CVE-2016-4852 (GCVE-0-2016-4852)

Vulnerability from cvelistv5 – Published: 2016-09-12 10:00 – Updated: 2024-08-06 00:46
VLAI
Summary
YoruFukurou (NightOwl) before 2.85 relies on support for emoji skin-tone modifiers even though this support is missing from the CoreText CTFramesetter API on OS X 10.9, which allows remote attackers to cause a denial of service (application crash) via a crafted emoji character sequence.
Severity
6.5 (Medium)
CVSS:3.0/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:H
CWE
  • n/a
Assigner
References
URL Tags
http://jvn.jp/en/jp/JVN94816361/index.html third-party-advisoryx_refsource_JVN
http://jvn.jp/en/jp/JVN94816361/995844/index.html x_refsource_CONFIRM
http://jvndb.jvn.jp/jvndb/JVNDB-2016-000151 third-party-advisoryx_refsource_JVNDB
http://www.securityfocus.com/bid/92609 vdb-entryx_refsource_BID
Date Public
2016-08-24 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.