CVE-2026-63632 (GCVE-0-2026-63632)

Vulnerability from cvelistv5 – Published: 2026-08-18 14:55 – Updated: 2026-08-18 18:51
VLAI
Title
ONNX: Heap-Buffer-Overflow READ in Gemm Version Converter Adapter via Undersized Input Shape
Summary
Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. From 1.3.0 until 1.22.0, onnx.version_converter.convert_version() can perform an out-of-bounds read in Gemm_7_6::adapt_gemm_7_6() in onnx/version_converter/adapters/gemm_7_6.h when a Gemm node has input tensors with fewer than two dimensions because B_shape[1], A_shape[0], or A_shape[1] is accessed without a rank check, potentially causing a process crash during an opset 7 to 6 downgrade. This issue is fixed in version 1.22.0.
SSVC
Exploitation: poc Automatable: no Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-08-18 18:51 UTC
CWE
Impacted products
Vendor Product Version CPE status
onnx onnx Affected: >= 1.3.0, < 1.22.0
guessed Create a notification for this product.
Show details on NVD website

{
  "containers": {
    "adp": [
      {
        "metrics": [
          {
            "other": {
              "content": {
                "id": "CVE-2026-63632",
                "options": [
                  {
                    "Exploitation": "poc"
                  },
                  {
                    "Automatable": "no"
                  },
                  {
                    "Technical Impact": "partial"
                  }
                ],
                "role": "CISA Coordinator",
                "timestamp": "2026-08-18T18:51:22.894530Z",
                "version": "2.0.3"
              },
              "type": "ssvc"
            }
          }
        ],
        "providerMetadata": {
          "dateUpdated": "2026-08-18T18:51:29.068Z",
          "orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
          "shortName": "CISA-ADP"
        },
        "references": [
          {
            "tags": [
              "exploit"
            ],
            "url": "https://github.com/onnx/onnx/security/advisories/GHSA-p893-rvq9-2xf9"
          }
        ],
        "title": "CISA ADP Vulnrichment"
      }
    ],
    "cna": {
      "affected": [
        {
          "product": "onnx",
          "vendor": "onnx",
          "versions": [
            {
              "status": "affected",
              "version": "\u003e= 1.3.0, \u003c 1.22.0"
            }
          ]
        }
      ],
      "descriptions": [
        {
          "lang": "en",
          "value": "Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. From 1.3.0 until 1.22.0, onnx.version_converter.convert_version() can perform an out-of-bounds read in Gemm_7_6::adapt_gemm_7_6() in onnx/version_converter/adapters/gemm_7_6.h when a Gemm node has input tensors with fewer than two dimensions because B_shape[1], A_shape[0], or A_shape[1] is accessed without a rank check, potentially causing a process crash during an opset 7 to 6 downgrade. This issue is fixed in version 1.22.0."
        }
      ],
      "metrics": [
        {
          "cvssV3_1": {
            "attackComplexity": "LOW",
            "attackVector": "LOCAL",
            "availabilityImpact": "LOW",
            "baseScore": 3.3,
            "baseSeverity": "LOW",
            "confidentialityImpact": "NONE",
            "integrityImpact": "NONE",
            "privilegesRequired": "NONE",
            "scope": "UNCHANGED",
            "userInteraction": "REQUIRED",
            "vectorString": "CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:L",
            "version": "3.1"
          }
        }
      ],
      "problemTypes": [
        {
          "descriptions": [
            {
              "cweId": "CWE-125",
              "description": "CWE-125: Out-of-bounds Read",
              "lang": "en",
              "type": "CWE"
            }
          ]
        }
      ],
      "providerMetadata": {
        "dateUpdated": "2026-08-18T14:55:15.923Z",
        "orgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
        "shortName": "GitHub_M"
      },
      "references": [
        {
          "name": "https://github.com/onnx/onnx/security/advisories/GHSA-p893-rvq9-2xf9",
          "tags": [
            "x_refsource_CONFIRM"
          ],
          "url": "https://github.com/onnx/onnx/security/advisories/GHSA-p893-rvq9-2xf9"
        },
        {
          "name": "https://github.com/onnx/onnx/pull/7880",
          "tags": [
            "x_refsource_MISC"
          ],
          "url": "https://github.com/onnx/onnx/pull/7880"
        },
        {
          "name": "https://github.com/onnx/onnx/commit/e9c74f596eaa0250f89e52a54160a25bbcb25b66",
          "tags": [
            "x_refsource_MISC"
          ],
          "url": "https://github.com/onnx/onnx/commit/e9c74f596eaa0250f89e52a54160a25bbcb25b66"
        },
        {
          "name": "https://github.com/onnx/onnx/releases/tag/v1.22.0",
          "tags": [
            "x_refsource_MISC"
          ],
          "url": "https://github.com/onnx/onnx/releases/tag/v1.22.0"
        }
      ],
      "source": {
        "advisory": "GHSA-p893-rvq9-2xf9",
        "discovery": "UNKNOWN"
      },
      "title": "ONNX: Heap-Buffer-Overflow READ in Gemm Version Converter Adapter via Undersized Input Shape"
    }
  },
  "cveMetadata": {
    "assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
    "assignerShortName": "GitHub_M",
    "cveId": "CVE-2026-63632",
    "datePublished": "2026-08-18T14:55:15.923Z",
    "dateReserved": "2026-07-17T14:11:15.482Z",
    "dateUpdated": "2026-08-18T18:51:29.068Z",
    "state": "PUBLISHED"
  },
  "dataType": "CVE_RECORD",
  "dataVersion": "5.2",
  "vulnerability-lookup:meta": {
    "nvd": "{\"cve\":{\"id\":\"CVE-2026-63632\",\"sourceIdentifier\":\"security-advisories@github.com\",\"published\":\"2026-08-18T15:16:56.463\",\"lastModified\":\"2026-08-18T15:16:56.463\",\"vulnStatus\":\"Received\",\"cveTags\":[],\"descriptions\":[{\"lang\":\"en\",\"value\":\"Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. From 1.3.0 until 1.22.0, onnx.version_converter.convert_version() can perform an out-of-bounds read in Gemm_7_6::adapt_gemm_7_6() in onnx/version_converter/adapters/gemm_7_6.h when a Gemm node has input tensors with fewer than two dimensions because B_shape[1], A_shape[0], or A_shape[1] is accessed without a rank check, potentially causing a process crash during an opset 7 to 6 downgrade. This issue is fixed in version 1.22.0.\"}],\"affected\":[{\"source\":\"security-advisories@github.com\",\"affectedData\":[{\"vendor\":\"onnx\",\"product\":\"onnx\",\"versions\":[{\"version\":\"\u003e= 1.3.0, \u003c 1.22.0\",\"status\":\"affected\"}]}]}],\"metrics\":{\"cvssMetricV31\":[{\"source\":\"security-advisories@github.com\",\"type\":\"Secondary\",\"cvssData\":{\"version\":\"3.1\",\"vectorString\":\"CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:L\",\"baseScore\":3.3,\"baseSeverity\":\"LOW\",\"attackVector\":\"LOCAL\",\"attackComplexity\":\"LOW\",\"privilegesRequired\":\"NONE\",\"userInteraction\":\"REQUIRED\",\"scope\":\"UNCHANGED\",\"confidentialityImpact\":\"NONE\",\"integrityImpact\":\"NONE\",\"availabilityImpact\":\"LOW\"},\"exploitabilityScore\":1.8,\"impactScore\":1.4}]},\"weaknesses\":[{\"source\":\"security-advisories@github.com\",\"type\":\"Primary\",\"description\":[{\"lang\":\"en\",\"value\":\"CWE-125\"}]}],\"references\":[{\"url\":\"https://github.com/onnx/onnx/commit/e9c74f596eaa0250f89e52a54160a25bbcb25b66\",\"source\":\"security-advisories@github.com\"},{\"url\":\"https://github.com/onnx/onnx/pull/7880\",\"source\":\"security-advisories@github.com\"},{\"url\":\"https://github.com/onnx/onnx/releases/tag/v1.22.0\",\"source\":\"security-advisories@github.com\"},{\"url\":\"https://github.com/onnx/onnx/security/advisories/GHSA-p893-rvq9-2xf9\",\"source\":\"security-advisories@github.com\"}]}}"
  }
}



Log in or create an account to share your comment.




Tags
Taxonomy of the tags.


Loading…

Loading…

Loading…

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.

Loading…

Detection rules are retrieved from Rulezet.

Loading…

Loading…

Loading…