FKIE_CVE-2024-5483
Vulnerability from fkie_nvd - Published: 2024-06-05 03:15 - Updated: 2026-06-17 08:16
Severity
Summary
The LearnPress – WordPress LMS Plugin plugin for WordPress is vulnerable to Sensitive Information Exposure in all versions up to, and including, 4.2.6.8 due to incorrect implementation of get_items_permissions_check function. This makes it possible for unauthenticated attackers to extract basic information about website users, including their emails
References
Impacted products
| Vendor | Product | Version | |
|---|---|---|---|
| thimpress | learnpress | * |
{
"affected": [
{
"affectedData": [
{
"defaultStatus": "unaffected",
"product": "LearnPress \u2013 WordPress LMS Plugin for Create and Sell Online Courses",
"vendor": "thimpress",
"versions": [
{
"lessThanOrEqual": "4.2.6.8",
"status": "affected",
"version": "0",
"versionType": "semver"
}
]
}
],
"source": "security@wordfence.com"
}
],
"configurations": [
{
"nodes": [
{
"cpeMatch": [
{
"criteria": "cpe:2.3:a:thimpress:learnpress:*:*:*:*:*:wordpress:*:*",
"matchCriteriaId": "75ACBE4E-FBE4-4AE6-94DA-C24DD3F48F07",
"versionEndExcluding": "4.2.6.8.1",
"vulnerable": true
}
],
"negate": false,
"operator": "OR"
}
]
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "The LearnPress \u2013 WordPress LMS Plugin plugin for WordPress is vulnerable to Sensitive Information Exposure in all versions up to, and including, 4.2.6.8 due to incorrect implementation of get_items_permissions_check function. This makes it possible for unauthenticated attackers to extract basic information about website users, including their emails"
},
{
"lang": "es",
"value": "El complemento LearnPress \u2013 WordPress LMS Plugin para WordPress es vulnerable a la exposici\u00f3n de informaci\u00f3n confidencial en todas las versiones hasta la 4.2.6.8 incluida debido a la implementaci\u00f3n incorrecta de la funci\u00f3n get_items_permissions_check. Esto hace posible que atacantes no autenticados extraigan informaci\u00f3n b\u00e1sica sobre los usuarios del sitio web, incluidos sus correos electr\u00f3nicos."
}
],
"id": "CVE-2024-5483",
"lastModified": "2026-06-17T08:16:02.233",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "NONE",
"baseScore": 5.3,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "LOW",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N",
"version": "3.1"
},
"exploitabilityScore": 3.9,
"impactScore": 1.4,
"source": "security@wordfence.com",
"type": "Secondary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2024-5483",
"options": [
{
"exploitation": "none"
},
{
"automatable": "no"
},
{
"technicalImpact": "partial"
}
],
"role": "CISA Coordinator",
"timestamp": "2024-06-05T14:22:11.106594Z",
"version": "2.0.3"
}
}
]
},
"published": "2024-06-05T03:15:08.810",
"references": [
{
"source": "security@wordfence.com",
"tags": [
"Product"
],
"url": "https://plugins.trac.wordpress.org/browser/learnpress/tags/4.2.6.8/inc/jwt/rest-api/version1/class-lp-rest-users-v1-controller.php#L130"
},
{
"source": "security@wordfence.com",
"tags": [
"Third Party Advisory"
],
"url": "https://www.wordfence.com/threat-intel/vulnerabilities/id/122b75d2-e882-45b9-baf1-acf847f8d60a?source=cve"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
"Product"
],
"url": "https://plugins.trac.wordpress.org/browser/learnpress/tags/4.2.6.8/inc/jwt/rest-api/version1/class-lp-rest-users-v1-controller.php#L130"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
"Third Party Advisory"
],
"url": "https://www.wordfence.com/threat-intel/vulnerabilities/id/122b75d2-e882-45b9-baf1-acf847f8d60a?source=cve"
}
],
"sourceIdentifier": "security@wordfence.com",
"vulnStatus": "Modified",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-200"
}
],
"source": "security@wordfence.com",
"type": "Secondary"
},
{
"description": [
{
"lang": "en",
"value": "NVD-CWE-noinfo"
}
],
"source": "nvd@nist.gov",
"type": "Secondary"
}
]
}
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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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