CVE-2015-1872 (GCVE-0-2015-1872)

Vulnerability from cvelistv5 – Published: 2015-07-26 22:00 – Updated: 2024-08-06 04:54
VLAI
Summary
The ff_mjpeg_decode_sof function in libavcodec/mjpegdec.c in FFmpeg before 2.5.4 does not validate the number of components in a JPEG-LS Start Of Frame segment, which allows remote attackers to cause a denial of service (out-of-bounds array access) or possibly have unspecified other impact via crafted Motion JPEG data.
Severity
No CVSS data available.
CWE
  • n/a
Assigner
References
URL Tags
http://git.videolan.org/?p=ffmpeg.git%3Ba=commit%… x_refsource_CONFIRM
http://www.ubuntu.com/usn/USN-2944-1 vendor-advisoryx_refsource_UBUNTU
http://www.securitytracker.com/id/1033078 vdb-entryx_refsource_SECTRACK
http://www.securityfocus.com/bid/72644 vdb-entryx_refsource_BID
https://lists.debian.org/debian-lts-announce/2019… mailing-listx_refsource_MLIST
Date Public
2015-02-05 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.



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.