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CVE-2016-9031 (GCVE-0-2016-9031)

Vulnerability from cvelistv5 – Published: 2016-12-14 17:00 – Updated: 2024-08-06 02:35
VLAI
Summary
An exploitable integer overflow exists in the Joyent SmartOS 20161110T013148Z Hyprlofs file system. The vulnerability is present in the Ioctl system call with the command HYPRLOFS_ADD_ENTRIES when dealing with 32-bit file systems. An attacker can craft an input that can cause a kernel panic and potentially be leveraged into a full privilege escalation vulnerability. This vulnerability is distinct from CVE-2016-8733.
Severity
7.8 (High)
CVSS:3.0/AV:L/AC:H/PR:L/UI:N/S:C/C:H/I:H/A:H
CWE
  • integer overflow
Assigner
References
Impacted products
Vendor Product Version CPE status
Joyent SmartOS Affected: OS 20161110T013148Z
guessed Create a notification for this product.
Date Public
2016-12-12 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.