{
  "document": {
    "category": "csaf_vex",
    "csaf_version": "2.0",
    "distribution": {
      "text": "Public",
      "tlp": {
        "label": "WHITE",
        "url": "https://www.first.org/tlp/"
      }
    },
    "lang": "en-US",
    "notes": [
      {
        "category": "general",
        "text": "To determine the support lifecycle for your software, see the Microsoft Support Lifecycle: https://support.microsoft.com/lifecycle",
        "title": "Additional Resources"
      },
      {
        "category": "legal_disclaimer",
        "text": "The information provided in the Microsoft Knowledge Base is provided \\\"as is\\\" without warranty of any kind. Microsoft disclaims all warranties, either express or implied, including the warranties of merchantability and fitness for a particular purpose. In no event shall Microsoft Corporation or its suppliers be liable for any damages whatsoever including direct, indirect, incidental, consequential, loss of business profits or special damages, even if Microsoft Corporation or its suppliers have been advised of the possibility of such damages. Some states do not allow the exclusion or limitation of liability for consequential or incidental damages so the foregoing limitation may not apply.",
        "title": "Disclaimer"
      }
    ],
    "publisher": {
      "category": "vendor",
      "contact_details": "secure@microsoft.com",
      "name": "Microsoft Security Response Center",
      "namespace": "https://msrc.microsoft.com"
    },
    "references": [
      {
        "category": "self",
        "summary": "CVE-2025-46153 PyTorch before 3.7.0 has a bernoulli_p decompose function in decompositions.py even though it lacks full consistency with the eager CPU implementation, negatively affecting nn.Dropout1d, nn.Dropout2d, and nn.Dropout3d for fallback_random=True. - VEX",
        "url": "https://msrc.microsoft.com/csaf/vex/2025/msrc_cve-2025-46153.json"
      },
      {
        "category": "external",
        "summary": "Microsoft Support Lifecycle",
        "url": "https://support.microsoft.com/lifecycle"
      },
      {
        "category": "external",
        "summary": "Common Vulnerability Scoring System",
        "url": "https://www.first.org/cvss"
      }
    ],
    "title": "PyTorch before 3.7.0 has a bernoulli_p decompose function in decompositions.py even though it lacks full consistency with the eager CPU implementation, negatively affecting nn.Dropout1d, nn.Dropout2d, and nn.Dropout3d for fallback_random=True.",
    "tracking": {
      "current_release_date": "2025-10-02T01:04:57.000Z",
      "generator": {
        "date": "2025-10-20T03:48:57.208Z",
        "engine": {
          "name": "MSRC Generator",
          "version": "1.0"
        }
      },
      "id": "msrc_CVE-2025-46153",
      "initial_release_date": "2025-09-02T00:00:00.000Z",
      "revision_history": [
        {
          "date": "2025-10-02T01:04:57.000Z",
          "legacy_version": "1",
          "number": "1",
          "summary": "Information published."
        }
      ],
      "status": "final",
      "version": "1"
    }
  },
  "product_tree": {
    "branches": [
      {
        "branches": [
          {
            "branches": [
              {
                "category": "product_version",
                "name": "3.0",
                "product": {
                  "name": "Azure Linux 3.0",
                  "product_id": "17084"
                }
              },
              {
                "category": "product_version",
                "name": "2.0",
                "product": {
                  "name": "CBL Mariner 2.0",
                  "product_id": "17086"
                }
              }
            ],
            "category": "product_name",
            "name": "Azure Linux"
          },
          {
            "branches": [
              {
                "category": "product_version_range",
                "name": "azl3 pytorch 2.2.2-7",
                "product": {
                  "name": "azl3 pytorch 2.2.2-7",
                  "product_id": "2"
                }
              },
              {
                "category": "product_version_range",
                "name": "cbl2 pytorch 2.0.0-9",
                "product": {
                  "name": "cbl2 pytorch 2.0.0-9",
                  "product_id": "1"
                }
              }
            ],
            "category": "product_name",
            "name": "pytorch"
          }
        ],
        "category": "vendor",
        "name": "Microsoft"
      }
    ],
    "relationships": [
      {
        "category": "default_component_of",
        "full_product_name": {
          "name": "azl3 pytorch 2.2.2-7 as a component of Azure Linux 3.0",
          "product_id": "17084-2"
        },
        "product_reference": "2",
        "relates_to_product_reference": "17084"
      },
      {
        "category": "default_component_of",
        "full_product_name": {
          "name": "cbl2 pytorch 2.0.0-9 as a component of CBL Mariner 2.0",
          "product_id": "17086-1"
        },
        "product_reference": "1",
        "relates_to_product_reference": "17086"
      }
    ]
  },
  "vulnerabilities": [
    {
      "cve": "CVE-2025-46153",
      "cwe": {
        "id": "CWE-1176",
        "name": "Inefficient CPU Computation"
      },
      "notes": [
        {
          "category": "general",
          "text": "mitre",
          "title": "Assigning CNA"
        }
      ],
      "product_status": {
        "known_affected": [
          "17084-2",
          "17086-1"
        ]
      },
      "references": [
        {
          "category": "self",
          "summary": "CVE-2025-46153 PyTorch before 3.7.0 has a bernoulli_p decompose function in decompositions.py even though it lacks full consistency with the eager CPU implementation, negatively affecting nn.Dropout1d, nn.Dropout2d, and nn.Dropout3d for fallback_random=True. - VEX",
          "url": "https://msrc.microsoft.com/csaf/vex/2025/msrc_cve-2025-46153.json"
        }
      ],
      "scores": [
        {
          "cvss_v3": {
            "attackComplexity": "LOW",
            "attackVector": "NETWORK",
            "availabilityImpact": "NONE",
            "baseScore": 5.3,
            "baseSeverity": "MEDIUM",
            "confidentialityImpact": "LOW",
            "environmentalsScore": 0.0,
            "integrityImpact": "NONE",
            "privilegesRequired": "NONE",
            "scope": "UNCHANGED",
            "temporalScore": 5.3,
            "userInteraction": "NONE",
            "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N",
            "version": "3.1"
          },
          "products": [
            "17084-2",
            "17086-1"
          ]
        }
      ],
      "title": "PyTorch before 3.7.0 has a bernoulli_p decompose function in decompositions.py even though it lacks full consistency with the eager CPU implementation, negatively affecting nn.Dropout1d, nn.Dropout2d, and nn.Dropout3d for fallback_random=True."
    }
  ]
}