FKIE_CVE-2022-39312
Vulnerability from fkie_nvd - Published: 2022-10-25 17:15 - Updated: 2026-06-17 04:58
Severity
9.8 (Critical) - CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
9.8 (Critical) - CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
9.8 (Critical) - CVSS:3.1/
Summary
Dataease is an open source data visualization analysis tool. Dataease prior to 1.15.2 has a deserialization vulnerability. In Dataease, the Mysql data source in the data source function can customize the JDBC connection parameters and the Mysql server target to be connected. In `backend/src/main/java/io/dataease/provider/datasource/JdbcProvider.java`, the `MysqlConfiguration` class does not filter any parameters. If an attacker adds some parameters to a JDBC url and connects to a malicious mysql server, the attacker can trigger the mysql jdbc deserialization vulnerability. Through the deserialization vulnerability, the attacker can execute system commands and obtain server privileges. Version 1.15.2 contains a patch for this issue.
References
{
"affected": [
{
"affectedData": [
{
"product": "dataease",
"vendor": "dataease",
"versions": [
{
"status": "affected",
"version": "\u003c 1.15.2"
}
]
}
],
"source": "security-advisories@github.com"
}
],
"configurations": [
{
"nodes": [
{
"cpeMatch": [
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"criteria": "cpe:2.3:a:dataease:dataease:*:*:*:*:*:*:*:*",
"matchCriteriaId": "118D387C-8D54-4649-B3A9-CD4DE706B423",
"versionEndExcluding": "1.15.2",
"vulnerable": true
}
],
"negate": false,
"operator": "OR"
}
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],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "Dataease is an open source data visualization analysis tool. Dataease prior to 1.15.2 has a deserialization vulnerability. In Dataease, the Mysql data source in the data source function can customize the JDBC connection parameters and the Mysql server target to be connected. In `backend/src/main/java/io/dataease/provider/datasource/JdbcProvider.java`, the `MysqlConfiguration` class does not filter any parameters. If an attacker adds some parameters to a JDBC url and connects to a malicious mysql server, the attacker can trigger the mysql jdbc deserialization vulnerability. Through the deserialization vulnerability, the attacker can execute system commands and obtain server privileges. Version 1.15.2 contains a patch for this issue."
},
{
"lang": "es",
"value": "Dataease es una herramienta de an\u00e1lisis de visualizaci\u00f3n de datos de c\u00f3digo abierto. Dataease versiones anteriores a 1.15.2, presenta una vulnerabilidad de deserializaci\u00f3n. En Dataease, la fuente de datos Mysql en la funci\u00f3n de fuente de datos puede personalizar los par\u00e1metros de conexi\u00f3n JDBC y el objetivo del servidor Mysql a conectar. En \"backend/src/main/java/io/dataease/provider/datasource/JdbcProvider.java\", la clase \"MysqlConfiguration\" no filtra ning\u00fan par\u00e1metro. Si un atacante a\u00f1ade algunos par\u00e1metros a una url JDBC y es conectado a un servidor mysql malicioso, el atacante puede desencadenar una vulnerabilidad de deserializaci\u00f3n mysql jdbc. Mediante una vulnerabilidad de deserializaci\u00f3n, el atacante puede ejecutar comandos del sistema y obtener privilegios del servidor. La versi\u00f3n 1.15.2 contiene un parche para este problema"
}
],
"id": "CVE-2022-39312",
"lastModified": "2026-06-17T04:58:07.373",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
"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,
"source": "security-advisories@github.com",
"type": "Secondary"
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{
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"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,
"source": "nvd@nist.gov",
"type": "Primary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2022-39312",
"options": [
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"exploitation": "poc"
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{
"automatable": "yes"
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{
"technicalImpact": "total"
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],
"role": "CISA Coordinator",
"timestamp": "2025-04-22T15:36:45.636359Z",
"version": "2.0.3"
}
}
]
},
"published": "2022-10-25T17:15:55.813",
"references": [
{
"source": "security-advisories@github.com",
"tags": [
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"Third Party Advisory"
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"url": "https://github.com/dataease/dataease/commit/956ee2d6c9e81349a60aef435efc046888e10a6d"
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"source": "security-advisories@github.com",
"tags": [
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{
"source": "security-advisories@github.com",
"tags": [
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"url": "https://github.com/dataease/dataease/releases/tag/v1.15.2"
},
{
"source": "security-advisories@github.com",
"tags": [
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"url": "https://github.com/dataease/dataease/security/advisories/GHSA-q4qq-jhjv-7rh2"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
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"url": "https://github.com/dataease/dataease/commit/956ee2d6c9e81349a60aef435efc046888e10a6d"
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{
"source": "af854a3a-2127-422b-91ae-364da2661108",
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"url": "https://github.com/dataease/dataease/pull/3328"
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{
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"tags": [
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{
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"tags": [
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"url": "https://github.com/dataease/dataease/security/advisories/GHSA-q4qq-jhjv-7rh2"
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"sourceIdentifier": "security-advisories@github.com",
"vulnStatus": "Modified",
"weaknesses": [
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"lang": "en",
"value": "CWE-20"
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{
"lang": "en",
"value": "CWE-502"
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],
"source": "security-advisories@github.com",
"type": "Secondary"
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{
"description": [
{
"lang": "en",
"value": "CWE-502"
}
],
"source": "nvd@nist.gov",
"type": "Primary"
}
]
}
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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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