FKIE_CVE-2010-0129
Vulnerability from fkie_nvd - Published: 2010-05-13 17:30 - Updated: 2026-06-16 23:15
Severity
Summary
Multiple integer overflows in Adobe Shockwave Player before 11.5.7.609 allow remote attackers to cause a denial of service (memory corruption) or possibly execute arbitrary code via a crafted .dir (aka Director) file that triggers an array index error.
References
{
"affected": [
{
"affectedData": [
{
"product": "n/a",
"vendor": "n/a",
"versions": [
{
"status": "affected",
"version": "n/a"
}
]
}
],
"source": "PSIRT-CNA@flexerasoftware.com"
}
],
"configurations": [
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"descriptions": [
{
"lang": "en",
"value": "Multiple integer overflows in Adobe Shockwave Player before 11.5.7.609 allow remote attackers to cause a denial of service (memory corruption) or possibly execute arbitrary code via a crafted .dir (aka Director) file that triggers an array index error."
},
{
"lang": "es",
"value": "M\u00faltiples desbordamientos de enteros en Adobe Shockwave Player en versiones anteriores a la 11.5.7.609 permite a atacantes remotos provocar una denegaci\u00f3n de servicio (corrupci\u00f3n de memoria) o posiblemente ejecutar c\u00f3digo de su elecci\u00f3n mediante un fichero .dir (tambi\u00e9n conocido como Director) manipulado que dispara un error de indice de matriz."
}
],
"evaluatorSolution": "Per: http://www.adobe.com/support/security/bulletins/apsb10-12.html\r\n\r\n\u0027Adobe recommends users of Adobe Shockwave Player 11.5.6.606 and earlier versions update to Adobe Shockwave Player 11.5.7.609\u0027",
"id": "CVE-2010-0129",
"lastModified": "2026-06-16T23:15:32.033",
"metrics": {
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"baseSeverity": "HIGH",
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"accessVector": "NETWORK",
"authentication": "NONE",
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"baseScore": 9.3,
"confidentialityImpact": "COMPLETE",
"integrityImpact": "COMPLETE",
"vectorString": "AV:N/AC:M/Au:N/C:C/I:C/A:C",
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"obtainAllPrivilege": false,
"obtainOtherPrivilege": false,
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"published": "2010-05-13T17:30:01.827",
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"tags": [
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"sourceIdentifier": "PSIRT-CNA@flexerasoftware.com",
"vulnStatus": "Modified",
"weaknesses": [
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"lang": "en",
"value": "CWE-190"
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"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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