CVE-2022-36399 (GCVE-0-2022-36399)

Vulnerability from cvelistv5 – Published: 2023-12-28 21:49 – Updated: 2026-04-28 16:07
VLAI
Title
WordPress Booked Plugin < 2.4.4 is vulnerable to Sensitive Data Exposure
Summary
Exposure of Sensitive Information to an Unauthorized Actor vulnerability in BoxyStudio Booked - Appointment Booking for WordPress | Calendars.This issue affects Booked - Appointment Booking for WordPress | Calendars: from n/a before 2.4.4.
Severity
5.3 (Medium)
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N
CWE
  • CWE-200 - Exposure of Sensitive Information to an Unauthorized Actor
Assigner
References
Impacted products
Vendor Product Version CPE status
BoxyStudio Booked - Appointment Booking for WordPress | Calendars Affected: n/a , < 2.4.4 (custom)
guessed Create a notification for this product.
Credits
coogee86 (Patchstack Alliance)
Show details on NVD website
To clipboard 

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Taxonomy of the tags.





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.



Related by attack behaviour

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.