FKIE_CVE-2024-13926
Vulnerability from fkie_nvd - Published: 2025-04-19 06:15 - Updated: 2026-06-17 07:03
Severity
Summary
The WP-Syntax WordPress plugin through 1.2 does not properly handle input, allowing an attacker to create a post containing a large number of tags, thereby exploiting a catastrophic backtracking issue in the regular expression processing to cause a DoS.
References
| URL | Tags | ||
|---|---|---|---|
| contact@wpscan.com | https://wpscan.com/vulnerability/b5f0092e-7cd5-412f-a8ea-7bd4a8bf86d2/ | Exploit, Third Party Advisory |
Impacted products
| Vendor | Product | Version | |
|---|---|---|---|
| connections-pro | wp-syntax | * |
{
"affected": [
{
"affectedData": [
{
"defaultStatus": "affected",
"product": "WP-Syntax",
"vendor": "Unknown",
"versions": [
{
"lessThanOrEqual": "1.2",
"status": "affected",
"version": "0",
"versionType": "semver"
}
]
}
],
"source": "contact@wpscan.com"
}
],
"configurations": [
{
"nodes": [
{
"cpeMatch": [
{
"criteria": "cpe:2.3:a:connections-pro:wp-syntax:*:*:*:*:*:wordpress:*:*",
"matchCriteriaId": "D38E570C-54B5-429F-8A99-E9267A7EB1F1",
"versionEndIncluding": "1.2",
"vulnerable": true
}
],
"negate": false,
"operator": "OR"
}
]
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "The WP-Syntax WordPress plugin through 1.2 does not properly handle input, allowing an attacker to create a post containing a large number of tags, thereby exploiting a catastrophic backtracking issue in the regular expression processing to cause a DoS."
},
{
"lang": "es",
"value": "El complemento WP-Syntax para WordPress hasta la versi\u00f3n 1.2 no gestiona adecuadamente la entrada, lo que permite que un atacante cree una publicaci\u00f3n que contenga una gran cantidad de etiquetas, explotando as\u00ed un problema de retroceso catastr\u00f3fico en el procesamiento de expresiones regulares para provocar un DoS."
}
],
"id": "CVE-2024-13926",
"lastModified": "2026-06-17T07:03:00.490",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 7.5,
"baseSeverity": "HIGH",
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"version": "3.1"
},
"exploitabilityScore": 3.9,
"impactScore": 3.6,
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"type": "Secondary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2024-13926",
"options": [
{
"exploitation": "poc"
},
{
"automatable": "yes"
},
{
"technicalImpact": "partial"
}
],
"role": "CISA Coordinator",
"timestamp": "2025-04-21T02:38:00.659019Z",
"version": "2.0.3"
}
}
]
},
"published": "2025-04-19T06:15:18.347",
"references": [
{
"source": "contact@wpscan.com",
"tags": [
"Exploit",
"Third Party Advisory"
],
"url": "https://wpscan.com/vulnerability/b5f0092e-7cd5-412f-a8ea-7bd4a8bf86d2/"
}
],
"sourceIdentifier": "contact@wpscan.com",
"vulnStatus": "Analyzed",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-1333"
}
],
"source": "nvd@nist.gov",
"type": "Primary"
}
]
}
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Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
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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.
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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.