FKIE_CVE-2015-10139
Vulnerability from fkie_nvd - Published: 2025-07-19 12:15 - Updated: 2026-06-17 00:21
Severity
Summary
The WPLMS theme for WordPress is vulnerable to Privilege Escalation in versions 1.5.2 to 1.8.4.1 via the 'wp_ajax_import_data' AJAX action. This makes it possible for authenticated attackers to change otherwise restricted settings and potentially create a new accessible admin account.
References
Impacted products
| Vendor | Product | Version | |
|---|---|---|---|
| vibethemes | wordpress_learning_management_system_ | * |
{
"affected": [
{
"affectedData": [
{
"defaultStatus": "unaffected",
"product": "WPLMS Learning Management System for WordPress, WordPress LMS",
"vendor": "VibeThemes",
"versions": [
{
"lessThanOrEqual": "1.8.4.1",
"status": "affected",
"version": "0",
"versionType": "semver"
}
]
}
],
"source": "security@wordfence.com"
}
],
"configurations": [
{
"nodes": [
{
"cpeMatch": [
{
"criteria": "cpe:2.3:a:vibethemes:wordpress_learning_management_system_:*:*:*:*:*:wordpress:*:*",
"matchCriteriaId": "FB4FCAB0-E172-4C37-AC2B-385A31B83462",
"versionEndExcluding": "1.8.9",
"versionStartIncluding": "1.5.2",
"vulnerable": true
}
],
"negate": false,
"operator": "OR"
}
]
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "The WPLMS theme for WordPress is vulnerable to Privilege Escalation in versions 1.5.2 to 1.8.4.1 via the \u0027wp_ajax_import_data\u0027 AJAX action. This makes it possible for authenticated attackers to change otherwise restricted settings and potentially create a new accessible admin account."
},
{
"lang": "es",
"value": "El tema WPLMS para WordPress es vulnerable a la escalada de privilegios en las versiones 1.5.2 a 1.8.4.1 mediante la acci\u00f3n AJAX \u0027wp_ajax_import_data\u0027. Esto permite a atacantes autenticados modificar configuraciones que de otro modo estar\u00edan restringidas y, potencialmente, crear una nueva cuenta de administrador accesible."
}
],
"id": "CVE-2015-10139",
"lastModified": "2026-06-17T00:21:35.877",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 8.8,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "LOW",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
"version": "3.1"
},
"exploitabilityScore": 2.8,
"impactScore": 5.9,
"source": "security@wordfence.com",
"type": "Secondary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2015-10139",
"options": [
{
"exploitation": "none"
},
{
"automatable": "no"
},
{
"technicalImpact": "partial"
}
],
"role": "CISA Coordinator",
"timestamp": "2025-07-21T15:41:14.341909Z",
"version": "2.0.3"
}
}
]
},
"published": "2025-07-19T12:15:35.127",
"references": [
{
"source": "security@wordfence.com",
"tags": [
"Exploit",
"Third Party Advisory"
],
"url": "https://packetstormsecurity.com/files/130291/"
},
{
"source": "security@wordfence.com",
"tags": [
"Product"
],
"url": "https://themeforest.net/item/wplms-learning-management-system/6780226"
},
{
"source": "security@wordfence.com",
"tags": [
"Broken Link"
],
"url": "https://twitter.com/_wpscan_/status/564874637679820800?lang=ca"
},
{
"source": "security@wordfence.com",
"tags": [
"Broken Link"
],
"url": "https://wpscan.com/vulnerability/7785"
},
{
"source": "security@wordfence.com",
"tags": [
"Third Party Advisory"
],
"url": "https://www.rapid7.com/db/modules/auxiliary/admin/http/wp_wplms_privilege_escalation/"
},
{
"source": "security@wordfence.com",
"tags": [
"Third Party Advisory"
],
"url": "https://www.wordfence.com/threat-intel/vulnerabilities/id/6e0e8f5f-8216-4276-a810-860f9b52c447?source=cve"
}
],
"sourceIdentifier": "security@wordfence.com",
"vulnStatus": "Analyzed",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-269"
}
],
"source": "security@wordfence.com",
"type": "Secondary"
},
{
"description": [
{
"lang": "en",
"value": "NVD-CWE-noinfo"
}
],
"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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