FKIE_CVE-2026-4084
Vulnerability from fkie_nvd - Published: 2026-03-21 04:17 - Updated: 2026-06-17 10:55
Severity
Summary
The fyyd podcast shortcodes plugin for WordPress is vulnerable to Stored Cross-Site Scripting via the 'fyyd-podcast', 'fyyd-episode', and 'fyyd' shortcodes in all versions up to, and including, 0.3.1. This is due to insufficient input sanitization and output escaping on user-supplied shortcode attributes such as 'color', 'podcast_id', and 'podcast_slug'. These attributes are directly concatenated into inline JavaScript within single-quoted string arguments without any escaping or sanitization, allowing an attacker to break out of the JavaScript string context. This makes it possible for authenticated attackers, with Contributor-level access and above, to inject arbitrary web scripts in pages that will execute whenever a user accesses an injected page.
References
Impacted products
| Vendor | Product | Version |
|---|
{
"affected": [
{
"affectedData": [
{
"defaultStatus": "unaffected",
"product": "fyyd podcast shortcodes",
"vendor": "cbednarek",
"versions": [
{
"lessThanOrEqual": "0.3.1",
"status": "affected",
"version": "0",
"versionType": "semver"
}
]
}
],
"source": "security@wordfence.com"
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "The fyyd podcast shortcodes plugin for WordPress is vulnerable to Stored Cross-Site Scripting via the \u0027fyyd-podcast\u0027, \u0027fyyd-episode\u0027, and \u0027fyyd\u0027 shortcodes in all versions up to, and including, 0.3.1. This is due to insufficient input sanitization and output escaping on user-supplied shortcode attributes such as \u0027color\u0027, \u0027podcast_id\u0027, and \u0027podcast_slug\u0027. These attributes are directly concatenated into inline JavaScript within single-quoted string arguments without any escaping or sanitization, allowing an attacker to break out of the JavaScript string context. This makes it possible for authenticated attackers, with Contributor-level access and above, to inject arbitrary web scripts in pages that will execute whenever a user accesses an injected page."
},
{
"lang": "es",
"value": "El plugin de shortcodes fyyd podcast para WordPress es vulnerable a Cross-Site Scripting Almacenado a trav\u00e9s de los shortcodes \u0027fyyd-podcast\u0027, \u0027fyyd-episode\u0027 y \u0027fyyd\u0027 en todas las versiones hasta la 0.3.1, inclusive. Esto se debe a una sanitizaci\u00f3n de entrada y un escape de salida insuficientes en atributos de shortcode proporcionados por el usuario, como \u0027color\u0027, \u0027podcast_id\u0027 y \u0027podcast_slug\u0027. Estos atributos se concatenan directamente en JavaScript en l\u00ednea dentro de argumentos de cadena entre comillas simples sin ning\u00fan escape o sanitizaci\u00f3n, lo que permite a un atacante salir del contexto de cadena de JavaScript. Esto hace posible que atacantes autenticados, con acceso de nivel Colaborador y superior, inyecten scripts web arbitrarios en p\u00e1ginas que se ejecutar\u00e1n cada vez que un usuario acceda a una p\u00e1gina inyectada."
}
],
"id": "CVE-2026-4084",
"lastModified": "2026-06-17T10:55:57.993",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "NONE",
"baseScore": 6.4,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "LOW",
"integrityImpact": "LOW",
"privilegesRequired": "LOW",
"scope": "CHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:L/I:L/A:N",
"version": "3.1"
},
"exploitabilityScore": 3.1,
"impactScore": 2.7,
"source": "security@wordfence.com",
"type": "Secondary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2026-4084",
"options": [
{
"exploitation": "none"
},
{
"automatable": "no"
},
{
"technicalImpact": "partial"
}
],
"role": "CISA Coordinator",
"timestamp": "2026-03-23T17:23:28.606505Z",
"version": "2.0.3"
}
}
]
},
"published": "2026-03-21T04:17:40.810",
"references": [
{
"source": "security@wordfence.com",
"url": "https://plugins.trac.wordpress.org/browser/fyyd-podcast-shortcodes/tags/0.3.1/fyyd-podcast-shortcodes.php#L100"
},
{
"source": "security@wordfence.com",
"url": "https://plugins.trac.wordpress.org/browser/fyyd-podcast-shortcodes/tags/0.3.1/fyyd-podcast-shortcodes.php#L141"
},
{
"source": "security@wordfence.com",
"url": "https://plugins.trac.wordpress.org/browser/fyyd-podcast-shortcodes/tags/0.3.1/fyyd-podcast-shortcodes.php#L224"
},
{
"source": "security@wordfence.com",
"url": "https://plugins.trac.wordpress.org/browser/fyyd-podcast-shortcodes/tags/0.3.1/fyyd-podcast-shortcodes.php#L48"
},
{
"source": "security@wordfence.com",
"url": "https://plugins.trac.wordpress.org/browser/fyyd-podcast-shortcodes/tags/0.3.1/fyyd-podcast-shortcodes.php#L60"
},
{
"source": "security@wordfence.com",
"url": "https://plugins.trac.wordpress.org/browser/fyyd-podcast-shortcodes/tags/0.3.1/fyyd-podcast-shortcodes.php#L65"
},
{
"source": "security@wordfence.com",
"url": "https://plugins.trac.wordpress.org/browser/fyyd-podcast-shortcodes/trunk/fyyd-podcast-shortcodes.php#L100"
},
{
"source": "security@wordfence.com",
"url": "https://plugins.trac.wordpress.org/browser/fyyd-podcast-shortcodes/trunk/fyyd-podcast-shortcodes.php#L141"
},
{
"source": "security@wordfence.com",
"url": "https://plugins.trac.wordpress.org/browser/fyyd-podcast-shortcodes/trunk/fyyd-podcast-shortcodes.php#L224"
},
{
"source": "security@wordfence.com",
"url": "https://plugins.trac.wordpress.org/browser/fyyd-podcast-shortcodes/trunk/fyyd-podcast-shortcodes.php#L48"
},
{
"source": "security@wordfence.com",
"url": "https://plugins.trac.wordpress.org/browser/fyyd-podcast-shortcodes/trunk/fyyd-podcast-shortcodes.php#L60"
},
{
"source": "security@wordfence.com",
"url": "https://plugins.trac.wordpress.org/browser/fyyd-podcast-shortcodes/trunk/fyyd-podcast-shortcodes.php#L65"
},
{
"source": "security@wordfence.com",
"url": "https://www.wordfence.com/threat-intel/vulnerabilities/id/3f9d57ae-b238-43db-8eee-ccab499b1cbc?source=cve"
}
],
"sourceIdentifier": "security@wordfence.com",
"vulnStatus": "Deferred",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-79"
}
],
"source": "security@wordfence.com",
"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.
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- 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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