CVE-2026-97764 (GCVE-0-2026-97764)
Vulnerability from cvelistv5 – Published: 2026-09-25 04:25 – Updated: 2026-09-25 04:25
VLAI
EPSS
VEX
Summary
django-allauth before 65.19.4 does not have the expected limits on failed login attempts because, in some common configurations, an attacker can leverage the handling of diacritics (e.g., accents) for a higher effective limit.
Severity
CWE
- CWE-180 - Incorrect Behavior Order: Validate Before Canonicalize
Assigner
References
5 references
| URL | Tags |
|---|---|
| https://docs.allauth.org/en/latest/release-notes/… | release-notes |
| https://pypi.org/project/django-allauth/ | product |
| https://codeberg.org/allauth/django-allauth/commi… | patch |
| https://codeberg.org/allauth/django-allauth/commi… | patch |
| https://codeberg.org/allauth/django-allauth/commi… | technical-descriptionrelated |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| allauth | django-allauth |
Affected:
0.25.0 , < 65.19.4
(custom)
|
guessed |
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}
],
"value": "The vulnerability is NOT exposed if any of the following settings is enabled.\n\n65.4 and later:\nACCOUNT_LOGIN_METHODS = {\"email\"}\n\n65.3 and earlier:\nACCOUNT_AUTHENTICATION_METHOD = \"email\""
}
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"datePublished": "2026-09-25T04:25:57.932Z",
"dateReserved": "2026-09-25T04:25:57.123Z",
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],
"id": "CVE-2026-97764",
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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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