GSD-2022-27207
Vulnerability from gsd - Updated: 2023-12-13 01:19Details
Jenkins global-build-stats Plugin 1.5 and earlier does not escape multiple fields in the chart configuration on the 'Global Build Stats' page, resulting in a stored cross-site scripting (XSS) vulnerability exploitable by attackers with Overall/Administer permission.
Aliases
Aliases
{
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"alias": "CVE-2022-27207",
"description": "Jenkins global-build-stats Plugin 1.5 and earlier does not escape multiple fields in the chart configuration on the \u0027Global Build Stats\u0027 page, resulting in a stored cross-site scripting (XSS) vulnerability exploitable by attackers with Overall/Administer permission.",
"id": "GSD-2022-27207"
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
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"details": "Jenkins global-build-stats Plugin 1.5 and earlier does not escape multiple fields in the chart configuration on the \u0027Global Build Stats\u0027 page, resulting in a stored cross-site scripting (XSS) vulnerability exploitable by attackers with Overall/Administer permission.",
"id": "GSD-2022-27207",
"modified": "2023-12-13T01:19:40.714358Z",
"schema_version": "1.4.0"
}
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"cwe_ids": [
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"CWE-79",
"CWE-937"
],
"date": "2022-03-23",
"description": "Jenkins global-build-stats Plugin 1.5 and earlier does not escape multiple fields in the chart configuration on the \u0027Global Build Stats\u0027 page, resulting in a stored cross-site scripting (XSS) vulnerability exploitable by attackers with Overall/Administer permission.",
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"identifier": "CVE-2022-27207",
"identifiers": [
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"not_impacted": "",
"package_slug": "maven/org.jenkins-ci.plugins/global-build-stats",
"pubdate": "2022-03-15",
"solution": "Unfortunately, there is no solution available yet.",
"title": "Improper Neutralization of Input During Web Page Generation (\u0027Cross-site Scripting\u0027)",
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"authentication": "SINGLE",
"availabilityImpact": "NONE",
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"confidentialityImpact": "NONE",
"integrityImpact": "PARTIAL",
"vectorString": "AV:N/AC:M/Au:S/C:N/I:P/A:N",
"version": "2.0"
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"exploitabilityScore": 6.8,
"impactScore": 2.9,
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"severity": "LOW",
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},
"lastModifiedDate": "2023-11-15T04:03Z",
"publishedDate": "2022-03-15T17:15Z"
}
}
}
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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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