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VAR-201911-1671

Vulnerability from variot - Updated: 2025-01-30 19:51

Lack of checking a variable received from driver and populating in Firmware data structure leads to buffer overflow in Snapdragon Auto, Snapdragon Compute, Snapdragon Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wearables in MSM8909W, MSM8996AU, QCS605, Qualcomm 215, SD 210/SD 212/SD 205, SD 425, SD 427, SD 430, SD 435, SD 439 / SD 429, SD 450, SD 625, SD 632, SD 636, SD 665, SD 675, SD 712 / SD 710 / SD 670, SD 730, SD 820, SD 820A, SD 835, SD 845 / SD 850, SD 855, SD 8CX, SDA660, SDM439, SDM630, SDM660, Snapdragon_High_Med_2016, SXR1130. plural Snapdragon The product contains a classic buffer overflow vulnerability.Information is obtained, information is altered, and service operation is disrupted (DoS) There is a possibility of being put into a state

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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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