CVE-2022-2080 (GCVE-0-2022-2080)

Vulnerability from cvelistv5 – Published: 2022-08-29 14:40 – Updated: 2024-08-03 00:24
VLAI
Title
Sensei LMS < 4.5.2 - Arbitrary Private Message Sending via IDOR
Summary
The Sensei LMS WordPress plugin before 4.5.2 does not ensure that the sender of a private message is either the teacher or the original sender, allowing any authenticated user to send messages to arbitrary private conversation via a IDOR attack. Note: Attackers are not able to see responses/messages between the teacher and student
Severity
4.3 (Medium)
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:L/A:N
CWE
  • CWE-639 - Authorization Bypass Through User-Controlled Key
Assigner
References
Impacted products
Vendor Product Version CPE status
Unknown Sensei LMS – Online Courses, Quizzes, & Learning Affected: 4.5.2 , < 4.5.2 (custom)
guessed Create a notification for this product.
Credits
Veshraj Ghimire
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.