GSD-2022-25196
Vulnerability from gsd - Updated: 2023-12-13 01:19Details
Jenkins GitLab Authentication Plugin 1.13 and earlier records the HTTP Referer header as part of the URL query parameters when the authentication process starts, allowing attackers with access to Jenkins to craft a URL that will redirect users to an attacker-specified URL after logging in.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2022-25196",
"description": "Jenkins GitLab Authentication Plugin 1.13 and earlier records the HTTP Referer header as part of the URL query parameters when the authentication process starts, allowing attackers with access to Jenkins to craft a URL that will redirect users to an attacker-specified URL after logging in.",
"id": "GSD-2022-25196"
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
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],
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"id": "GSD-2022-25196",
"modified": "2023-12-13T01:19:27.211393Z",
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"cwe_ids": [
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"CWE-601",
"CWE-937"
],
"date": "2022-02-23",
"description": "Jenkins GitLab Authentication Plugin 1.13 and earlier records the HTTP Referer header as part of the URL query parameters when the authentication process starts, allowing attackers with access to Jenkins to craft a URL that will redirect users to an attacker-specified URL after logging in.",
"fixed_versions": [],
"identifier": "CVE-2022-25196",
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"not_impacted": "",
"package_slug": "maven/org.jenkins-ci.plugins/gitlab-oauth",
"pubdate": "2022-02-15",
"solution": "Unfortunately, there is no solution available yet.",
"title": "URL Redirection to Untrusted Site (\u0027Open Redirect\u0027)",
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"accessVector": "NETWORK",
"authentication": "SINGLE",
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"vectorString": "AV:N/AC:M/Au:S/C:P/I:P/A:N",
"version": "2.0"
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"exploitabilityScore": 6.8,
"impactScore": 4.9,
"obtainAllPrivilege": false,
"obtainOtherPrivilege": false,
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"privilegesRequired": "LOW",
"scope": "CHANGED",
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},
"lastModifiedDate": "2023-11-03T16:24Z",
"publishedDate": "2022-02-15T17:15Z"
}
}
}
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Sightings
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Vulnerability timeline
Sightings and recorded dates, grouped by day · UTC
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
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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.
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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.