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CVE-2023-44991 (GCVE-0-2023-44991)

Vulnerability from cvelistv5 – Published: 2023-12-19 15:34 – Updated: 2026-04-28 16:08
VLAI
Title
WordPress Media File Renamer Plugin <= 5.6.9 is vulnerable to Sensitive Data Exposure
Summary
Exposure of Sensitive Information to an Unauthorized Actor vulnerability in Jordy Meow Media File Renamer: Rename Files (Manual, Auto & AI).This issue affects Media File Renamer: Rename Files (Manual, Auto & AI): from n/a through 5.6.9.
Severity
6.5 (Medium)
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:N/A:N
CWE
  • CWE-200 - Exposure of Sensitive Information to an Unauthorized Actor
Assigner
References
Impacted products
Vendor Product Version CPE status
Jordy Meow Media File Renamer: Rename Files (Manual, Auto & AI) Affected: n/a , ≤ 5.6.9 (custom)
guessed Create a notification for this product.
Credits
Joshua Chan (Patchstack Alliance)
Show details on NVD website
To clipboard 

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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.


Detection rules are retrieved from Rulezet.


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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.