FKIE_CVE-2026-17577
Vulnerability from fkie_nvd - Published: 2026-09-25 08:16 - Updated: 2026-09-25 13:08
Severity
Summary
The SSL Zen plugin for WordPress is vulnerable to Reflected Cross-Site Scripting via the 'uri' (and 'host') parameters in versions up to, and including, 4.7.42. The ssl_zen_messages::getMessages() function builds the 'token_missmatch' message using base64_decode(sanitize_text_field($_REQUEST['uri'])) and (optionally) base64_decode(sanitize_text_field($_REQUEST['host'])). sanitize_text_field() cannot strip HTML/JavaScript that is hidden inside a base64-encoded blob, and the resulting decoded raw HTML is echoed unescaped by showMessage() . This makes it possible for unauthenticated attackers to inject arbitrary web scripts in pages that execute if they can successfully trick a user into performing an action such as clicking on a specially crafted link.
References
Impacted products
| Vendor | Product | Version |
|---|
{
"affected": [
{
"affectedData": [
{
"defaultStatus": "unaffected",
"product": "SSL Zen \u2014 SSL Certificate Installer \u0026 HTTPS Redirects",
"vendor": "sslzen",
"versions": [
{
"lessThanOrEqual": "4.7.42",
"status": "affected",
"version": "0",
"versionType": "semver"
}
]
}
],
"source": "security@wordfence.com"
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "The SSL Zen plugin for WordPress is vulnerable to Reflected Cross-Site Scripting via the \u0027uri\u0027 (and \u0027host\u0027) parameters in versions up to, and including, 4.7.42. The ssl_zen_messages::getMessages() function builds the \u0027token_missmatch\u0027 message using base64_decode(sanitize_text_field($_REQUEST[\u0027uri\u0027])) and (optionally) base64_decode(sanitize_text_field($_REQUEST[\u0027host\u0027])). sanitize_text_field() cannot strip HTML/JavaScript that is hidden inside a base64-encoded blob, and the resulting decoded raw HTML is echoed unescaped by showMessage() . This makes it possible for unauthenticated attackers to inject arbitrary web scripts in pages that execute if they can successfully trick a user into performing an action such as clicking on a specially crafted link."
}
],
"id": "CVE-2026-17577",
"lastModified": "2026-09-25T13:08:08.163",
"metrics": {
"cvssMetricV31": [
{
"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": "security@wordfence.com",
"type": "Secondary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2026-17577",
"options": [
{
"exploitation": "none"
},
{
"automatable": "no"
},
{
"technicalImpact": "partial"
}
],
"role": "CISA Coordinator",
"timestamp": "2026-09-25T10:31:30.444491Z",
"version": "2.0.3"
}
}
]
},
"published": "2026-09-25T08:16:40.103",
"references": [
{
"source": "security@wordfence.com",
"url": "https://plugins.trac.wordpress.org/browser/ssl-zen/tags/4.7.14/ssl_zen/classes/class.ssl_zen_admin.php#L863"
},
{
"source": "security@wordfence.com",
"url": "https://plugins.trac.wordpress.org/browser/ssl-zen/tags/4.7.14/ssl_zen/classes/class.ssl_zen_messages.php#L44"
},
{
"source": "security@wordfence.com",
"url": "https://plugins.trac.wordpress.org/browser/ssl-zen/tags/4.7.42/ssl_zen/classes/class.ssl_zen_admin.php#L863"
},
{
"source": "security@wordfence.com",
"url": "https://plugins.trac.wordpress.org/browser/ssl-zen/tags/4.7.42/ssl_zen/classes/class.ssl_zen_messages.php#L44"
},
{
"source": "security@wordfence.com",
"url": "https://plugins.trac.wordpress.org/changeset?reponame=\u0026old=3701590%40ssl-zen\u0026new=3701590%40ssl-zen"
},
{
"source": "security@wordfence.com",
"url": "https://www.wordfence.com/threat-intel/vulnerabilities/id/20816039-0b1c-420a-b5f4-b5370d0331da?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.
- 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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