CVE-2015-10082 (GCVE-0-2015-10082)
Vulnerability from cvelistv5 – Published: 2023-02-21 07:00 – Updated: 2024-08-06 08:58
VLAI
EPSS
VEX
Title
UIKit0 libplist XML xplist.c plist_from_xml xml external entity reference
Summary
A vulnerability classified as problematic has been found in UIKit0 libplist 1.12. This affects the function plist_from_xml of the file src/xplist.c of the component XML Handler. The manipulation leads to xml external entity reference. The patch is named c086cb139af7c82845f6d565e636073ff4b37440. It is recommended to apply a patch to fix this issue. The associated identifier of this vulnerability is VDB-221499.
Severity
5.5 (Medium)
5.5 (Medium)
CWE
- CWE-611 - XML External Entity Reference
Assigner
References
3 references
| URL | Tags |
|---|---|
| https://vuldb.com/?id.221499 | vdb-entrytechnical-description |
| https://vuldb.com/?ctiid.221499 | signaturepermissions-required |
| https://github.com/UIKit0/libplist/commit/c086cb1… | patch |
Impacted products
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"value": "A vulnerability classified as problematic has been found in UIKit0 libplist 1.12. This affects the function plist_from_xml of the file src/xplist.c of the component XML Handler. The manipulation leads to xml external entity reference. The patch is named c086cb139af7c82845f6d565e636073ff4b37440. It is recommended to apply a patch to fix this issue. The associated identifier of this vulnerability is VDB-221499."
},
{
"lang": "de",
"value": "Es wurde eine Schwachstelle in UIKit0 libplist 1.12 entdeckt. Sie wurde als problematisch eingestuft. Betroffen hiervon ist die Funktion plist_from_xml der Datei src/xplist.c der Komponente XML Handler. Durch die Manipulation mit unbekannten Daten kann eine xml external entity reference-Schwachstelle ausgenutzt werden. Der Patch wird als c086cb139af7c82845f6d565e636073ff4b37440 bezeichnet. Als bestm\u00f6gliche Massnahme wird Patching empfohlen."
}
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"value": "VulDB entry created"
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"lang": "en",
"time": "2023-03-23T11:08:47.000Z",
"value": "VulDB entry last update"
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"title": "SUSE CVE CVE-2015-10082",
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}
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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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