FKIE_CVE-2022-39398
Vulnerability from fkie_nvd - Published: 2022-11-10 01:15 - Updated: 2026-06-17 04:58
Severity
8.8 (High) - CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:L/A:L
6.1 (Medium) - CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:L/I:L/A:N
6.1 (Medium) - CVSS:3.1/
Summary
tasklists is a tasklists plugin for GLPI (Kanban). Versions prior to 2.0.3 are vulnerable to Cross-site Scripting. Cross-site Scripting (XSS) - Create XSS in task content (when add it). This issue is patched in version 2.0.3. There are no known workarounds.
References
{
"affected": [
{
"affectedData": [
{
"product": "tasklists",
"vendor": "InfotelGLPI",
"versions": [
{
"status": "affected",
"version": "\u003c 2.0.3"
}
]
}
],
"source": "security-advisories@github.com"
}
],
"configurations": [
{
"nodes": [
{
"cpeMatch": [
{
"criteria": "cpe:2.3:a:infotel:tasklists:*:*:*:*:*:glpi:*:*",
"matchCriteriaId": "643B1E15-7E4D-4DC2-B883-10285972F414",
"versionEndExcluding": "2.0.3",
"vulnerable": true
}
],
"negate": false,
"operator": "OR"
}
]
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "tasklists is a tasklists plugin for GLPI (Kanban). Versions prior to 2.0.3 are vulnerable to Cross-site Scripting. Cross-site Scripting (XSS) - Create XSS in task content (when add it). This issue is patched in version 2.0.3. There are no known workarounds."
},
{
"lang": "es",
"value": "Tasklists es un complemento de listas de tareas para GLPI (Kanban). Las versiones anteriores a la 2.0.3 son vulnerables a Cross-Site Scripting. Cross-Site Scripting (XSS): Crea XSS en el contenido de la tarea (al agregarlo). Este problema se solucion\u00f3 en la versi\u00f3n 2.0.3. No se conocen workarounds."
}
],
"id": "CVE-2022-39398",
"lastModified": "2026-06-17T04:58:16.923",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "LOW",
"baseScore": 8.8,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "LOW",
"privilegesRequired": "NONE",
"scope": "CHANGED",
"userInteraction": "REQUIRED",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:L/A:L",
"version": "3.1"
},
"exploitabilityScore": 2.8,
"impactScore": 5.3,
"source": "security-advisories@github.com",
"type": "Secondary"
},
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "NONE",
"baseScore": 6.1,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "LOW",
"integrityImpact": "LOW",
"privilegesRequired": "NONE",
"scope": "CHANGED",
"userInteraction": "REQUIRED",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:L/I:L/A:N",
"version": "3.1"
},
"exploitabilityScore": 2.8,
"impactScore": 2.7,
"source": "nvd@nist.gov",
"type": "Primary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2022-39398",
"options": [
{
"exploitation": "none"
},
{
"automatable": "no"
},
{
"technicalImpact": "partial"
}
],
"role": "CISA Coordinator",
"timestamp": "2025-04-23T13:54:54.931644Z",
"version": "2.0.3"
}
}
]
},
"published": "2022-11-10T01:15:12.333",
"references": [
{
"source": "security-advisories@github.com",
"tags": [
"Patch",
"Third Party Advisory"
],
"url": "https://github.com/InfotelGLPI/tasklists/commit/4a1b30f3d9fa764695f98ce011c8542772530d47"
},
{
"source": "security-advisories@github.com",
"tags": [
"Third Party Advisory"
],
"url": "https://github.com/InfotelGLPI/tasklists/security/advisories/GHSA-3qv3-8393-777q"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
"Patch",
"Third Party Advisory"
],
"url": "https://github.com/InfotelGLPI/tasklists/commit/4a1b30f3d9fa764695f98ce011c8542772530d47"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
"Third Party Advisory"
],
"url": "https://github.com/InfotelGLPI/tasklists/security/advisories/GHSA-3qv3-8393-777q"
}
],
"sourceIdentifier": "security-advisories@github.com",
"vulnStatus": "Modified",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-79"
}
],
"source": "security-advisories@github.com",
"type": "Secondary"
},
{
"description": [
{
"lang": "en",
"value": "CWE-79"
}
],
"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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