FKIE_CVE-2018-5800
Vulnerability from fkie_nvd - Published: 2018-12-07 22:29 - Updated: 2026-06-17 02:00
Severity
Summary
An off-by-one error within the "LibRaw::kodak_ycbcr_load_raw()" function (internal/dcraw_common.cpp) in LibRaw versions prior to 0.18.7 can be exploited to cause a heap-based buffer overflow and subsequently cause a crash.
References
Impacted products
| Vendor | Product | Version | |
|---|---|---|---|
| libraw | libraw | * | |
| redhat | enterprise_linux_desktop | 7.0 | |
| redhat | enterprise_linux_server | 7.0 | |
| redhat | enterprise_linux_workstation | 7.0 | |
| canonical | ubuntu_linux | 14.04 | |
| canonical | ubuntu_linux | 16.04 | |
| canonical | ubuntu_linux | 17.10 | |
| debian | debian_linux | 8.0 |
{
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{
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"product": "LibRaw",
"vendor": "n/a",
"versions": [
{
"status": "affected",
"version": "Prior to 0.18.7"
}
]
}
],
"source": "PSIRT-CNA@flexerasoftware.com"
}
],
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"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "An off-by-one error within the \"LibRaw::kodak_ycbcr_load_raw()\" function (internal/dcraw_common.cpp) in LibRaw versions prior to 0.18.7 can be exploited to cause a heap-based buffer overflow and subsequently cause a crash."
},
{
"lang": "es",
"value": "Un error por un paso relacionado con la funci\u00f3n \"LibRaw::kodak_ycbcr_load_raw()\" (internal/dcraw_common.cpp) en las versiones anteriores a la 0.18.7 de LibRaw puede explotarse para provocar un desbordamiento de b\u00fafer basado en memoria din\u00e1mica (heap) y un cierre inesperado."
}
],
"id": "CVE-2018-5800",
"lastModified": "2026-06-17T02:00:48.263",
"metrics": {
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{
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"baseSeverity": "MEDIUM",
"cvssData": {
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"accessVector": "NETWORK",
"authentication": "NONE",
"availabilityImpact": "PARTIAL",
"baseScore": 4.3,
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"vectorString": "AV:N/AC:M/Au:N/C:N/I:N/A:P",
"version": "2.0"
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"source": "nvd@nist.gov",
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"published": "2018-12-07T22:29:00.443",
"references": [
{
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"tags": [
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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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