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CVE-2017-18316 (GCVE-0-2017-18316)

Vulnerability from cvelistv5 – Published: 2018-11-28 15:00 – Updated: 2024-08-05 21:20
VLAI
Summary
Secure application can access QSEE kernel memory through Ontario kernel driver in Snapdragon Automobile, Snapdragon Mobile and Snapdragon Wear in versions MDM9206, MDM9607, MDM9650, MSM8996AU, SD 210/SD 212/SD 205, SD 425, SD 430, SD 450, SD 625, SD 820, SD 820A, SD 835, SD 845, SD 850, SDA660, SDA845, SDX24, SXR1130.
CWE
  • Improper Access Control in Biometrics
References
Impacted products
Vendor Product Version CPE status
Qualcomm, Inc. Snapdragon Automobile, Snapdragon Mobile, Snapdragon Wear Affected: MDM9206, MDM9607, MDM9650, MSM8996AU, SD 210/SD 212/SD 205, SD 425, SD 430, SD 450, SD 625, SD 820, SD 820A, SD 835, SD 845, SD 850, SDA660, SDA845, SDX24, SXR1130
guessed Create a notification for this product.
Date Public
2018-11-28 00:00
Show details on NVD website

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  }
}



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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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