GSD-2022-2807
Vulnerability from gsd - Updated: 2023-12-13 01:19Details
SQL Injection vulnerability in Algan Software Prens Student Information System allows SQL Injection.This issue affects Prens Student Information System: before 2.1.11.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2022-2807",
"description": "Algan Yaz\u0131l\u0131m Prens Student Information System product has an unauthenticated SQL Injection vulnerability.",
"id": "GSD-2022-2807"
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
"osvSchema": {
"aliases": [
"CVE-2022-2807"
],
"details": "SQL Injection vulnerability in Algan Software Prens Student Information System allows SQL Injection.This issue affects Prens Student Information System: before 2.1.11.\n\n",
"id": "GSD-2022-2807",
"modified": "2023-12-13T01:19:19.765362Z",
"schema_version": "1.4.0"
}
},
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},
"affects": {
"vendor": {
"vendor_data": [
{
"product": {
"product_data": [
{
"product_name": "Prens Student Information System",
"version": {
"version_data": [
{
"version_affected": "\u003c",
"version_name": "0",
"version_value": "2.1.11"
}
]
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}
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}
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"generator": {
"engine": "Vulnogram 0.0.9"
},
"impact": {
"cvss": [
{
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 9.8,
"baseSeverity": "CRITICAL",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
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}
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"problemtype": {
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"description": [
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"cweId": "CWE-89",
"lang": "eng",
"value": "CWE-89 Improper Neutralization of Special Elements used in an SQL Command (\u0027SQL Injection\u0027)"
}
]
}
]
},
"references": {
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"name": "https://www.usom.gov.tr/bildirim/tr-22-0708",
"refsource": "MISC",
"url": "https://www.usom.gov.tr/bildirim/tr-22-0708"
}
]
},
"solution": [
{
"lang": "en",
"supportingMedia": [
{
"base64": false,
"type": "text/html",
"value": "\u003cp\u003e\n\nAlgan Software Prens Student Information System should be updated to \u0026gt;= 2.1.11.\n\n\u003c/p\u003e"
}
],
"value": "\nAlgan Software Prens Student Information System should be updated to \u003e= 2.1.11.\n\n\n\n"
}
],
"source": {
"advisory": "TR-22-0708",
"defect": [
"TR-22-0708"
],
"discovery": "EXTERNAL"
}
},
"nvd.nist.gov": {
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"nodes": [
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"cpe_match": [
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"cpe23Uri": "cpe:2.3:a:algan:prens_student_information_system:*:*:*:*:*:*:*:*",
"cpe_name": [],
"versionEndExcluding": "2.1.11",
"vulnerable": true
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"operator": "OR"
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"ID": "CVE-2022-2807"
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"description": {
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"value": "SQL Injection vulnerability in Algan Software Prens Student Information System allows SQL Injection.This issue affects Prens Student Information System: before 2.1.11.\n\n"
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"problemtype": {
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"tags": [
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"url": "https://www.usom.gov.tr/bildirim/tr-22-0708"
}
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}
},
"impact": {
"baseMetricV3": {
"cvssV3": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 9.8,
"baseSeverity": "CRITICAL",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
"version": "3.1"
},
"exploitabilityScore": 3.9,
"impactScore": 5.9
}
},
"lastModifiedDate": "2023-04-16T10:15Z",
"publishedDate": "2022-12-02T12:15Z"
}
}
}
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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.
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- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
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- 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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