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CVE-2017-8106 (GCVE-0-2017-8106)

Vulnerability from cvelistv5 – Published: 2017-04-24 23:00 – Updated: 2024-09-16 23:41
VLAI
Summary
The handle_invept function in arch/x86/kvm/vmx.c in the Linux kernel 3.12 through 3.15 allows privileged KVM guest OS users to cause a denial of service (NULL pointer dereference and host OS crash) via a single-context INVEPT instruction with a NULL EPT pointer.
CWE
  • n/a
References
Show details on NVD website

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      "cve": "CVE-2017-8106",
      "id": "CVE-2017-8106",
      "initial_release_date": "2023-02-15T04:46:18Z",
      "product_status:known_not_affected": "487",
      "product_status:recommended": "104",
      "source": "SUSE CSAF VEX",
      "status": "interim",
      "title": "SUSE CVE CVE-2017-8106",
      "url": "https://ftp.suse.com/pub/projects/security/csaf-vex/cve-2017-8106.json",
      "version": "18"
    }
  }
}



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Taxonomy of the tags.


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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.

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Detection rules are retrieved from Rulezet.

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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.


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