3"
}
],
"summary": "MLflow Uncontrolled Resource Consumption vulnerability"
}
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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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