FKIE_CVE-2016-2533
Vulnerability from fkie_nvd - Published: 2016-04-13 16:59 - Updated: 2026-06-17 00:44
Severity
Summary
Buffer overflow in the ImagingPcdDecode function in PcdDecode.c in Pillow before 3.1.1 and Python Imaging Library (PIL) 1.1.7 and earlier allows remote attackers to cause a denial of service (crash) via a crafted PhotoCD file.
References
Impacted products
| Vendor | Product | Version | |
|---|---|---|---|
| python | pillow | * | |
| python_imaging_project | python_imaging | * | |
| debian | debian_linux | 7.0 | |
| debian | debian_linux | 8.0 |
{
"affected": [
{
"affectedData": [
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"product": "n/a",
"vendor": "n/a",
"versions": [
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"status": "affected",
"version": "n/a"
}
]
}
],
"source": "cve@mitre.org"
}
],
"configurations": [
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"matchCriteriaId": "2F573E4A-55AB-4868-8CA1-7C7E5EEAC905",
"versionEndIncluding": "3.1.0",
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"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "Buffer overflow in the ImagingPcdDecode function in PcdDecode.c in Pillow before 3.1.1 and Python Imaging Library (PIL) 1.1.7 and earlier allows remote attackers to cause a denial of service (crash) via a crafted PhotoCD file."
},
{
"lang": "es",
"value": "Desbordamiento de buffer en la funci\u00f3n ImagengPcdDecode en PcdDecode.c en Pillow en versiones anteriores a 3.1.1 y Python Imageng Library (PIL) 1.1.7 y versiones anteriores permite a atacantes remotos provocar una denegaci\u00f3n de servicio (ca\u00edda) a trav\u00e9s de un archivo PhotoCD manipulado."
}
],
"id": "CVE-2016-2533",
"lastModified": "2026-06-17T00:44:14.590",
"metrics": {
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"version": "2.0"
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"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
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"integrityImpact": "NONE",
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"scope": "UNCHANGED",
"userInteraction": "REQUIRED",
"vectorString": "CVSS:3.0/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:H",
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"published": "2016-04-13T16:59:14.600",
"references": [
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"url": "http://www.debian.org/security/2016/dsa-3499"
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{
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"url": "https://security.gentoo.org/glsa/201612-52"
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"sourceIdentifier": "cve@mitre.org",
"vulnStatus": "Modified",
"weaknesses": [
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"description": [
{
"lang": "en",
"value": "CWE-119"
}
],
"source": "nvd@nist.gov",
"type": "Primary"
}
]
}
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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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