GHSA-WQFG-M96J-85VM
Vulnerability from github – Published: 2025-04-02 15:31 – Updated: 2025-04-09 20:02An issue was discovered in Django 5.1 before 5.1.8 and 5.0 before 5.0.14. The NFKC normalization is slow on Windows. As a consequence, django.contrib.auth.views.LoginView, django.contrib.auth.views.LogoutView, and django.views.i18n.set_language are subject to a potential denial-of-service attack via certain inputs with a very large number of Unicode characters.
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "Django"
},
"ranges": [
{
"events": [
{
"introduced": "5.0"
},
{
"fixed": "5.0.14"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "Django"
},
"ranges": [
{
"events": [
{
"introduced": "5.1"
},
{
"fixed": "5.1.8"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2025-27556"
],
"database_specific": {
"cwe_ids": [
"CWE-770"
],
"github_reviewed": true,
"github_reviewed_at": "2025-04-02T20:11:40Z",
"nvd_published_at": "2025-04-02T13:15:44Z",
"severity": "MODERATE"
},
"details": "An issue was discovered in Django 5.1 before 5.1.8 and 5.0 before 5.0.14. The NFKC normalization is slow on Windows. As a consequence, django.contrib.auth.views.LoginView, django.contrib.auth.views.LogoutView, and django.views.i18n.set_language are subject to a potential denial-of-service attack via certain inputs with a very large number of Unicode characters.",
"id": "GHSA-wqfg-m96j-85vm",
"modified": "2025-04-09T20:02:06Z",
"published": "2025-04-02T15:31:37Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2025-27556"
},
{
"type": "WEB",
"url": "https://github.com/django/django/commit/2cb311f7b069723027fb5def4044d1816d7d2afd"
},
{
"type": "WEB",
"url": "https://github.com/django/django/commit/39e2297210d9d2938c75fc911d45f0e863dc4821"
},
{
"type": "WEB",
"url": "https://github.com/django/django/commit/8c6871b097b6c49d2a782c0d80d908bcbe2116f1"
},
{
"type": "WEB",
"url": "https://github.com/django/django/commit/edc2716d01a6fdd84b173c02031695231bcee1f8"
},
{
"type": "WEB",
"url": "https://docs.djangoproject.com/en/dev/releases/security"
},
{
"type": "PACKAGE",
"url": "https://github.com/django/django"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/django/PYSEC-2025-14.yaml"
},
{
"type": "WEB",
"url": "https://groups.google.com/g/django-announce"
},
{
"type": "WEB",
"url": "https://www.djangoproject.com/weblog/2025/apr/02/security-releases"
},
{
"type": "WEB",
"url": "http://www.openwall.com/lists/oss-security/2025/04/02/2"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:N/I:N/A:L",
"type": "CVSS_V3"
}
],
"summary": "Django Potential Denial of Service (DoS) on Windows "
}
Drag nodes to arrange them. Double-click a related vulnerability to open it, or a source to visit its link. The Physics button on the left tunes the layout and the simulation; the legend at the bottom left hides or shows nodes by kind and by sighting type.
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.
Vulnerability timeline
Sightings and recorded dates, grouped by day · UTC
Loading timeline…
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.