GSD-2014-3995
Vulnerability from gsd - Updated: 2023-12-13 01:22Details
Cross-site scripting (XSS) vulnerability in gravatars/templatetags/gravatars.py in Djblets before 0.7.30 and 0.8.x before 0.8.3 for Django allows remote attackers to inject arbitrary web script or HTML via a user display name.
Aliases
Aliases
{
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"alias": "CVE-2014-3995",
"description": "Cross-site scripting (XSS) vulnerability in gravatars/templatetags/gravatars.py in Djblets before 0.7.30 and 0.8.x before 0.8.3 for Django allows remote attackers to inject arbitrary web script or HTML via a user display name.",
"id": "GSD-2014-3995",
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"credit": "Christian Hammond of Bean Bag, Inc.",
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"cwe_ids": [
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"CWE-79",
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],
"date": "2014-06-17",
"description": "The generated gravatar HTML wasn\u0027t handling escaping of the display name of the user, allowing an attacker to choose a name that would close out the \u003cimg\u003e tag and inject a \u003cscript\u003e tag.",
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"package_slug": "pypi/Djblets",
"pubdate": "2014-06-16",
"solution": "Upgrade to versions 0.7.30, 0.8.3 or above.",
"title": "XSS Vulnerability in Djblets gravatar templates",
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"accessVector": "NETWORK",
"authentication": "NONE",
"availabilityImpact": "NONE",
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"integrityImpact": "PARTIAL",
"vectorString": "AV:N/AC:M/Au:N/C:N/I:P/A:N",
"version": "2.0"
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"exploitabilityScore": 8.6,
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},
"lastModifiedDate": "2014-06-17T14:22Z",
"publishedDate": "2014-06-16T18:55Z"
}
}
}
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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.
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- 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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