CVE-2026-14293 (GCVE-0-2026-14293)
Vulnerability from cvelistv5 – Published: 2026-08-10 06:00 – Updated: 2026-08-11 14:57
VLAI
EPSS
VEX
Title
Autopay / Blue Media for WooCommerce < 5.0.1 - Unauthenticated Stored XSS via CSS Editor
Summary
The Autopay WordPress plugin before 5.0.1 does not perform any capability or nonce check before saving a styling option from a public request, and does not escape that value when it is later output on the checkout page, allowing unauthenticated attackers to store JavaScript that executes in the browser of any user, including administrators, who loads the checkout page.
Severity
8.8 (High)
SSVC
Exploitation: none
Automatable: no
Technical Impact: total
CISA Coordinator (v2.0.3)
CWE
- CWE-79 Cross-Site Scripting (XSS)
- CWE-79 - Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')
Assigner
References
1 reference
| URL | Tags |
|---|---|
| https://wpscan.com/vulnerability/99fa208c-1a6f-43… | exploitvdb-entrytechnical-description |
Credits
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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.
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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