CVE-2025-32608 (GCVE-0-2025-32608)

Vulnerability from cvelistv5 – Published: 2025-04-17 15:47 – Updated: 2026-04-28 16:12
VLAI
Title
WordPress Movylo Marketing Automation Plugin <= 2.0.7 - Cross Site Scripting (XSS) vulnerability
Summary
Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting') vulnerability in Movylo Movylo Marketing Automation movylo-widget allows Reflected XSS.This issue affects Movylo Marketing Automation: from n/a through <= 2.0.7.
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 2025-04-17 18:07 UTC
CWE
  • CWE-79 - Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')
Assigner
References
Impacted products
Vendor Product Version CPE status
Movylo Movylo Marketing Automation Affected: 0 , ≤ 2.0.7 (custom)
guessed Create a notification for this product.
Date Public
2026-04-01 16:38
Credits
0xd4rk5id3 | 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

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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.


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.