FKIE_CVE-2019-6977
Vulnerability from fkie_nvd - Published: 2019-01-27 02:29 - Updated: 2026-06-17 02:39
Severity
Summary
gdImageColorMatch in gd_color_match.c in the GD Graphics Library (aka LibGD) 2.2.5, as used in the imagecolormatch function in PHP before 5.6.40, 7.x before 7.1.26, 7.2.x before 7.2.14, and 7.3.x before 7.3.1, has a heap-based buffer overflow. This can be exploited by an attacker who is able to trigger imagecolormatch calls with crafted image data.
References
Impacted products
| Vendor | Product | Version | |
|---|---|---|---|
| libgd | libgd | 2.2.5 | |
| php | php | * | |
| php | php | * | |
| php | php | * | |
| php | php | 7.3.0 | |
| debian | debian_linux | 8.0 | |
| debian | debian_linux | 9.0 | |
| canonical | ubuntu_linux | 14.04 | |
| canonical | ubuntu_linux | 16.04 | |
| canonical | ubuntu_linux | 18.04 | |
| canonical | ubuntu_linux | 18.10 | |
| netapp | storage_automation_store | * |
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"cveTags": [],
"descriptions": [
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"lang": "en",
"value": "gdImageColorMatch in gd_color_match.c in the GD Graphics Library (aka LibGD) 2.2.5, as used in the imagecolormatch function in PHP before 5.6.40, 7.x before 7.1.26, 7.2.x before 7.2.14, and 7.3.x before 7.3.1, has a heap-based buffer overflow. This can be exploited by an attacker who is able to trigger imagecolormatch calls with crafted image data."
},
{
"lang": "es",
"value": "gdImageColorMatch in gd_color_match.c en la versi\u00f3n 2.2.5 de GD Graphics Library (tambi\u00e9n conocido como LibGD), tal y como se utiliza en la funci\u00f3n imagecolormatch en PHP, en versiones anteriores a la 5.6.40, en las 7.x anteriores a la 7.1.26, en las 7.2.x anteriores a la 7.2.14 y en las 7.3.x anteriores a la 7.3.1, tiene un desbordamiento de b\u00fafer basado en memoria din\u00e1mica (heap). Esto puede ser explotado por un atacante capaz de provocar llamadas imagecolormatch con datos de imagen manipulados."
}
],
"id": "CVE-2019-6977",
"lastModified": "2026-06-17T02:39:51.670",
"metrics": {
"cvssMetricV2": [
{
"acInsufInfo": false,
"baseSeverity": "MEDIUM",
"cvssData": {
"accessComplexity": "MEDIUM",
"accessVector": "NETWORK",
"authentication": "NONE",
"availabilityImpact": "PARTIAL",
"baseScore": 6.8,
"confidentialityImpact": "PARTIAL",
"integrityImpact": "PARTIAL",
"vectorString": "AV:N/AC:M/Au:N/C:P/I:P/A:P",
"version": "2.0"
},
"exploitabilityScore": 8.6,
"impactScore": 6.4,
"obtainAllPrivilege": false,
"obtainOtherPrivilege": false,
"obtainUserPrivilege": false,
"source": "nvd@nist.gov",
"type": "Primary",
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"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 8.8,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "REQUIRED",
"vectorString": "CVSS:3.0/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H",
"version": "3.0"
},
"exploitabilityScore": 2.8,
"impactScore": 5.9,
"source": "nvd@nist.gov",
"type": "Primary"
}
]
},
"published": "2019-01-27T02:29:00.340",
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"url": "http://lists.opensuse.org/opensuse-security-announce/2019-04/msg00025.html"
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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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