FKIE_CVE-2015-2942
Vulnerability from fkie_nvd - Published: 2015-04-13 14:59 - Updated: 2026-06-17 00:25
Severity
Summary
MediaWiki before 1.19.24, 1.2x before 1.23.9, and 1.24.x before 1.24.2, when using HHVM, allows remote attackers to cause a denial of service (CPU and memory consumption) via a large number of nested entity references in an (1) SVG file or (2) XMP metadata in a PDF file, aka a "billion laughs attack," a different vulnerability than CVE-2015-2937.
References
Impacted products
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"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "MediaWiki before 1.19.24, 1.2x before 1.23.9, and 1.24.x before 1.24.2, when using HHVM, allows remote attackers to cause a denial of service (CPU and memory consumption) via a large number of nested entity references in an (1) SVG file or (2) XMP metadata in a PDF file, aka a \"billion laughs attack,\" a different vulnerability than CVE-2015-2937."
},
{
"lang": "es",
"value": "MediaWiki anterior a 1.19.24, 1.2x anterior a 1.23.9 y 1.24.x anterior a 1.24.2, cuando se utiliza HHVM, permite a atacantes remotos causar una denegaci\u00f3n de servicio (consumo de CPU y memoria) a trav\u00e9s de un gran n\u00famero de referencias de entidades anidadas en (1) un fichero SVG o (2) metadatos XMP en un fichero PDF, tambi\u00e9n conocido como \u0027billion laughs attack\u0027, una vulnerabilidad diferente a CVE-2015-2937."
}
],
"id": "CVE-2015-2942",
"lastModified": "2026-06-17T00:25:00.747",
"metrics": {
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"acInsufInfo": false,
"baseSeverity": "HIGH",
"cvssData": {
"accessComplexity": "MEDIUM",
"accessVector": "NETWORK",
"authentication": "NONE",
"availabilityImpact": "COMPLETE",
"baseScore": 7.1,
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"vectorString": "AV:N/AC:M/Au:N/C:N/I:N/A:C",
"version": "2.0"
},
"exploitabilityScore": 8.6,
"impactScore": 6.9,
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"source": "nvd@nist.gov",
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"published": "2015-04-13T14:59:15.367",
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"weaknesses": [
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"value": "CWE-399"
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"source": "nvd@nist.gov",
"type": "Primary"
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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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