GSD-2011-4140
Vulnerability from gsd - Updated: 2023-12-13 01:19Details
The CSRF protection mechanism in Django through 1.2.7 and 1.3.x through 1.3.1 does not properly handle web-server configurations supporting arbitrary HTTP Host headers, which allows remote attackers to trigger unauthenticated forged requests via vectors involving a DNS CNAME record and a web page containing JavaScript code.
Aliases
Aliases
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"alias": "CVE-2011-4140",
"description": "The CSRF protection mechanism in Django through 1.2.7 and 1.3.x through 1.3.1 does not properly handle web-server configurations supporting arbitrary HTTP Host headers, which allows remote attackers to trigger unauthenticated forged requests via vectors involving a DNS CNAME record and a web page containing JavaScript code.",
"id": "GSD-2011-4140",
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"https://www.debian.org/security/2011/dsa-2332"
]
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"modified": "2023-12-13T01:19:06.096585Z",
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"affected_versions": "All versions before 1.2.7, all versions starting from 1.3.0 before 1.3.1",
"cvss_v2": "AV:N/AC:M/Au:N/C:P/I:P/A:P",
"cwe_ids": [
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"CWE-352",
"CWE-352",
"CWE-937"
],
"date": "2021-09-14",
"description": "The CSRF protection mechanism in Django through 1.2.7 and 1.3.x through 1.3.1 does not properly handle web-server configurations supporting arbitrary HTTP Host headers, which allows remote attackers to trigger unauthenticated forged requests via vectors involving a DNS CNAME record and a web page containing JavaScript code.",
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"1.3.1"
],
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"not_impacted": "All versions starting from 1.2.7 before 1.3.0, all versions starting from 1.3.1",
"package_slug": "pypi/Django",
"pubdate": "2018-07-23",
"solution": "Upgrade to versions 1.2.7, 1.3.1 or above.",
"title": "Cross-Site Request Forgery ",
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"impact": {
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"accessComplexity": "MEDIUM",
"accessVector": "NETWORK",
"authentication": "NONE",
"availabilityImpact": "PARTIAL",
"baseScore": 6.8,
"confidentialityImpact": "PARTIAL",
"integrityImpact": "PARTIAL",
"vectorString": "AV:N/AC:M/Au:N/C:P/I:P/A:P",
"version": "2.0"
},
"exploitabilityScore": 8.6,
"impactScore": 6.4,
"obtainAllPrivilege": false,
"obtainOtherPrivilege": false,
"obtainUserPrivilege": false,
"severity": "MEDIUM",
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}
},
"lastModifiedDate": "2018-01-18T02:29Z",
"publishedDate": "2011-10-19T10:55Z"
}
}
}
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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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