CVE-2016-4575 (GCVE-0-2016-4575)

Vulnerability from cvelistv5 – Published: 2016-05-25 15:00 – Updated: 2024-08-06 00:32
VLAI
Summary
Cross-site scripting (XSS) vulnerability in the email APP in Huawei PLK smartphones with software AL10C00 before AL10C00B211 and AL10C92 before AL10C92B211; ATH smartphones with software AL00C00 before AL00C00B361, CL00C92 before CL00C92B361, TL00HC01 before TL00HC01B361, and UL00C00 before UL00C00B361; CherryPlus smartphones with software TL00C00 before TL00C00B553, UL00C00 before UL00C00B553, and TL00MC01 before TL00MC01B553; and RIO smartphones with software AL00C00 before AL00C00B360 allows remote attackers to inject arbitrary web script or HTML via an email message.
Severity
6.1 (Medium)
CVSS:3.0/AV:N/AC:L/PR:N/UI:R/S:C/C:L/I:L/A:N
CWE
  • n/a
Assigner
References
Date Public
2016-05-07 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

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.