CVE-2024-51643 (GCVE-0-2024-51643)

Vulnerability from cvelistv5 – Published: 2024-11-19 16:32 – Updated: 2026-05-11 22:09
VLAI
Title
WordPress Amazon Associate Filter plugin <= 0.4 - CSRF to Stored XSS vulnerability
Summary
Cross-Site Request Forgery (CSRF) vulnerability in ragaskar Amazon Associate Filter amazon-associate-filter allows Stored XSS.This issue affects Amazon Associate Filter: from n/a through <= 0.4.
Severity
7.1 (High)
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:L/I:L/A:L
SSVC
Exploitation: none Automatable: no Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2024-11-19 20:42 UTC
CWE
  • CWE-352 - Cross-Site Request Forgery (CSRF)
Assigner
References
Impacted products
Vendor Product Version CPE status
ragaskar Amazon Associate Filter Affected: 0 , ≤ 0.4 (custom)
guessed Create a notification for this product.
Date Public
2026-04-01 16:29
Credits
SOPROBRO | Patchstack Bug Bounty Program
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.


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.