FKIE_CVE-2010-4652
Vulnerability from fkie_nvd - Published: 2011-02-02 01:00 - Updated: 2026-06-16 23:25
Severity
Summary
Heap-based buffer overflow in the sql_prepare_where function (contrib/mod_sql.c) in ProFTPD before 1.3.3d, when mod_sql is enabled, allows remote attackers to cause a denial of service (crash) and possibly execute arbitrary code via a crafted username containing substitution tags, which are not properly handled during construction of an SQL query.
References
Impacted products
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],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "Heap-based buffer overflow in the sql_prepare_where function (contrib/mod_sql.c) in ProFTPD before 1.3.3d, when mod_sql is enabled, allows remote attackers to cause a denial of service (crash) and possibly execute arbitrary code via a crafted username containing substitution tags, which are not properly handled during construction of an SQL query."
},
{
"lang": "es",
"value": "Desbordamiento de b\u00fafer en la memoria din\u00e1mica en la funci\u00f3n sql_prepare_where (contrib/mod_sql.c) en ProFTPD anterior a v1.3.3d, cuando mod_sql est\u00e1 habilitado, permite a atacantes remotos provocar una denegaci\u00f3n de servicio (ca\u00edda) y posiblemente ejecutar c\u00f3digo de su elecci\u00f3n a trav\u00e9s de un usuario manipulado que contiene etiquetas de sustituci\u00f3n, lo que no es sustituido adecuadamente durante la construcci\u00f3n de una consulta SQL"
}
],
"id": "CVE-2010-4652",
"lastModified": "2026-06-16T23:25:15.087",
"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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}
]
},
"published": "2011-02-02T01:00:04.533",
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"tags": [
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"vulnStatus": "Modified",
"weaknesses": [
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"value": "CWE-119"
}
],
"source": "nvd@nist.gov",
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}
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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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