GSD-2022-23640
Vulnerability from gsd - Updated: 2023-12-13 01:19Details
Excel-Streaming-Reader is an easy-to-use implementation of a streaming Excel reader using Apache POI. Prior to xlsx-streamer 2.1.0, the XML parser that was used did apply all the necessary settings to prevent XML Entity Expansion issues. Upgrade to version 2.1.0 to receive a patch. There is no known workaround.
Aliases
Aliases
{
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"description": "Excel-Streaming-Reader is an easy-to-use implementation of a streaming Excel reader using Apache POI. Prior to xlsx-streamer 2.1.0, the XML parser that was used did apply all the necessary settings to prevent XML Entity Expansion issues. Upgrade to version 2.1.0 to receive a patch. There is no known workaround.",
"id": "GSD-2022-23640"
},
"gsd": {
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"remediation": "unknown",
"reportConfidence": "confirmed",
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"id": "GSD-2022-23640",
"modified": "2023-12-13T01:19:35.780556Z",
"schema_version": "1.4.0"
}
},
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},
"affects": {
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}
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"source": {
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"gitlab.com": {
"advisories": [
{
"affected_range": "(,2.1.0)",
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"CWE-937"
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"date": "2022-03-03",
"description": "Excel-Streaming-Reader is an easy-to-use implementation of a streaming Excel reader using Apache POI. Prior to xlsx-streamer 2.1.0, the XML parser that was used did apply all the necessary settings to prevent XML Entity Expansion issues. Upgrade to version 2.1.0 to receive a patch. There is no known workaround.",
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"package_slug": "maven/com.monitorjbl/xlsx-streamer",
"pubdate": "2022-03-02",
"solution": "Upgrade to version 2.1.0 or above.",
"title": "Improper Restriction of XML External Entity Reference",
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"authentication": "NONE",
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"baseScore": 7.5,
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"integrityImpact": "PARTIAL",
"vectorString": "AV:N/AC:L/Au:N/C:P/I:P/A:P",
"version": "2.0"
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},
"lastModifiedDate": "2023-07-24T13:47Z",
"publishedDate": "2022-03-02T20:15Z"
}
}
}
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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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