CVE-2023-49829 (GCVE-0-2023-49829)

Vulnerability from cvelistv5 – Published: 2023-12-15 15:30 – Updated: 2026-04-28 16:08
VLAI
Title
WordPress Tutor LMS Plugin <= 2.2.4 is vulnerable to Cross Site Scripting (XSS)
Summary
Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting') vulnerability in Themeum Tutor LMS – eLearning and online course solution allows Stored XSS.This issue affects Tutor LMS – eLearning and online course solution: from n/a through 2.2.4.
Severity
5.9 (Medium)
CVSS:3.1/AV:N/AC:L/PR:H/UI:R/S:C/C:L/I:L/A:L
CWE
  • CWE-79 - Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')
Assigner
References
Impacted products
Vendor Product Version CPE status
Themeum Tutor LMS – eLearning and online course solution Affected: n/a , ≤ 2.2.4 (custom)
guessed Create a notification for this product.
Credits
emad (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

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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.