GSD-2022-4093
Vulnerability from gsd - Updated: 2023-12-13 01:19Details
SQL injection attacks can result in unauthorized access to sensitive data, such as passwords, credit card details, or personal user information. Many high-profile data breaches in recent years have been the result of SQL injection attacks, leading to reputational damage and regulatory fines. In some cases, an attacker can obtain a persistent backdoor into an organization's systems, leading to a long-term compromise that can go unnoticed for an extended period. This affect 16.0.1 and 16.0.2 only. 16.0.0 or lower, and 16.0.3 or higher are not affected
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2022-4093",
"description": "SQL injection attacks can result in unauthorized access to sensitive data, such as passwords, credit card details, or personal user information. Many high-profile data breaches in recent years have been the result of SQL injection attacks, leading to reputational damage and regulatory fines. In some cases, an attacker can obtain a persistent backdoor into an organization\u0027s systems, leading to a long-term compromise that can go unnoticed for an extended period. This affect 16.0.1 and 16.0.2 only. 16.0.0 or lower, and 16.0.3 or higher are not affected",
"id": "GSD-2022-4093"
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
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"id": "GSD-2022-4093",
"modified": "2023-12-13T01:19:15.848101Z",
"schema_version": "1.4.0"
}
},
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"ID": "CVE-2022-4093",
"STATE": "PUBLIC",
"TITLE": " SQL Injection in dolibarr/dolibarr"
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"affects": {
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"value": "SQL injection attacks can result in unauthorized access to sensitive data, such as passwords, credit card details, or personal user information. Many high-profile data breaches in recent years have been the result of SQL injection attacks, leading to reputational damage and regulatory fines. In some cases, an attacker can obtain a persistent backdoor into an organization\u0027s systems, leading to a long-term compromise that can go unnoticed for an extended period. This affect 16.0.1 and 16.0.2 only. 16.0.0 or lower, and 16.0.3 or higher are not affected"
}
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"impact": {
"cvss": {
"attackComplexity": "HIGH",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 8.1,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.0/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:H",
"version": "3.0"
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"value": "CWE-89 Improper Neutralization of Special Elements used in an SQL Command"
}
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"url": "https://huntr.dev/bounties/677ca8ee-ffbc-4b39-b294-2ce81bd56788"
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"name": "https://github.com/dolibarr/dolibarr/commit/7c1eac9774bd1fed0b7b4594159f2ac2d12a4011",
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"advisories": [
{
"affected_range": "\u003e=16.0.1,\u003c=16.0.2",
"affected_versions": "All versions starting from 16.0.1 up to 16.0.2",
"cvss_v3": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
"cwe_ids": [
"CWE-1035",
"CWE-89",
"CWE-937"
],
"date": "2022-11-23",
"description": "SQL injection attacks can result in unauthorized access to sensitive data, such as passwords, credit card details, or personal user information. Many high-profile data breaches in recent years have been the result of SQL injection attacks, leading to reputational damage and regulatory fines. In some cases, an attacker can obtain a persistent backdoor into an organization\u0027s systems, leading to a long-term compromise that can go unnoticed for an extended period. This affect 16.0.1 and 16.0.2 only. 16.0.0 or lower, and 16.0.3 or higher are not affected",
"fixed_versions": [],
"identifier": "CVE-2022-4093",
"identifiers": [
"CVE-2022-4093",
"GHSA-gjg7-qfvp-9hm4"
],
"not_impacted": "",
"package_slug": "packagist/dolibarr/dolibarr",
"pubdate": "2022-11-21",
"solution": "Unfortunately, there is no solution available yet.",
"title": "SQL injection in Dolibarr",
"urls": [
"https://nvd.nist.gov/vuln/detail/CVE-2022-4093",
"https://github.com/dolibarr/dolibarr/commit/7c1eac9774bd1fed0b7b4594159f2ac2d12a4011",
"https://huntr.dev/bounties/677ca8ee-ffbc-4b39-b294-2ce81bd56788",
"https://github.com/advisories/GHSA-gjg7-qfvp-9hm4"
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"uuid": "bf1894a1-0cef-4509-a838-bc3a5128a20b"
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"name": "https://github.com/dolibarr/dolibarr/commit/7c1eac9774bd1fed0b7b4594159f2ac2d12a4011",
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"impact": {
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"attackVector": "NETWORK",
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"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"
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"exploitabilityScore": 3.9,
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}
},
"lastModifiedDate": "2022-11-23T14:15Z",
"publishedDate": "2022-11-21T05:15Z"
}
}
}
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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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