Search

Find a vulnerability

Search criteria ⓘ Use this form to refine search results.
Full-text search supports keyword queries with ranking and filtering.
You can combine vendor, product, and sources to narrow results.
Enable “Apply ordering” to sort by date instead of relevance.

    9 vulnerabilities found for pytorch by pytorch

    CVE-2026-24747 (GCVE-0-2026-24747)

    Vulnerability from nvd – Published: 2026-01-27 21:13 – Updated: 2026-06-30 12:06
    VLAI
    Title
    PyTorch Vulnerable to Remote Code Execution via Untrusted Checkpoint Files
    Summary
    PyTorch is a Python package that provides tensor computation. Prior to version 2.10.0, a vulnerability in PyTorch's `weights_only` unpickler allows an attacker to craft a malicious checkpoint file (`.pth`) that, when loaded with `torch.load(..., weights_only=True)`, can corrupt memory and potentially lead to arbitrary code execution. Version 2.10.0 fixes the issue.
    Severity
    8.8 (High)
    CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
    SSVC
    Exploitation: none Automatable: no Technical Impact: total
    CISA Coordinator (v2.0.3)
    CWE
    • CWE-502 - Deserialization of Untrusted Data
    • CWE-94 - Improper Control of Generation of Code ('Code Injection')
    Assigner
    References
    Impacted products
    Show details on NVD website
    To clipboard 

    {
  "containers": {
    "adp": [
      {
        "metrics": [
          {
            "other": {
              "content": {
                "id": "CVE-2026-24747",
                "options": [
                  {
                    "Exploitation": "none"
                  },
                  {
                    "Automatable": "no"
                  },
                  {
                    "Technical Impact": "total"
                  }
                ],
                "role": "CISA Coordinator",
                "timestamp": "2026-01-30T04:55:40.763016Z",
                "version": "2.0.3"
              },
              "type": "ssvc"
            }
          }
        ],
        "providerMetadata": {
          "dateUpdated": "2026-02-26T15:04:50.008Z",
          "orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
          "shortName": "CISA-ADP"
        },
        "title": "CISA ADP Vulnrichment"
      },
      {
        "affected": [
          {
            "cpes": [
              "cpe:/a:redhat:openshift_ai:2.25::el9"
            ],
            "defaultStatus": "affected",
            "product": "Red Hat OpenShift AI 2.25",
            "vendor": "Red Hat"
          },
          {
            "cpes": [
              "cpe:/a:redhat:openshift_ai"
            ],
            "defaultStatus": "unaffected",
            "product": "Red Hat OpenShift AI (RHOAI)",
            "vendor": "Red Hat"
          }
        ],
        "datePublic": "2026-01-27T21:13:46.878Z",
        "descriptions": [
          {
            "lang": "en",
            "value": "A flaw was found in PyTorch, a Python package for tensor computation. A remote attacker could craft a malicious checkpoint file, which, when loaded using the `weights_only` unpickler, could lead to memory corruption. This vulnerability may enable an attacker to achieve arbitrary code execution on the affected system."
          }
        ],
        "metrics": [
          {
            "other": {
              "content": {
                "namespace": "https://access.redhat.com/security/updates/classification/",
                "value": "Important"
              },
              "type": "Red Hat severity rating"
            }
          },
          {
            "cvssV3_1": {
              "attackComplexity": "LOW",
              "attackVector": "NETWORK",
              "availabilityImpact": "HIGH",
              "baseScore": 8.8,
              "baseSeverity": "HIGH",
              "confidentialityImpact": "HIGH",
              "integrityImpact": "HIGH",
              "privilegesRequired": "NONE",
              "scope": "UNCHANGED",
              "userInteraction": "REQUIRED",
              "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H",
              "version": "3.1"
            },
            "format": "CVSS"
          }
        ],
        "problemTypes": [
          {
            "descriptions": [
              {
                "cweId": "CWE-502",
                "description": "Deserialization of Untrusted Data",
                "lang": "en",
                "type": "CWE"
              }
            ]
          }
        ],
        "providerMetadata": {
          "dateUpdated": "2026-06-30T12:06:37.429Z",
          "orgId": "0b0ca135-0b70-47e7-9f44-1890c2a1c46c",
          "shortName": "redhat-SADP"
        },
        "references": [
          {
            "tags": [
              "vdb-entry",
              "x_refsource_REDHAT"
            ],
            "url": "https://access.redhat.com/security/cve/CVE-2026-24747"
          },
          {
            "name": "RHBZ#2433612",
            "tags": [
              "issue-tracking",
              "x_refsource_REDHAT"
            ],
            "url": "https://bugzilla.redhat.com/show_bug.cgi?id=2433612"
          },
          {
            "tags": [
              "x_sadp-csaf-vex"
            ],
            "url": "https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-24747.json"
          },
          {
            "tags": [
              "vendor-advisory",
              "x_refsource_REDHAT"
            ],
            "url": "https://access.redhat.com/errata/RHSA-2026:24977"
          }
        ],
        "solutions": [
          {
            "lang": "en",
            "value": "RHSA-2026:24977: Red Hat OpenShift AI 2.25"
          }
        ],
        "timeline": [
          {
            "lang": "en",
            "time": "2026-01-27T22:01:52.649Z",
            "value": "Reported to Red Hat."
          },
          {
            "lang": "en",
            "time": "2026-01-27T21:13:46.878Z",
            "value": "Made public."
          }
        ],
        "title": "pytorch: PyTorch: Arbitrary code execution via malicious checkpoint file loading",
        "x_adpType": "supplier",
        "x_generator": {
          "engine": "sadp-cli 1.0.0"
        }
      }
    ],
    "cna": {
      "affected": [
        {
          "product": "pytorch",
          "vendor": "pytorch",
          "versions": [
            {
              "status": "affected",
              "version": "\u003c 2.10.0"
            }
          ]
        }
      ],
      "descriptions": [
        {
          "lang": "en",
          "value": "PyTorch is a Python package that provides tensor computation. Prior to version 2.10.0, a vulnerability in PyTorch\u0027s `weights_only` unpickler allows an attacker to craft a malicious checkpoint file (`.pth`) that, when loaded with `torch.load(..., weights_only=True)`, can corrupt memory and potentially lead to arbitrary code execution. Version 2.10.0 fixes the issue."
        }
      ],
      "metrics": [
        {
          "cvssV3_1": {
            "attackComplexity": "LOW",
            "attackVector": "NETWORK",
            "availabilityImpact": "HIGH",
            "baseScore": 8.8,
            "baseSeverity": "HIGH",
            "confidentialityImpact": "HIGH",
            "integrityImpact": "HIGH",
            "privilegesRequired": "NONE",
            "scope": "UNCHANGED",
            "userInteraction": "REQUIRED",
            "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H",
            "version": "3.1"
          }
        }
      ],
      "problemTypes": [
        {
          "descriptions": [
            {
              "cweId": "CWE-502",
              "description": "CWE-502: Deserialization of Untrusted Data",
              "lang": "en",
              "type": "CWE"
            }
          ]
        },
        {
          "descriptions": [
            {
              "cweId": "CWE-94",
              "description": "CWE-94: Improper Control of Generation of Code (\u0027Code Injection\u0027)",
              "lang": "en",
              "type": "CWE"
            }
          ]
        }
      ],
      "providerMetadata": {
        "dateUpdated": "2026-01-27T21:13:46.878Z",
        "orgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
        "shortName": "GitHub_M"
      },
      "references": [
        {
          "name": "https://github.com/pytorch/pytorch/security/advisories/GHSA-63cw-57p8-fm3p",
          "tags": [
            "x_refsource_CONFIRM"
          ],
          "url": "https://github.com/pytorch/pytorch/security/advisories/GHSA-63cw-57p8-fm3p"
        },
        {
          "name": "https://github.com/pytorch/pytorch/issues/163105",
          "tags": [
            "x_refsource_MISC"
          ],
          "url": "https://github.com/pytorch/pytorch/issues/163105"
        },
        {
          "name": "https://github.com/pytorch/pytorch/163122/commit/954dc5183ee9205cbe79876ad05dd2d9ae752139",
          "tags": [
            "x_refsource_MISC"
          ],
          "url": "https://github.com/pytorch/pytorch/163122/commit/954dc5183ee9205cbe79876ad05dd2d9ae752139"
        },
        {
          "name": "https://github.com/pytorch/pytorch/releases/tag/v2.10.0",
          "tags": [
            "x_refsource_MISC"
          ],
          "url": "https://github.com/pytorch/pytorch/releases/tag/v2.10.0"
        }
      ],
      "source": {
        "advisory": "GHSA-63cw-57p8-fm3p",
        "discovery": "UNKNOWN"
      },
      "title": "PyTorch Vulnerable to Remote Code Execution via Untrusted Checkpoint Files"
    }
  },
  "cveMetadata": {
    "assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
    "assignerShortName": "GitHub_M",
    "cveId": "CVE-2026-24747",
    "datePublished": "2026-01-27T21:13:46.878Z",
    "dateReserved": "2026-01-26T19:06:16.059Z",
    "dateUpdated": "2026-06-30T12:06:37.429Z",
    "state": "PUBLISHED"
  },
  "dataType": "CVE_RECORD",
  "dataVersion": "5.2"
}

    CVE-2025-32434 (GCVE-0-2025-32434)

    Vulnerability from nvd – Published: 2025-04-18 15:48 – Updated: 2025-12-01 07:05
    VLAI
    Title
    PyTorch: `torch.load` with `weights_only=True` leads to remote code execution
    Summary
    PyTorch is a Python package that provides tensor computation with strong GPU acceleration and deep neural networks built on a tape-based autograd system. In version 2.5.1 and prior, a Remote Command Execution (RCE) vulnerability exists in PyTorch when loading a model using torch.load with weights_only=True. This issue has been patched in version 2.6.0.
    Severity
    9.3 (Critical)
    CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N
    SSVC
    Exploitation: none Automatable: yes Technical Impact: total
    CISA Coordinator (v2.0.3)
    CWE
    • CWE-502 - Deserialization of Untrusted Data
    Assigner
    References
    Impacted products
    Vendor Product Version
    pytorch pytorch Affected: < 2.6.0
    		Create a notification for this product.
    Show details on NVD website
    To clipboard 

    {
  "containers": {
    "adp": [
      {
        "metrics": [
          {
            "other": {
              "content": {
                "id": "CVE-2025-32434",
                "options": [
                  {
                    "Exploitation": "none"
                  },
                  {
                    "Automatable": "yes"
                  },
                  {
                    "Technical Impact": "total"
                  }
                ],
                "role": "CISA Coordinator",
                "timestamp": "2025-04-18T16:06:40.000632Z",
                "version": "2.0.3"
              },
              "type": "ssvc"
            }
          }
        ],
        "providerMetadata": {
          "dateUpdated": "2025-04-18T16:06:51.966Z",
          "orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
          "shortName": "CISA-ADP"
        },
        "title": "CISA ADP Vulnrichment"
      },
      {
        "providerMetadata": {
          "dateUpdated": "2025-12-01T07:05:28.923Z",
          "orgId": "af854a3a-2127-422b-91ae-364da2661108",
          "shortName": "CVE"
        },
        "references": [
          {
            "url": "https://lists.debian.org/debian-lts-announce/2025/12/msg00000.html"
          }
        ],
        "title": "CVE Program Container"
      }
    ],
    "cna": {
      "affected": [
        {
          "product": "pytorch",
          "vendor": "pytorch",
          "versions": [
            {
              "status": "affected",
              "version": "\u003c 2.6.0"
            }
          ]
        }
      ],
      "descriptions": [
        {
          "lang": "en",
          "value": "PyTorch is a Python package that provides tensor computation with strong GPU acceleration and deep neural networks built on a tape-based autograd system. In version 2.5.1 and prior, a Remote Command Execution (RCE) vulnerability exists in PyTorch when loading a model using torch.load with weights_only=True. This issue has been patched in version 2.6.0."
        }
      ],
      "metrics": [
        {
          "cvssV4_0": {
            "attackComplexity": "LOW",
            "attackRequirements": "NONE",
            "attackVector": "NETWORK",
            "baseScore": 9.3,
            "baseSeverity": "CRITICAL",
            "privilegesRequired": "NONE",
            "subAvailabilityImpact": "NONE",
            "subConfidentialityImpact": "NONE",
            "subIntegrityImpact": "NONE",
            "userInteraction": "NONE",
            "vectorString": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N",
            "version": "4.0",
            "vulnAvailabilityImpact": "HIGH",
            "vulnConfidentialityImpact": "HIGH",
            "vulnIntegrityImpact": "HIGH"
          }
        }
      ],
      "problemTypes": [
        {
          "descriptions": [
            {
              "cweId": "CWE-502",
              "description": "CWE-502: Deserialization of Untrusted Data",
              "lang": "en",
              "type": "CWE"
            }
          ]
        }
      ],
      "providerMetadata": {
        "dateUpdated": "2025-04-18T15:48:18.851Z",
        "orgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
        "shortName": "GitHub_M"
      },
      "references": [
        {
          "name": "https://github.com/pytorch/pytorch/security/advisories/GHSA-53q9-r3pm-6pq6",
          "tags": [
            "x_refsource_CONFIRM"
          ],
          "url": "https://github.com/pytorch/pytorch/security/advisories/GHSA-53q9-r3pm-6pq6"
        }
      ],
      "source": {
        "advisory": "GHSA-53q9-r3pm-6pq6",
        "discovery": "UNKNOWN"
      },
      "title": "PyTorch: `torch.load` with `weights_only=True` leads to remote code execution"
    }
  },
  "cveMetadata": {
    "assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
    "assignerShortName": "GitHub_M",
    "cveId": "CVE-2025-32434",
    "datePublished": "2025-04-18T15:48:18.851Z",
    "dateReserved": "2025-04-08T10:54:58.368Z",
    "dateUpdated": "2025-12-01T07:05:28.923Z",
    "state": "PUBLISHED"
  },
  "dataType": "CVE_RECORD",
  "dataVersion": "5.2"
}

    CVE-2025-2149 (GCVE-0-2025-2149)

    Vulnerability from nvd – Published: 2025-03-10 12:31 – Updated: 2025-03-10 14:08
    VLAI
    Title
    PyTorch Quantized Sigmoid Module nnq_Sigmoid initialization
    Summary
    A vulnerability was found in PyTorch 2.6.0+cu124. It has been rated as problematic. Affected by this issue is the function nnq_Sigmoid of the component Quantized Sigmoid Module. The manipulation of the argument scale/zero_point leads to improper initialization. The attack needs to be approached locally. The complexity of an attack is rather high. The exploitation is known to be difficult. The exploit has been disclosed to the public and may be used.
    Severity
    2 (Low)
    CVSS:4.0/AV:L/AC:H/AT:N/PR:L/UI:N/VC:N/VI:L/VA:N/SC:N/SI:N/SA:N
    2.5 (Low)
    CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:L/A:N
    2.5 (Low)
    CVSS:3.0/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:L/A:N
    SSVC
    Exploitation: poc Automatable: no Technical Impact: partial
    CISA Coordinator (v2.0.3)
    CWE
    • CWE-665 - Improper Initialization
    Assigner
    References
    URL Tags
    https://vuldb.com/?id.299060 vdb-entrytechnical-description
    https://vuldb.com/?ctiid.299060 signaturepermissions-required
    https://vuldb.com/?submit.506563 third-party-advisory
    https://github.com/pytorch/pytorch/issues/147818 issue-tracking
    https://github.com/pytorch/pytorch/issues/147818#… exploitissue-tracking
    Impacted products
    Vendor Product Version
    n/a PyTorch Affected: 2.6.0+cu124
    Credits
    Default436352 (VulDB User)
    Show details on NVD website
    To clipboard 

    {
  "containers": {
    "adp": [
      {
        "metrics": [
          {
            "other": {
              "content": {
                "id": "CVE-2025-2149",
                "options": [
                  {
                    "Exploitation": "poc"
                  },
                  {
                    "Automatable": "no"
                  },
                  {
                    "Technical Impact": "partial"
                  }
                ],
                "role": "CISA Coordinator",
                "timestamp": "2025-03-10T14:08:09.193144Z",
                "version": "2.0.3"
              },
              "type": "ssvc"
            }
          }
        ],
        "providerMetadata": {
          "dateUpdated": "2025-03-10T14:08:14.533Z",
          "orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
          "shortName": "CISA-ADP"
        },
        "references": [
          {
            "tags": [
              "exploit"
            ],
            "url": "https://github.com/pytorch/pytorch/issues/147818#issue-2877301660"
          },
          {
            "tags": [
              "exploit"
            ],
            "url": "https://github.com/pytorch/pytorch/issues/147818"
          }
        ],
        "title": "CISA ADP Vulnrichment"
      }
    ],
    "cna": {
      "affected": [
        {
          "modules": [
            "Quantized Sigmoid Module"
          ],
          "product": "PyTorch",
          "vendor": "n/a",
          "versions": [
            {
              "status": "affected",
              "version": "2.6.0+cu124"
            }
          ]
        }
      ],
      "credits": [
        {
          "lang": "en",
          "type": "reporter",
          "value": "Default436352 (VulDB User)"
        }
      ],
      "descriptions": [
        {
          "lang": "en",
          "value": "A vulnerability was found in PyTorch 2.6.0+cu124. It has been rated as problematic. Affected by this issue is the function nnq_Sigmoid of the component Quantized Sigmoid Module. The manipulation of the argument scale/zero_point leads to improper initialization. The attack needs to be approached locally. The complexity of an attack is rather high. The exploitation is known to be difficult. The exploit has been disclosed to the public and may be used."
        },
        {
          "lang": "de",
          "value": "Eine problematische Schwachstelle wurde in PyTorch 2.6.0+cu124 ausgemacht. Davon betroffen ist die Funktion nnq_Sigmoid der Komponente Quantized Sigmoid Module. Durch die Manipulation des Arguments scale/zero_point mit unbekannten Daten kann eine improper initialization-Schwachstelle ausgenutzt werden. Der Angriff muss lokal passieren. Die Komplexit\u00e4t eines Angriffs ist eher hoch. Sie ist schwierig ausnutzbar. Der Exploit steht zur \u00f6ffentlichen Verf\u00fcgung."
        }
      ],
      "metrics": [
        {
          "cvssV4_0": {
            "baseScore": 2,
            "baseSeverity": "LOW",
            "vectorString": "CVSS:4.0/AV:L/AC:H/AT:N/PR:L/UI:N/VC:N/VI:L/VA:N/SC:N/SI:N/SA:N",
            "version": "4.0"
          }
        },
        {
          "cvssV3_1": {
            "baseScore": 2.5,
            "baseSeverity": "LOW",
            "vectorString": "CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:L/A:N",
            "version": "3.1"
          }
        },
        {
          "cvssV3_0": {
            "baseScore": 2.5,
            "baseSeverity": "LOW",
            "vectorString": "CVSS:3.0/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:L/A:N",
            "version": "3.0"
          }
        },
        {
          "cvssV2_0": {
            "baseScore": 1,
            "vectorString": "AV:L/AC:H/Au:S/C:N/I:P/A:N",
            "version": "2.0"
          }
        }
      ],
      "problemTypes": [
        {
          "descriptions": [
            {
              "cweId": "CWE-665",
              "description": "Improper Initialization",
              "lang": "en",
              "type": "CWE"
            }
          ]
        }
      ],
      "providerMetadata": {
        "dateUpdated": "2025-03-10T12:31:04.788Z",
        "orgId": "1af790b2-7ee1-4545-860a-a788eba489b5",
        "shortName": "VulDB"
      },
      "references": [
        {
          "name": "VDB-299060 | PyTorch Quantized Sigmoid Module nnq_Sigmoid initialization",
          "tags": [
            "vdb-entry",
            "technical-description"
          ],
          "url": "https://vuldb.com/?id.299060"
        },
        {
          "name": "VDB-299060 | CTI Indicators (IOB, IOC, IOA)",
          "tags": [
            "signature",
            "permissions-required"
          ],
          "url": "https://vuldb.com/?ctiid.299060"
        },
        {
          "name": "Submit #506563 | pytorch 2.6.0+cu124 Inconsistency Between Implementation and Documented Design",
          "tags": [
            "third-party-advisory"
          ],
          "url": "https://vuldb.com/?submit.506563"
        },
        {
          "tags": [
            "issue-tracking"
          ],
          "url": "https://github.com/pytorch/pytorch/issues/147818"
        },
        {
          "tags": [
            "exploit",
            "issue-tracking"
          ],
          "url": "https://github.com/pytorch/pytorch/issues/147818#issue-2877301660"
        }
      ],
      "timeline": [
        {
          "lang": "en",
          "time": "2025-03-10T00:00:00.000Z",
          "value": "Advisory disclosed"
        },
        {
          "lang": "en",
          "time": "2025-03-10T01:00:00.000Z",
          "value": "VulDB entry created"
        },
        {
          "lang": "en",
          "time": "2025-03-10T07:19:09.000Z",
          "value": "VulDB entry last update"
        }
      ],
      "title": "PyTorch Quantized Sigmoid Module nnq_Sigmoid initialization"
    }
  },
  "cveMetadata": {
    "assignerOrgId": "1af790b2-7ee1-4545-860a-a788eba489b5",
    "assignerShortName": "VulDB",
    "cveId": "CVE-2025-2149",
    "datePublished": "2025-03-10T12:31:04.788Z",
    "dateReserved": "2025-03-10T06:13:15.319Z",
    "dateUpdated": "2025-03-10T14:08:14.533Z",
    "state": "PUBLISHED"
  },
  "dataType": "CVE_RECORD",
  "dataVersion": "5.1"
}

    CVE-2025-2148 (GCVE-0-2025-2148)

    Vulnerability from nvd – Published: 2025-03-10 12:00 – Updated: 2025-03-10 14:10
    VLAI
    Title
    PyTorch Tuple torch.ops.profiler._call_end_callbacks_on_jit_fut memory corruption
    Summary
    A vulnerability was found in PyTorch 2.6.0+cu124. It has been declared as critical. Affected by this vulnerability is the function torch.ops.profiler._call_end_callbacks_on_jit_fut of the component Tuple Handler. The manipulation of the argument None leads to memory corruption. The attack can be launched remotely. The complexity of an attack is rather high. The exploitation appears to be difficult.
    Severity
    2.3 (Low)
    CVSS:4.0/AV:N/AC:H/AT:N/PR:N/UI:P/VC:L/VI:L/VA:L/SC:N/SI:N/SA:N
    5 (Medium)
    CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:L/I:L/A:L
    5 (Medium)
    CVSS:3.0/AV:N/AC:H/PR:N/UI:R/S:U/C:L/I:L/A:L
    SSVC
    Exploitation: poc Automatable: no Technical Impact: partial
    CISA Coordinator (v2.0.3)
    CWE
    Assigner
    References
    URL Tags
    https://vuldb.com/?id.299059 vdb-entrytechnical-description
    https://vuldb.com/?ctiid.299059 signaturepermissions-required
    https://vuldb.com/?submit.505959 third-party-advisory
    https://github.com/pytorch/pytorch/issues/147722 issue-tracking
    Impacted products
    Vendor Product Version
    n/a PyTorch Affected: 2.6.0+cu124
    Credits
    Default436352 (VulDB User)
    Show details on NVD website
    To clipboard 

    {
  "containers": {
    "adp": [
      {
        "metrics": [
          {
            "other": {
              "content": {
                "id": "CVE-2025-2148",
                "options": [
                  {
                    "Exploitation": "poc"
                  },
                  {
                    "Automatable": "no"
                  },
                  {
                    "Technical Impact": "partial"
                  }
                ],
                "role": "CISA Coordinator",
                "timestamp": "2025-03-10T14:10:27.409283Z",
                "version": "2.0.3"
              },
              "type": "ssvc"
            }
          }
        ],
        "providerMetadata": {
          "dateUpdated": "2025-03-10T14:10:36.958Z",
          "orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
          "shortName": "CISA-ADP"
        },
        "references": [
          {
            "tags": [
              "exploit"
            ],
            "url": "https://github.com/pytorch/pytorch/issues/147722"
          }
        ],
        "title": "CISA ADP Vulnrichment"
      }
    ],
    "cna": {
      "affected": [
        {
          "modules": [
            "Tuple Handler"
          ],
          "product": "PyTorch",
          "vendor": "n/a",
          "versions": [
            {
              "status": "affected",
              "version": "2.6.0+cu124"
            }
          ]
        }
      ],
      "credits": [
        {
          "lang": "en",
          "type": "reporter",
          "value": "Default436352 (VulDB User)"
        }
      ],
      "descriptions": [
        {
          "lang": "en",
          "value": "A vulnerability was found in PyTorch 2.6.0+cu124. It has been declared as critical. Affected by this vulnerability is the function torch.ops.profiler._call_end_callbacks_on_jit_fut of the component Tuple Handler. The manipulation of the argument None leads to memory corruption. The attack can be launched remotely. The complexity of an attack is rather high. The exploitation appears to be difficult."
        },
        {
          "lang": "de",
          "value": "In PyTorch 2.6.0+cu124 wurde eine kritische Schwachstelle ausgemacht. Hierbei betrifft es die Funktion torch.ops.profiler._call_end_callbacks_on_jit_fut der Komponente Tuple Handler. Mit der Manipulation des Arguments None mit unbekannten Daten kann eine memory corruption-Schwachstelle ausgenutzt werden. Umgesetzt werden kann der Angriff \u00fcber das Netzwerk. Die Komplexit\u00e4t eines Angriffs ist eher hoch. Sie gilt als schwierig ausnutzbar."
        }
      ],
      "metrics": [
        {
          "cvssV4_0": {
            "baseScore": 2.3,
            "baseSeverity": "LOW",
            "vectorString": "CVSS:4.0/AV:N/AC:H/AT:N/PR:N/UI:P/VC:L/VI:L/VA:L/SC:N/SI:N/SA:N",
            "version": "4.0"
          }
        },
        {
          "cvssV3_1": {
            "baseScore": 5,
            "baseSeverity": "MEDIUM",
            "vectorString": "CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:L/I:L/A:L",
            "version": "3.1"
          }
        },
        {
          "cvssV3_0": {
            "baseScore": 5,
            "baseSeverity": "MEDIUM",
            "vectorString": "CVSS:3.0/AV:N/AC:H/PR:N/UI:R/S:U/C:L/I:L/A:L",
            "version": "3.0"
          }
        },
        {
          "cvssV2_0": {
            "baseScore": 5.1,
            "vectorString": "AV:N/AC:H/Au:N/C:P/I:P/A:P",
            "version": "2.0"
          }
        }
      ],
      "problemTypes": [
        {
          "descriptions": [
            {
              "cweId": "CWE-119",
              "description": "Memory Corruption",
              "lang": "en",
              "type": "CWE"
            }
          ]
        }
      ],
      "providerMetadata": {
        "dateUpdated": "2025-03-10T12:00:07.912Z",
        "orgId": "1af790b2-7ee1-4545-860a-a788eba489b5",
        "shortName": "VulDB"
      },
      "references": [
        {
          "name": "VDB-299059 | PyTorch Tuple torch.ops.profiler._call_end_callbacks_on_jit_fut memory corruption",
          "tags": [
            "vdb-entry",
            "technical-description"
          ],
          "url": "https://vuldb.com/?id.299059"
        },
        {
          "name": "VDB-299059 | CTI Indicators (IOB, IOC, IOA)",
          "tags": [
            "signature",
            "permissions-required"
          ],
          "url": "https://vuldb.com/?ctiid.299059"
        },
        {
          "name": "Submit #505959 | pytorch 2.6.0+cu124 Segmentation fault",
          "tags": [
            "third-party-advisory"
          ],
          "url": "https://vuldb.com/?submit.505959"
        },
        {
          "tags": [
            "issue-tracking"
          ],
          "url": "https://github.com/pytorch/pytorch/issues/147722"
        }
      ],
      "timeline": [
        {
          "lang": "en",
          "time": "2025-03-10T00:00:00.000Z",
          "value": "Advisory disclosed"
        },
        {
          "lang": "en",
          "time": "2025-03-10T01:00:00.000Z",
          "value": "VulDB entry created"
        },
        {
          "lang": "en",
          "time": "2025-03-10T07:19:04.000Z",
          "value": "VulDB entry last update"
        }
      ],
      "title": "PyTorch Tuple torch.ops.profiler._call_end_callbacks_on_jit_fut memory corruption"
    }
  },
  "cveMetadata": {
    "assignerOrgId": "1af790b2-7ee1-4545-860a-a788eba489b5",
    "assignerShortName": "VulDB",
    "cveId": "CVE-2025-2148",
    "datePublished": "2025-03-10T12:00:07.912Z",
    "dateReserved": "2025-03-10T06:12:36.829Z",
    "dateUpdated": "2025-03-10T14:10:36.958Z",
    "state": "PUBLISHED"
  },
  "dataType": "CVE_RECORD",
  "dataVersion": "5.1"
}

    CVE-2026-24747 (GCVE-0-2026-24747)

    Vulnerability from cvelistv5 – Published: 2026-01-27 21:13 – Updated: 2026-06-30 12:06
    VLAI
    Title
    PyTorch Vulnerable to Remote Code Execution via Untrusted Checkpoint Files
    Summary
    PyTorch is a Python package that provides tensor computation. Prior to version 2.10.0, a vulnerability in PyTorch's `weights_only` unpickler allows an attacker to craft a malicious checkpoint file (`.pth`) that, when loaded with `torch.load(..., weights_only=True)`, can corrupt memory and potentially lead to arbitrary code execution. Version 2.10.0 fixes the issue.
    Severity
    8.8 (High)
    CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
    SSVC
    Exploitation: none Automatable: no Technical Impact: total
    CISA Coordinator (v2.0.3)
    CWE
    • CWE-502 - Deserialization of Untrusted Data
    • CWE-94 - Improper Control of Generation of Code ('Code Injection')
    Assigner
    References
    Impacted products
    Show details on NVD website
    To clipboard 

    {
  "containers": {
    "adp": [
      {
        "metrics": [
          {
            "other": {
              "content": {
                "id": "CVE-2026-24747",
                "options": [
                  {
                    "Exploitation": "none"
                  },
                  {
                    "Automatable": "no"
                  },
                  {
                    "Technical Impact": "total"
                  }
                ],
                "role": "CISA Coordinator",
                "timestamp": "2026-01-30T04:55:40.763016Z",
                "version": "2.0.3"
              },
              "type": "ssvc"
            }
          }
        ],
        "providerMetadata": {
          "dateUpdated": "2026-02-26T15:04:50.008Z",
          "orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
          "shortName": "CISA-ADP"
        },
        "title": "CISA ADP Vulnrichment"
      },
      {
        "affected": [
          {
            "cpes": [
              "cpe:/a:redhat:openshift_ai:2.25::el9"
            ],
            "defaultStatus": "affected",
            "product": "Red Hat OpenShift AI 2.25",
            "vendor": "Red Hat"
          },
          {
            "cpes": [
              "cpe:/a:redhat:openshift_ai"
            ],
            "defaultStatus": "unaffected",
            "product": "Red Hat OpenShift AI (RHOAI)",
            "vendor": "Red Hat"
          }
        ],
        "datePublic": "2026-01-27T21:13:46.878Z",
        "descriptions": [
          {
            "lang": "en",
            "value": "A flaw was found in PyTorch, a Python package for tensor computation. A remote attacker could craft a malicious checkpoint file, which, when loaded using the `weights_only` unpickler, could lead to memory corruption. This vulnerability may enable an attacker to achieve arbitrary code execution on the affected system."
          }
        ],
        "metrics": [
          {
            "other": {
              "content": {
                "namespace": "https://access.redhat.com/security/updates/classification/",
                "value": "Important"
              },
              "type": "Red Hat severity rating"
            }
          },
          {
            "cvssV3_1": {
              "attackComplexity": "LOW",
              "attackVector": "NETWORK",
              "availabilityImpact": "HIGH",
              "baseScore": 8.8,
              "baseSeverity": "HIGH",
              "confidentialityImpact": "HIGH",
              "integrityImpact": "HIGH",
              "privilegesRequired": "NONE",
              "scope": "UNCHANGED",
              "userInteraction": "REQUIRED",
              "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H",
              "version": "3.1"
            },
            "format": "CVSS"
          }
        ],
        "problemTypes": [
          {
            "descriptions": [
              {
                "cweId": "CWE-502",
                "description": "Deserialization of Untrusted Data",
                "lang": "en",
                "type": "CWE"
              }
            ]
          }
        ],
        "providerMetadata": {
          "dateUpdated": "2026-06-30T12:06:37.429Z",
          "orgId": "0b0ca135-0b70-47e7-9f44-1890c2a1c46c",
          "shortName": "redhat-SADP"
        },
        "references": [
          {
            "tags": [
              "vdb-entry",
              "x_refsource_REDHAT"
            ],
            "url": "https://access.redhat.com/security/cve/CVE-2026-24747"
          },
          {
            "name": "RHBZ#2433612",
            "tags": [
              "issue-tracking",
              "x_refsource_REDHAT"
            ],
            "url": "https://bugzilla.redhat.com/show_bug.cgi?id=2433612"
          },
          {
            "tags": [
              "x_sadp-csaf-vex"
            ],
            "url": "https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-24747.json"
          },
          {
            "tags": [
              "vendor-advisory",
              "x_refsource_REDHAT"
            ],
            "url": "https://access.redhat.com/errata/RHSA-2026:24977"
          }
        ],
        "solutions": [
          {
            "lang": "en",
            "value": "RHSA-2026:24977: Red Hat OpenShift AI 2.25"
          }
        ],
        "timeline": [
          {
            "lang": "en",
            "time": "2026-01-27T22:01:52.649Z",
            "value": "Reported to Red Hat."
          },
          {
            "lang": "en",
            "time": "2026-01-27T21:13:46.878Z",
            "value": "Made public."
          }
        ],
        "title": "pytorch: PyTorch: Arbitrary code execution via malicious checkpoint file loading",
        "x_adpType": "supplier",
        "x_generator": {
          "engine": "sadp-cli 1.0.0"
        }
      }
    ],
    "cna": {
      "affected": [
        {
          "product": "pytorch",
          "vendor": "pytorch",
          "versions": [
            {
              "status": "affected",
              "version": "\u003c 2.10.0"
            }
          ]
        }
      ],
      "descriptions": [
        {
          "lang": "en",
          "value": "PyTorch is a Python package that provides tensor computation. Prior to version 2.10.0, a vulnerability in PyTorch\u0027s `weights_only` unpickler allows an attacker to craft a malicious checkpoint file (`.pth`) that, when loaded with `torch.load(..., weights_only=True)`, can corrupt memory and potentially lead to arbitrary code execution. Version 2.10.0 fixes the issue."
        }
      ],
      "metrics": [
        {
          "cvssV3_1": {
            "attackComplexity": "LOW",
            "attackVector": "NETWORK",
            "availabilityImpact": "HIGH",
            "baseScore": 8.8,
            "baseSeverity": "HIGH",
            "confidentialityImpact": "HIGH",
            "integrityImpact": "HIGH",
            "privilegesRequired": "NONE",
            "scope": "UNCHANGED",
            "userInteraction": "REQUIRED",
            "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H",
            "version": "3.1"
          }
        }
      ],
      "problemTypes": [
        {
          "descriptions": [
            {
              "cweId": "CWE-502",
              "description": "CWE-502: Deserialization of Untrusted Data",
              "lang": "en",
              "type": "CWE"
            }
          ]
        },
        {
          "descriptions": [
            {
              "cweId": "CWE-94",
              "description": "CWE-94: Improper Control of Generation of Code (\u0027Code Injection\u0027)",
              "lang": "en",
              "type": "CWE"
            }
          ]
        }
      ],
      "providerMetadata": {
        "dateUpdated": "2026-01-27T21:13:46.878Z",
        "orgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
        "shortName": "GitHub_M"
      },
      "references": [
        {
          "name": "https://github.com/pytorch/pytorch/security/advisories/GHSA-63cw-57p8-fm3p",
          "tags": [
            "x_refsource_CONFIRM"
          ],
          "url": "https://github.com/pytorch/pytorch/security/advisories/GHSA-63cw-57p8-fm3p"
        },
        {
          "name": "https://github.com/pytorch/pytorch/issues/163105",
          "tags": [
            "x_refsource_MISC"
          ],
          "url": "https://github.com/pytorch/pytorch/issues/163105"
        },
        {
          "name": "https://github.com/pytorch/pytorch/163122/commit/954dc5183ee9205cbe79876ad05dd2d9ae752139",
          "tags": [
            "x_refsource_MISC"
          ],
          "url": "https://github.com/pytorch/pytorch/163122/commit/954dc5183ee9205cbe79876ad05dd2d9ae752139"
        },
        {
          "name": "https://github.com/pytorch/pytorch/releases/tag/v2.10.0",
          "tags": [
            "x_refsource_MISC"
          ],
          "url": "https://github.com/pytorch/pytorch/releases/tag/v2.10.0"
        }
      ],
      "source": {
        "advisory": "GHSA-63cw-57p8-fm3p",
        "discovery": "UNKNOWN"
      },
      "title": "PyTorch Vulnerable to Remote Code Execution via Untrusted Checkpoint Files"
    }
  },
  "cveMetadata": {
    "assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
    "assignerShortName": "GitHub_M",
    "cveId": "CVE-2026-24747",
    "datePublished": "2026-01-27T21:13:46.878Z",
    "dateReserved": "2026-01-26T19:06:16.059Z",
    "dateUpdated": "2026-06-30T12:06:37.429Z",
    "state": "PUBLISHED"
  },
  "dataType": "CVE_RECORD",
  "dataVersion": "5.2"
}

    CVE-2025-32434 (GCVE-0-2025-32434)

    Vulnerability from cvelistv5 – Published: 2025-04-18 15:48 – Updated: 2025-12-01 07:05
    VLAI
    Title
    PyTorch: `torch.load` with `weights_only=True` leads to remote code execution
    Summary
    PyTorch is a Python package that provides tensor computation with strong GPU acceleration and deep neural networks built on a tape-based autograd system. In version 2.5.1 and prior, a Remote Command Execution (RCE) vulnerability exists in PyTorch when loading a model using torch.load with weights_only=True. This issue has been patched in version 2.6.0.
    Severity
    9.3 (Critical)
    CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N
    SSVC
    Exploitation: none Automatable: yes Technical Impact: total
    CISA Coordinator (v2.0.3)
    CWE
    • CWE-502 - Deserialization of Untrusted Data
    Assigner
    References
    Impacted products
    Vendor Product Version
    pytorch pytorch Affected: < 2.6.0
    		Create a notification for this product.
    Show details on NVD website
    To clipboard 

    {
  "containers": {
    "adp": [
      {
        "metrics": [
          {
            "other": {
              "content": {
                "id": "CVE-2025-32434",
                "options": [
                  {
                    "Exploitation": "none"
                  },
                  {
                    "Automatable": "yes"
                  },
                  {
                    "Technical Impact": "total"
                  }
                ],
                "role": "CISA Coordinator",
                "timestamp": "2025-04-18T16:06:40.000632Z",
                "version": "2.0.3"
              },
              "type": "ssvc"
            }
          }
        ],
        "providerMetadata": {
          "dateUpdated": "2025-04-18T16:06:51.966Z",
          "orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
          "shortName": "CISA-ADP"
        },
        "title": "CISA ADP Vulnrichment"
      },
      {
        "providerMetadata": {
          "dateUpdated": "2025-12-01T07:05:28.923Z",
          "orgId": "af854a3a-2127-422b-91ae-364da2661108",
          "shortName": "CVE"
        },
        "references": [
          {
            "url": "https://lists.debian.org/debian-lts-announce/2025/12/msg00000.html"
          }
        ],
        "title": "CVE Program Container"
      }
    ],
    "cna": {
      "affected": [
        {
          "product": "pytorch",
          "vendor": "pytorch",
          "versions": [
            {
              "status": "affected",
              "version": "\u003c 2.6.0"
            }
          ]
        }
      ],
      "descriptions": [
        {
          "lang": "en",
          "value": "PyTorch is a Python package that provides tensor computation with strong GPU acceleration and deep neural networks built on a tape-based autograd system. In version 2.5.1 and prior, a Remote Command Execution (RCE) vulnerability exists in PyTorch when loading a model using torch.load with weights_only=True. This issue has been patched in version 2.6.0."
        }
      ],
      "metrics": [
        {
          "cvssV4_0": {
            "attackComplexity": "LOW",
            "attackRequirements": "NONE",
            "attackVector": "NETWORK",
            "baseScore": 9.3,
            "baseSeverity": "CRITICAL",
            "privilegesRequired": "NONE",
            "subAvailabilityImpact": "NONE",
            "subConfidentialityImpact": "NONE",
            "subIntegrityImpact": "NONE",
            "userInteraction": "NONE",
            "vectorString": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N",
            "version": "4.0",
            "vulnAvailabilityImpact": "HIGH",
            "vulnConfidentialityImpact": "HIGH",
            "vulnIntegrityImpact": "HIGH"
          }
        }
      ],
      "problemTypes": [
        {
          "descriptions": [
            {
              "cweId": "CWE-502",
              "description": "CWE-502: Deserialization of Untrusted Data",
              "lang": "en",
              "type": "CWE"
            }
          ]
        }
      ],
      "providerMetadata": {
        "dateUpdated": "2025-04-18T15:48:18.851Z",
        "orgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
        "shortName": "GitHub_M"
      },
      "references": [
        {
          "name": "https://github.com/pytorch/pytorch/security/advisories/GHSA-53q9-r3pm-6pq6",
          "tags": [
            "x_refsource_CONFIRM"
          ],
          "url": "https://github.com/pytorch/pytorch/security/advisories/GHSA-53q9-r3pm-6pq6"
        }
      ],
      "source": {
        "advisory": "GHSA-53q9-r3pm-6pq6",
        "discovery": "UNKNOWN"
      },
      "title": "PyTorch: `torch.load` with `weights_only=True` leads to remote code execution"
    }
  },
  "cveMetadata": {
    "assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
    "assignerShortName": "GitHub_M",
    "cveId": "CVE-2025-32434",
    "datePublished": "2025-04-18T15:48:18.851Z",
    "dateReserved": "2025-04-08T10:54:58.368Z",
    "dateUpdated": "2025-12-01T07:05:28.923Z",
    "state": "PUBLISHED"
  },
  "dataType": "CVE_RECORD",
  "dataVersion": "5.2"
}

    CVE-2025-2149 (GCVE-0-2025-2149)

    Vulnerability from cvelistv5 – Published: 2025-03-10 12:31 – Updated: 2025-03-10 14:08
    VLAI
    Title
    PyTorch Quantized Sigmoid Module nnq_Sigmoid initialization
    Summary
    A vulnerability was found in PyTorch 2.6.0+cu124. It has been rated as problematic. Affected by this issue is the function nnq_Sigmoid of the component Quantized Sigmoid Module. The manipulation of the argument scale/zero_point leads to improper initialization. The attack needs to be approached locally. The complexity of an attack is rather high. The exploitation is known to be difficult. The exploit has been disclosed to the public and may be used.
    Severity
    2 (Low)
    CVSS:4.0/AV:L/AC:H/AT:N/PR:L/UI:N/VC:N/VI:L/VA:N/SC:N/SI:N/SA:N
    2.5 (Low)
    CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:L/A:N
    2.5 (Low)
    CVSS:3.0/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:L/A:N
    SSVC
    Exploitation: poc Automatable: no Technical Impact: partial
    CISA Coordinator (v2.0.3)
    CWE
    • CWE-665 - Improper Initialization
    Assigner
    References
    URL Tags
    https://vuldb.com/?id.299060 vdb-entrytechnical-description
    https://vuldb.com/?ctiid.299060 signaturepermissions-required
    https://vuldb.com/?submit.506563 third-party-advisory
    https://github.com/pytorch/pytorch/issues/147818 issue-tracking
    https://github.com/pytorch/pytorch/issues/147818#… exploitissue-tracking
    Impacted products
    Vendor Product Version
    n/a PyTorch Affected: 2.6.0+cu124
    Credits
    Default436352 (VulDB User)
    Show details on NVD website
    To clipboard 

    {
  "containers": {
    "adp": [
      {
        "metrics": [
          {
            "other": {
              "content": {
                "id": "CVE-2025-2149",
                "options": [
                  {
                    "Exploitation": "poc"
                  },
                  {
                    "Automatable": "no"
                  },
                  {
                    "Technical Impact": "partial"
                  }
                ],
                "role": "CISA Coordinator",
                "timestamp": "2025-03-10T14:08:09.193144Z",
                "version": "2.0.3"
              },
              "type": "ssvc"
            }
          }
        ],
        "providerMetadata": {
          "dateUpdated": "2025-03-10T14:08:14.533Z",
          "orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
          "shortName": "CISA-ADP"
        },
        "references": [
          {
            "tags": [
              "exploit"
            ],
            "url": "https://github.com/pytorch/pytorch/issues/147818#issue-2877301660"
          },
          {
            "tags": [
              "exploit"
            ],
            "url": "https://github.com/pytorch/pytorch/issues/147818"
          }
        ],
        "title": "CISA ADP Vulnrichment"
      }
    ],
    "cna": {
      "affected": [
        {
          "modules": [
            "Quantized Sigmoid Module"
          ],
          "product": "PyTorch",
          "vendor": "n/a",
          "versions": [
            {
              "status": "affected",
              "version": "2.6.0+cu124"
            }
          ]
        }
      ],
      "credits": [
        {
          "lang": "en",
          "type": "reporter",
          "value": "Default436352 (VulDB User)"
        }
      ],
      "descriptions": [
        {
          "lang": "en",
          "value": "A vulnerability was found in PyTorch 2.6.0+cu124. It has been rated as problematic. Affected by this issue is the function nnq_Sigmoid of the component Quantized Sigmoid Module. The manipulation of the argument scale/zero_point leads to improper initialization. The attack needs to be approached locally. The complexity of an attack is rather high. The exploitation is known to be difficult. The exploit has been disclosed to the public and may be used."
        },
        {
          "lang": "de",
          "value": "Eine problematische Schwachstelle wurde in PyTorch 2.6.0+cu124 ausgemacht. Davon betroffen ist die Funktion nnq_Sigmoid der Komponente Quantized Sigmoid Module. Durch die Manipulation des Arguments scale/zero_point mit unbekannten Daten kann eine improper initialization-Schwachstelle ausgenutzt werden. Der Angriff muss lokal passieren. Die Komplexit\u00e4t eines Angriffs ist eher hoch. Sie ist schwierig ausnutzbar. Der Exploit steht zur \u00f6ffentlichen Verf\u00fcgung."
        }
      ],
      "metrics": [
        {
          "cvssV4_0": {
            "baseScore": 2,
            "baseSeverity": "LOW",
            "vectorString": "CVSS:4.0/AV:L/AC:H/AT:N/PR:L/UI:N/VC:N/VI:L/VA:N/SC:N/SI:N/SA:N",
            "version": "4.0"
          }
        },
        {
          "cvssV3_1": {
            "baseScore": 2.5,
            "baseSeverity": "LOW",
            "vectorString": "CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:L/A:N",
            "version": "3.1"
          }
        },
        {
          "cvssV3_0": {
            "baseScore": 2.5,
            "baseSeverity": "LOW",
            "vectorString": "CVSS:3.0/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:L/A:N",
            "version": "3.0"
          }
        },
        {
          "cvssV2_0": {
            "baseScore": 1,
            "vectorString": "AV:L/AC:H/Au:S/C:N/I:P/A:N",
            "version": "2.0"
          }
        }
      ],
      "problemTypes": [
        {
          "descriptions": [
            {
              "cweId": "CWE-665",
              "description": "Improper Initialization",
              "lang": "en",
              "type": "CWE"
            }
          ]
        }
      ],
      "providerMetadata": {
        "dateUpdated": "2025-03-10T12:31:04.788Z",
        "orgId": "1af790b2-7ee1-4545-860a-a788eba489b5",
        "shortName": "VulDB"
      },
      "references": [
        {
          "name": "VDB-299060 | PyTorch Quantized Sigmoid Module nnq_Sigmoid initialization",
          "tags": [
            "vdb-entry",
            "technical-description"
          ],
          "url": "https://vuldb.com/?id.299060"
        },
        {
          "name": "VDB-299060 | CTI Indicators (IOB, IOC, IOA)",
          "tags": [
            "signature",
            "permissions-required"
          ],
          "url": "https://vuldb.com/?ctiid.299060"
        },
        {
          "name": "Submit #506563 | pytorch 2.6.0+cu124 Inconsistency Between Implementation and Documented Design",
          "tags": [
            "third-party-advisory"
          ],
          "url": "https://vuldb.com/?submit.506563"
        },
        {
          "tags": [
            "issue-tracking"
          ],
          "url": "https://github.com/pytorch/pytorch/issues/147818"
        },
        {
          "tags": [
            "exploit",
            "issue-tracking"
          ],
          "url": "https://github.com/pytorch/pytorch/issues/147818#issue-2877301660"
        }
      ],
      "timeline": [
        {
          "lang": "en",
          "time": "2025-03-10T00:00:00.000Z",
          "value": "Advisory disclosed"
        },
        {
          "lang": "en",
          "time": "2025-03-10T01:00:00.000Z",
          "value": "VulDB entry created"
        },
        {
          "lang": "en",
          "time": "2025-03-10T07:19:09.000Z",
          "value": "VulDB entry last update"
        }
      ],
      "title": "PyTorch Quantized Sigmoid Module nnq_Sigmoid initialization"
    }
  },
  "cveMetadata": {
    "assignerOrgId": "1af790b2-7ee1-4545-860a-a788eba489b5",
    "assignerShortName": "VulDB",
    "cveId": "CVE-2025-2149",
    "datePublished": "2025-03-10T12:31:04.788Z",
    "dateReserved": "2025-03-10T06:13:15.319Z",
    "dateUpdated": "2025-03-10T14:08:14.533Z",
    "state": "PUBLISHED"
  },
  "dataType": "CVE_RECORD",
  "dataVersion": "5.1"
}

    CVE-2025-2148 (GCVE-0-2025-2148)

    Vulnerability from cvelistv5 – Published: 2025-03-10 12:00 – Updated: 2025-03-10 14:10
    VLAI
    Title
    PyTorch Tuple torch.ops.profiler._call_end_callbacks_on_jit_fut memory corruption
    Summary
    A vulnerability was found in PyTorch 2.6.0+cu124. It has been declared as critical. Affected by this vulnerability is the function torch.ops.profiler._call_end_callbacks_on_jit_fut of the component Tuple Handler. The manipulation of the argument None leads to memory corruption. The attack can be launched remotely. The complexity of an attack is rather high. The exploitation appears to be difficult.
    Severity
    2.3 (Low)
    CVSS:4.0/AV:N/AC:H/AT:N/PR:N/UI:P/VC:L/VI:L/VA:L/SC:N/SI:N/SA:N
    5 (Medium)
    CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:L/I:L/A:L
    5 (Medium)
    CVSS:3.0/AV:N/AC:H/PR:N/UI:R/S:U/C:L/I:L/A:L
    SSVC
    Exploitation: poc Automatable: no Technical Impact: partial
    CISA Coordinator (v2.0.3)
    CWE
    Assigner
    References
    URL Tags
    https://vuldb.com/?id.299059 vdb-entrytechnical-description
    https://vuldb.com/?ctiid.299059 signaturepermissions-required
    https://vuldb.com/?submit.505959 third-party-advisory
    https://github.com/pytorch/pytorch/issues/147722 issue-tracking
    Impacted products
    Vendor Product Version
    n/a PyTorch Affected: 2.6.0+cu124
    Credits
    Default436352 (VulDB User)
    Show details on NVD website
    To clipboard 

    {
  "containers": {
    "adp": [
      {
        "metrics": [
          {
            "other": {
              "content": {
                "id": "CVE-2025-2148",
                "options": [
                  {
                    "Exploitation": "poc"
                  },
                  {
                    "Automatable": "no"
                  },
                  {
                    "Technical Impact": "partial"
                  }
                ],
                "role": "CISA Coordinator",
                "timestamp": "2025-03-10T14:10:27.409283Z",
                "version": "2.0.3"
              },
              "type": "ssvc"
            }
          }
        ],
        "providerMetadata": {
          "dateUpdated": "2025-03-10T14:10:36.958Z",
          "orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
          "shortName": "CISA-ADP"
        },
        "references": [
          {
            "tags": [
              "exploit"
            ],
            "url": "https://github.com/pytorch/pytorch/issues/147722"
          }
        ],
        "title": "CISA ADP Vulnrichment"
      }
    ],
    "cna": {
      "affected": [
        {
          "modules": [
            "Tuple Handler"
          ],
          "product": "PyTorch",
          "vendor": "n/a",
          "versions": [
            {
              "status": "affected",
              "version": "2.6.0+cu124"
            }
          ]
        }
      ],
      "credits": [
        {
          "lang": "en",
          "type": "reporter",
          "value": "Default436352 (VulDB User)"
        }
      ],
      "descriptions": [
        {
          "lang": "en",
          "value": "A vulnerability was found in PyTorch 2.6.0+cu124. It has been declared as critical. Affected by this vulnerability is the function torch.ops.profiler._call_end_callbacks_on_jit_fut of the component Tuple Handler. The manipulation of the argument None leads to memory corruption. The attack can be launched remotely. The complexity of an attack is rather high. The exploitation appears to be difficult."
        },
        {
          "lang": "de",
          "value": "In PyTorch 2.6.0+cu124 wurde eine kritische Schwachstelle ausgemacht. Hierbei betrifft es die Funktion torch.ops.profiler._call_end_callbacks_on_jit_fut der Komponente Tuple Handler. Mit der Manipulation des Arguments None mit unbekannten Daten kann eine memory corruption-Schwachstelle ausgenutzt werden. Umgesetzt werden kann der Angriff \u00fcber das Netzwerk. Die Komplexit\u00e4t eines Angriffs ist eher hoch. Sie gilt als schwierig ausnutzbar."
        }
      ],
      "metrics": [
        {
          "cvssV4_0": {
            "baseScore": 2.3,
            "baseSeverity": "LOW",
            "vectorString": "CVSS:4.0/AV:N/AC:H/AT:N/PR:N/UI:P/VC:L/VI:L/VA:L/SC:N/SI:N/SA:N",
            "version": "4.0"
          }
        },
        {
          "cvssV3_1": {
            "baseScore": 5,
            "baseSeverity": "MEDIUM",
            "vectorString": "CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:L/I:L/A:L",
            "version": "3.1"
          }
        },
        {
          "cvssV3_0": {
            "baseScore": 5,
            "baseSeverity": "MEDIUM",
            "vectorString": "CVSS:3.0/AV:N/AC:H/PR:N/UI:R/S:U/C:L/I:L/A:L",
            "version": "3.0"
          }
        },
        {
          "cvssV2_0": {
            "baseScore": 5.1,
            "vectorString": "AV:N/AC:H/Au:N/C:P/I:P/A:P",
            "version": "2.0"
          }
        }
      ],
      "problemTypes": [
        {
          "descriptions": [
            {
              "cweId": "CWE-119",
              "description": "Memory Corruption",
              "lang": "en",
              "type": "CWE"
            }
          ]
        }
      ],
      "providerMetadata": {
        "dateUpdated": "2025-03-10T12:00:07.912Z",
        "orgId": "1af790b2-7ee1-4545-860a-a788eba489b5",
        "shortName": "VulDB"
      },
      "references": [
        {
          "name": "VDB-299059 | PyTorch Tuple torch.ops.profiler._call_end_callbacks_on_jit_fut memory corruption",
          "tags": [
            "vdb-entry",
            "technical-description"
          ],
          "url": "https://vuldb.com/?id.299059"
        },
        {
          "name": "VDB-299059 | CTI Indicators (IOB, IOC, IOA)",
          "tags": [
            "signature",
            "permissions-required"
          ],
          "url": "https://vuldb.com/?ctiid.299059"
        },
        {
          "name": "Submit #505959 | pytorch 2.6.0+cu124 Segmentation fault",
          "tags": [
            "third-party-advisory"
          ],
          "url": "https://vuldb.com/?submit.505959"
        },
        {
          "tags": [
            "issue-tracking"
          ],
          "url": "https://github.com/pytorch/pytorch/issues/147722"
        }
      ],
      "timeline": [
        {
          "lang": "en",
          "time": "2025-03-10T00:00:00.000Z",
          "value": "Advisory disclosed"
        },
        {
          "lang": "en",
          "time": "2025-03-10T01:00:00.000Z",
          "value": "VulDB entry created"
        },
        {
          "lang": "en",
          "time": "2025-03-10T07:19:04.000Z",
          "value": "VulDB entry last update"
        }
      ],
      "title": "PyTorch Tuple torch.ops.profiler._call_end_callbacks_on_jit_fut memory corruption"
    }
  },
  "cveMetadata": {
    "assignerOrgId": "1af790b2-7ee1-4545-860a-a788eba489b5",
    "assignerShortName": "VulDB",
    "cveId": "CVE-2025-2148",
    "datePublished": "2025-03-10T12:00:07.912Z",
    "dateReserved": "2025-03-10T06:12:36.829Z",
    "dateUpdated": "2025-03-10T14:10:36.958Z",
    "state": "PUBLISHED"
  },
  "dataType": "CVE_RECORD",
  "dataVersion": "5.1"
}

    AVID-2023-V015

    Vulnerability from avid – Published: 2023-03-31 – Updated: 2023-03-31 ATLAS Case Study
    Summary
    Linux packages for PyTorch's pre-release version, called Pytorch-nightly, were compromised from December 25 to 30, 2022 by a malicious binary uploaded to the Python Package Index (PyPI) code repository. The malicious binary had the same name as a PyTorch dependency and the PyPI package manager (pip) installed this malicious package instead of the legitimate one. This supply chain attack, also known as "dependency confusion," exposed sensitive information of Linux machines with the affected pip-installed versions of PyTorch-nightly. On December 30, 2022, PyTorch announced the incident and initial steps towards mitigation, including the rename and removal of `torchtriton` dependencies.
    Risk domain
    Security
    SEP view
    S0202: Software Compromise
    Lifecycle
    L02: Data Understanding, L03: Data Preparation, L04: Model Development, L05: Evaluation, L06: Deployment
    Organisations
    PyTorch (deployer)
    Affected artifacts
    Artifact Type
    PyTorch System
    References
    URL Label
    https://atlas.mitre.org/studies/AML.CS0015 Compromised PyTorch Dependency Chain
    https://pytorch.org/blog/compromised-nightly-depe… PyTorch statement on compromised dependency
    https://www.bleepingcomputer.com/news/security/py… Analysis by BleepingComputer
    To clipboard 

    {
  "affects": {
    "artifacts": [
      {
        "name": "PyTorch",
        "type": "System"
      }
    ],
    "deployer": [
      "PyTorch"
    ],
    "developer": []
  },
  "credit": [
    {
      "lang": "eng",
      "value": "PyTorch"
    }
  ],
  "data_type": "AVID",
  "data_version": "0.2",
  "description": {
    "lang": "eng",
    "value": "Linux packages for PyTorch\u0027s pre-release version, called Pytorch-nightly, were compromised from December 25 to 30, 2022 by a malicious binary uploaded to the Python Package Index (PyPI) code repository.  The malicious binary had the same name as a PyTorch dependency and the PyPI package manager (pip) installed this malicious package instead of the legitimate one.\n\nThis supply chain attack, also known as \"dependency confusion,\" exposed sensitive information of Linux machines with the affected pip-installed versions of PyTorch-nightly. On December 30, 2022, PyTorch announced the incident and initial steps towards mitigation, including the rename and removal of `torchtriton` dependencies."
  },
  "impact": {
    "avid": {
      "lifecycle_view": [
        "L02: Data Understanding",
        "L03: Data Preparation",
        "L04: Model Development",
        "L05: Evaluation",
        "L06: Deployment"
      ],
      "risk_domain": [
        "Security"
      ],
      "sep_view": [
        "S0202: Software Compromise"
      ],
      "taxonomy_version": "0.2"
    }
  },
  "last_modified_date": "2023-03-31",
  "metadata": {
    "vuln_id": "AVID-2023-V015"
  },
  "problemtype": {
    "classof": "ATLAS Case Study",
    "description": {
      "lang": "eng",
      "value": "Compromised PyTorch Dependency Chain"
    },
    "type": "Advisory"
  },
  "published_date": "2023-03-31",
  "references": [
    {
      "label": "Compromised PyTorch Dependency Chain",
      "type": "source",
      "url": "https://atlas.mitre.org/studies/AML.CS0015"
    },
    {
      "label": "PyTorch statement on compromised dependency",
      "type": "source",
      "url": "https://pytorch.org/blog/compromised-nightly-dependency/"
    },
    {
      "label": "Analysis by BleepingComputer",
      "type": "source",
      "url": "https://www.bleepingcomputer.com/news/security/pytorch-discloses-malicious-dependency-chain-compromise-over-holidays/"
    }
  ],
  "reports": null
}