CVE-2026-0950
Published: 03 February 2026
Summary
CVE-2026-0950 is a medium-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Wordpress (inferred from references). Its CVSS base score is 5.3 (Medium).
Operationally, ranked at the 33.4th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-5268
Vulnerability details
The Spectra Gutenberg Blocks – Website Builder for the Block Editor plugin for WordPress is vulnerable to Information Disclosure in all versions up to, and including, 2.19.17. This is due to the plugin failing to check `post_password_required()` before rendering post…
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excerpts in the `render_excerpt()` function and the `uagb_get_excerpt()` helper function. This makes it possible for unauthenticated attackers to read excerpts of password-protected posts by simply viewing any page that contains a Spectra Post Grid, Post Masonry, Post Carousel, or Post Timeline block.
- CWE(s)
Related Threats
No named actor attribution yet. ATT&CK technique mapping in progress for this CVE.
Affected Assets
Mitigating Controls
Likely Mitigating Controls AI
Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.
Automated marking applies security attributes to system outputs, making it harder for attackers to exploit unmarked sensitive information leading to unauthorized exposure.
Proper attribute retention and permitted-value enforcement limits unauthorized actors from accessing sensitive information lacking correct labels.
Prevents unauthorized exposure of sensitive information by prohibiting untrusted external systems from processing or storing it.
By enforcing authorization matching prior to sharing, the control reduces the risk of exposing sensitive information to unauthorized actors.
Review and removal of nonpublic information from publicly accessible systems directly prevents exposure of sensitive data to unauthorized actors.
Data mining protection mechanisms detect and block unauthorized bulk extraction of sensitive data, directly mitigating exposure to unauthorized actors.
Literacy training teaches users to recognize and avoid actions that result in unauthorized exposure of sensitive information.
Retaining and monitoring training records confirms personnel have completed privacy and security awareness training on handling sensitive data, reducing the chance of unauthorized exposure due to lack of knowledge.