GHSA-VWHF-3V6X-WFF8
Vulnerability from github – Published: 2023-12-07 06:30 – Updated: 2024-04-16 18:49A reflected Cross-Site Scripting (XSS) vulnerability exists in the mlflow/mlflow repository, specifically within the handling of the Content-Type header in POST requests. An attacker can inject malicious JavaScript code into the Content-Type header, which is then improperly reflected back to the user without adequate sanitization or escaping, leading to arbitrary JavaScript execution in the context of the victim's browser. The vulnerability is present in the mlflow/server/auth/init.py file, where the user-supplied Content-Type header is directly injected into a Python formatted string and returned to the user, facilitating the XSS attack.
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "mlflow"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.9.0"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2023-6568"
],
"database_specific": {
"cwe_ids": [
"CWE-79"
],
"github_reviewed": true,
"github_reviewed_at": "2023-12-12T00:57:44Z",
"nvd_published_at": "2023-12-07T05:15:09Z",
"severity": "MODERATE"
},
"details": "A reflected Cross-Site Scripting (XSS) vulnerability exists in the mlflow/mlflow repository, specifically within the handling of the Content-Type header in POST requests. An attacker can inject malicious JavaScript code into the Content-Type header, which is then improperly reflected back to the user without adequate sanitization or escaping, leading to arbitrary JavaScript execution in the context of the victim\u0027s browser. The vulnerability is present in the mlflow/server/auth/__init__.py file, where the user-supplied Content-Type header is directly injected into a Python formatted string and returned to the user, facilitating the XSS attack.",
"id": "GHSA-vwhf-3v6x-wff8",
"modified": "2024-04-16T18:49:18Z",
"published": "2023-12-07T06:30:21Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2023-6568"
},
{
"type": "WEB",
"url": "https://github.com/mlflow/mlflow/commit/28ff3f94994941e038f2172c6484b65dc4db6ca1"
},
{
"type": "PACKAGE",
"url": "https://github.com/mlflow/mlflow"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/mlflow/PYSEC-2023-260.yaml"
},
{
"type": "WEB",
"url": "https://huntr.com/bounties/816bdaaa-8153-4732-951e-b0d92fddf709"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.0/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:N/A:N",
"type": "CVSS_V3"
}
],
"summary": "Cross-site Scripting (XSS) in MLflow"
}
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.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.