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CVE-2020-29444 (GCVE-0-2020-29444)

Vulnerability from cvelistv5 – Published: 2021-05-07 06:10 – Updated: 2025-02-12 20:56
VLAI
Summary
Affected versions of Team Calendar in Confluence Server before 7.11.0 allow attackers to inject arbitrary HTML or Javascript via a Cross Site Scripting Vulnerability in admin global setting parameters.
Severity
5.4 (Medium)
CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:C/C:L/I:L/A:N
SSVC
Exploitation: none Automatable: no Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-02-12 20:54 UTC
CWE
  • Cross Site Scripting
  • CWE-79 - Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')
Assigner
References
Impacted products
Vendor Product Version CPE status
Atlassian Confluence Server Affected: unspecified , < 7.11.0 (custom)
guessed Create a notification for this product.
Date Public
2021-04-22 00:00
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.