CVE-2016-0133 (GCVE-0-2016-0133)

Vulnerability from cvelistv5 – Published: 2016-03-09 11:00 – Updated: 2024-08-05 22:08
VLAI
Summary
The USB Mass Storage Class driver in Microsoft Windows Vista SP2, Windows Server 2008 SP2 and R2 SP1, Windows 7 SP1, Windows 8.1, Windows Server 2012 Gold and R2, Windows RT 8.1, and Windows 10 Gold and 1511 allows physically proximate attackers to execute arbitrary code by inserting a crafted USB device, aka "USB Mass Storage Elevation of Privilege Vulnerability."
Severity
6.8 (Medium)
CVSS:3.0/AV:P/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
CWE
  • n/a
Assigner
References
URL Tags
https://docs.microsoft.com/en-us/security-updates… vendor-advisoryx_refsource_MS
http://www.securitytracker.com/id/1035211 vdb-entryx_refsource_SECTRACK
http://www.securityfocus.com/bid/84035 vdb-entryx_refsource_BID
Date Public
2016-03-08 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.


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.