CVE-2026-47572 (GCVE-0-2026-47572)

Vulnerability from cvelistv5 – Published: 2026-09-30 15:50 – Updated: 2026-09-30 17:59
VLAI
Summary
NVIDIA GPU Display Driver for Linux contains a vulnerability in the kernel mode layer where a user could cause type confusion. A successful exploit of this vulnerability might lead to code execution, denial of service, escalation of privileges, information disclosure, and data tampering.
SSVC
Exploitation: none Automatable: no Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-09-30 17:49 UTC
CWE
  • CWE-843 - Access of Resource Using Incompatible Type ('Type Confusion')
Impacted products
Vendor Product Version CPE status
NVIDIA GeForce Affected: All driver versions prior to 615.71.09
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NVIDIA GeForce Affected: All driver versions prior to 610.57.04
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NVIDIA RTX, Quadro, NVS Affected: All driver versions prior to 615.71.09
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NVIDIA RTX, Quadro, NVS Affected: All driver versions prior to 610.57.04
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NVIDIA RTX, Quadro, NVS Affected: All driver versions prior to 595.91.07
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NVIDIA RTX, Quadro, NVS Affected: All driver versions prior to 580.178.04
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NVIDIA Tesla Affected: All driver versions prior to 615.71.09
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NVIDIA Tesla Affected: All driver versions prior to 610.57.04
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NVIDIA Tesla Affected: All driver versions prior to 595.91.07
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NVIDIA Tesla Affected: All driver versions prior to 580.178.04
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NVIDIA GeForce Affected: All driver versions prior to 595.91.07
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NVIDIA GeForce Affected: All driver versions prior to 580.178.04
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Show details on NVD website

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                {
                  "cweId": "CWE-843",
                  "description": "CWE-843 Access of Resource Using Incompatible Type (\u0027Type Confusion\u0027)",
                  "lang": "en",
                  "type": "CWE"
                }
              ]
            }
          ],
          "providerMetadata": {
            "dateUpdated": "2026-09-30T15:50:42.877Z",
            "orgId": "9576f279-3576-44b5-a4af-b9a8644b2de6",
            "shortName": "nvidia"
          },
          "references": [
            {
              "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-47572"
            },
            {
              "url": "https://www.cve.org/CVERecord?id=CVE-2026-47572"
            },
            {
              "url": "https://github.com/NVIDIA/product-security/tree/main/2026/5861"
            }
          ],
          "source": {
            "discovery": "UNKNOWN"
          },
          "x_generator": {
            "engine": "NVIDIA PSIRT"
          }
        }
      },
      "cveMetadata": {
        "assignerOrgId": "9576f279-3576-44b5-a4af-b9a8644b2de6",
        "assignerShortName": "nvidia",
        "cveId": "CVE-2026-47572",
        "datePublished": "2026-09-30T15:50:42.877Z",
        "dateReserved": "2026-05-19T19:55:47.437Z",
        "dateUpdated": "2026-09-30T17:59:50.037Z",
        "state": "PUBLISHED"
      },
      "dataType": "CVE_RECORD",
      "dataVersion": "5.2"
    }
  }
}



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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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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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