GSD-2022-36890
Vulnerability from gsd - Updated: 2023-12-13 01:19Details
Jenkins Deployer Framework Plugin 85.v1d1888e8c021 and earlier does not restrict the name of files in methods implementing form validation, allowing attackers with Item/Read permission to check for the existence of an attacker-specified file path on the Jenkins controller file system.
Aliases
Aliases
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"id": "GSD-2022-36890"
},
"gsd": {
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"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
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"id": "GSD-2022-36890",
"modified": "2023-12-13T01:19:21.192819Z",
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"cwe_ids": [
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"date": "2022-08-03",
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"package_slug": "maven/org.jenkins-ci.plugins/deployer-framework",
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"solution": "Unfortunately, there is no solution available yet.",
"title": "Improper Limitation of a Pathname to a Restricted Directory (\u0027Path Traversal\u0027)",
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"attackVector": "NETWORK",
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"baseScore": 4.3,
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"confidentialityImpact": "LOW",
"integrityImpact": "NONE",
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"scope": "UNCHANGED",
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"vectorString": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:N/A:N",
"version": "3.1"
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"lastModifiedDate": "2023-11-22T21:09Z",
"publishedDate": "2022-07-27T15:15Z"
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}
}
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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.
- 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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