PYSEC-2026-3853
Vulnerability from pysec - Published: 2026-09-10 09:44 - Updated: 2026-09-10 11:02
VLAI
Details
Impact
Invalid input to login resulted in unbounded logging output. Only form-based Authenticators (the default PAM Authenticator, but not the more widely used OAuthenticator) are affected.
Patches
Upgrade to 5.5.0.
Workarounds
Use an Authenticator that doesn't use a login form, such as OAuthenticator.
Severity
5.3 (Medium)
Impacted products
| Name | purl | jupyterhub | pkg:pypi/jupyterhub |
|---|
Aliases
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "jupyterhub",
"purl": "pkg:pypi/jupyterhub"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "5.5.0"
}
],
"type": "ECOSYSTEM"
}
],
"versions": [
"0.1.0",
"0.2.0",
"0.3.0",
"0.4.0",
"0.4.1",
"0.5.0",
"0.6.0",
"0.6.1",
"0.7.0",
"0.7.0b1",
"0.7.1",
"0.7.2",
"0.8.0",
"0.8.0b1",
"0.8.0b2",
"0.8.0b3",
"0.8.0b4",
"0.8.0b5",
"0.8.0rc1",
"0.8.0rc2",
"0.8.1",
"0.9.0",
"0.9.0b1",
"0.9.0b2",
"0.9.0b3",
"0.9.0rc1",
"0.9.1",
"0.9.2",
"0.9.3",
"0.9.4",
"0.9.5",
"0.9.6",
"1.0.0",
"1.0.0b1",
"1.0.0b2",
"1.1.0",
"1.1.0b1",
"1.2.0",
"1.2.0b1",
"1.2.1",
"1.2.2",
"1.3.0",
"1.4.0",
"1.4.1",
"1.4.2",
"1.5.0",
"1.5.1",
"2.0.0",
"2.0.0b1",
"2.0.0b2",
"2.0.0b3",
"2.0.0rc1",
"2.0.0rc2",
"2.0.0rc3",
"2.0.0rc4",
"2.0.0rc5",
"2.0.1",
"2.0.2",
"2.1.0",
"2.1.1",
"2.2.0",
"2.2.1",
"2.2.2",
"2.3.0",
"2.3.1",
"3.0.0",
"3.0.0b1",
"3.1.0",
"3.1.1",
"4.0.0",
"4.0.0b1",
"4.0.0b2",
"4.0.1",
"4.0.2",
"4.1.0",
"4.1.1",
"4.1.2",
"4.1.3",
"4.1.4",
"4.1.5",
"4.1.6",
"5.0.0",
"5.0.0b1",
"5.0.0b2",
"5.1.0",
"5.2.0",
"5.2.1",
"5.3.0",
"5.3.0rc0",
"5.4.0",
"5.4.1",
"5.4.2",
"5.4.3",
"5.4.4",
"5.4.5",
"5.4.6"
]
}
],
"aliases": [
"CVE-2026-54338",
"GHSA-p43p-whwx-q52h"
],
"details": "### Impact\n\nInvalid input to login resulted in unbounded logging output. Only form-based Authenticators (the default PAM Authenticator, but not the more widely used OAuthenticator) are affected.\n\n### Patches\n\nUpgrade to 5.5.0.\n\n### Workarounds\n\nUse an Authenticator that doesn\u0027t use a login form, such as OAuthenticator.",
"id": "PYSEC-2026-3853",
"modified": "2026-09-10T11:02:10.150719Z",
"published": "2026-09-10T09:44:57.193967Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/jupyterhub/jupyterhub/security/advisories/GHSA-p43p-whwx-q52h"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-54338"
},
{
"type": "WEB",
"url": "https://github.com/jupyterhub/jupyterhub/commit/d6dc595f84b7509969686da31d87d6d69e7fce0a"
},
{
"type": "PACKAGE",
"url": "https://github.com/jupyterhub/jupyterhub"
},
{
"type": "PACKAGE",
"url": "https://pypi.org/project/jupyterhub"
},
{
"type": "ADVISORY",
"url": "https://github.com/advisories/GHSA-p43p-whwx-q52h"
}
],
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L",
"type": "CVSS_V3"
}
],
"summary": "JupyterHub has Unauthenticated Denial of Service via Unbounded Username Logging on Failed Login"
}
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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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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
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.
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.
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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.
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