CVE-2026-6075 (GCVE-0-2026-6075)
Vulnerability from cvelistv5 – Published: 2026-05-29 07:46 – Updated: 2026-05-29 10:05
VLAI
EPSS
VEX
Title
Media Library Assistant <= 3.35 - Cross-Site Request Forgery via Bulk Action Form
Summary
The Media Library Assistant plugin for WordPress is vulnerable to Cross-Site Request Forgery in versions up to, and including, 3.35 This is due to missing nonce verification on the bulk action handlers in the settings tab handlers. This makes it possible for unauthenticated attackers to trick an administrator into performing bulk delete, edit, or purge operations on plugin settings and attachment metadata via a forged request.
Severity
8.1 (High)
SSVC
Exploitation: none
Automatable: no
Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
- CWE-352 - Cross-Site Request Forgery (CSRF)
Assigner
References
11 references
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| dglingren | Media Library Assistant |
Affected:
0 , ≤ 3.35
(semver)
|
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.
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