GSD-2023-4674
Vulnerability from gsd - Updated: 2023-12-13 01:20Details
Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection') vulnerability in Yaztek Software Technologies and Computer Systems E-Commerce Software allows SQL Injection.This issue affects E-Commerce Software: through 20231229.
NOTE: The vendor was contacted early about this disclosure but did not respond in any way.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2023-4674",
"id": "GSD-2023-4674"
},
"gsd": {
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"exploitCode": "unknown",
"remediation": "unknown",
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"details": "Improper Neutralization of Special Elements used in an SQL Command (\u0027SQL Injection\u0027) vulnerability in Yaztek Software Technologies and Computer Systems E-Commerce Software allows SQL Injection.This issue affects E-Commerce Software: through 20231229.\u00a0\n\nNOTE: The vendor was contacted early about this disclosure but did not respond in any way.\n\n\n\n",
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"modified": "2023-12-13T01:20:27.205498Z",
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"value": "Resul Melih MAC\u0130T"
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"impact": {
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"attackVector": "NETWORK",
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"baseScore": 9.8,
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"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
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"descriptions": [
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"lang": "en",
"value": "Improper Neutralization of Special Elements used in an SQL Command (\u0027SQL Injection\u0027) vulnerability in Yaztek Software Technologies and Computer Systems E-Commerce Software allows SQL Injection.This issue affects E-Commerce Software: through 20231229.\u00a0\n\nNOTE: The vendor was contacted early about this disclosure but did not respond in any way.\n\n\n\n"
},
{
"lang": "es",
"value": "Neutralizaci\u00f3n incorrecta de elementos especiales utilizados en una vulnerabilidad de comando SQL (\"Inyecci\u00f3n SQL\") en Yaztek Software Technologies and Computer Systems E-Commerce Software. El software de comercio electr\u00f3nico permite la inyecci\u00f3n de SQL. Este problema afecta a E-Commerce Software: hasta 20231229. NOTA: Se contact\u00f3 primeramente al proveedor sobre esta divulgaci\u00f3n, pero no respondi\u00f3 de nignuna forma."
}
],
"id": "CVE-2023-4674",
"lastModified": "2024-01-08T17:16:09.257",
"metrics": {
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"source": "iletisim@usom.gov.tr",
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"published": "2023-12-29T15:15:09.497",
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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.
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- 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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