CVE-2026-1233 (GCVE-0-2026-1233)
Vulnerability from cvelistv5 – Published: 2026-04-04 11:16 – Updated: 2026-04-08 17:17
VLAI
EPSS
VEX
Title
Text to Speech (TTS) by Mementor <= 1.9.8 - Use of Hardcoded Password to Unauthenticated Remote Database Access
Summary
The Text to Speech for WP (AI Voices by Mementor) plugin for WordPress is vulnerable to sensitive information exposure in all versions up to, and including, 1.9.8. This is due to the plugin containing hardcoded MySQL database credentials for the vendor's external telemetry server in the `Mementor_TTS_Remote_Telemetry` class. This makes it possible for unauthenticated attackers to extract and decode these credentials, gaining unauthorized write access to the vendor's telemetry database.
Severity
7.5 (High)
SSVC
Exploitation: none
Automatable: yes
Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-04-06 15:44 UTC
CWE
- CWE-798 - Use of Hard-coded Credentials
Assigner
References
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| mvirik | Text to Speech – TTSWP |
Affected:
0 , ≤ 1.9.8
(semver)
|
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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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