CVE-2026-115922 (GCVE-0-2026-115922)

Vulnerability from cvelistv5 – Published: 2026-10-26 17:31 – Updated: 2026-10-26 17:31
VLAI
Title
ONNX: Denial of service via unchecked expansion of packed sub-byte tensors in ONNX Python APIs
Summary
Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. Prior to 1.22.0, _unpack_2bit() and _unpack_4bit() resize unpacked arrays according to attacker-controlled TensorProto.dims without verifying that raw_data or int32_data encodes the declared number of elements. Materializing an untrusted UINT2, INT2, UINT4, INT4, or FLOAT4E2M1 tensor through onnx.numpy_helper.to_array() or onnx.reference.ReferenceEvaluator can therefore expand a small packed payload into a disproportionately large allocation and exhaust memory. This issue is fixed in version 1.22.0.
CWE
  • CWE-789 - Memory Allocation with Excessive Size Value
Assigner
GitHub_M CNA under the mitre root
CNA scorecard C 72/100 over 7812 records in the last 180 days details
Impacted products
Vendor Product Version CPE status
onnx onnx Affected: < 1.22.0
guessed Create a notification for this product.
Show details on NVD website

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          "value": "Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. Prior to 1.22.0, _unpack_2bit() and _unpack_4bit() resize unpacked arrays according to attacker-controlled TensorProto.dims without verifying that raw_data or int32_data encodes the declared number of elements. Materializing an untrusted UINT2, INT2, UINT4, INT4, or FLOAT4E2M1 tensor through onnx.numpy_helper.to_array() or onnx.reference.ReferenceEvaluator can therefore expand a small packed payload into a disproportionately large allocation and exhaust memory. This issue is fixed in version 1.22.0."
        }
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            "confidentialityImpact": "NONE",
            "integrityImpact": "NONE",
            "privilegesRequired": "NONE",
            "scope": "UNCHANGED",
            "userInteraction": "NONE",
            "vectorString": "CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
            "version": "3.1"
          }
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      ],
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      "providerMetadata": {
        "dateUpdated": "2026-10-26T17:31:03.716Z",
        "orgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
        "shortName": "GitHub_M"
      },
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        {
          "name": "https://github.com/onnx/onnx/security/advisories/GHSA-q69g-f4f5-v8m7",
          "tags": [
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          "url": "https://github.com/onnx/onnx/security/advisories/GHSA-q69g-f4f5-v8m7"
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        {
          "name": "https://github.com/onnx/onnx/pull/8033",
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          "tags": [
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          "tags": [
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          "url": "https://github.com/onnx/onnx/pull/8066"
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          "url": "https://github.com/onnx/onnx/commit/05c1bc3bceceb8d3cf11e9e7fc7f19f971c44988"
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          "tags": [
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          "url": "https://github.com/onnx/onnx/commit/8de2cf6aa47928e6515ac6d9e1a8b4758886a7df"
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          "tags": [
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          "url": "https://github.com/onnx/onnx/commit/dce5876d6cc6cc30157af7d26a752ef44976da8e"
        },
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          "tags": [
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          ],
          "url": "https://github.com/onnx/onnx/releases/tag/v1.22.0"
        }
      ],
      "source": {
        "advisory": "GHSA-q69g-f4f5-v8m7",
        "discovery": "UNKNOWN"
      },
      "title": "ONNX: Denial of service via unchecked expansion of packed sub-byte tensors in ONNX Python APIs"
    }
  },
  "cveMetadata": {
    "assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
    "assignerShortName": "GitHub_M",
    "cveId": "CVE-2026-115922",
    "datePublished": "2026-10-26T17:31:03.716Z",
    "dateReserved": "2026-10-23T20:21:45.107Z",
    "dateUpdated": "2026-10-26T17:31:03.716Z",
    "state": "PUBLISHED"
  },
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  "dataVersion": "5.2",
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      "percentile": "0.02674"
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                    "version": "\u003c 1.22.0"
                  }
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        ],
        "cveTags": [],
        "descriptions": [
          {
            "lang": "en",
            "value": "Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. Prior to 1.22.0, _unpack_2bit() and _unpack_4bit() resize unpacked arrays according to attacker-controlled TensorProto.dims without verifying that raw_data or int32_data encodes the declared number of elements. Materializing an untrusted UINT2, INT2, UINT4, INT4, or FLOAT4E2M1 tensor through onnx.numpy_helper.to_array() or onnx.reference.ReferenceEvaluator can therefore expand a small packed payload into a disproportionately large allocation and exhaust memory. This issue is fixed in version 1.22.0."
          }
        ],
        "id": "CVE-2026-115922",
        "lastModified": "2026-10-26T18:34:17.050",
        "metrics": {
          "cvssMetricV31": [
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              "cvssData": {
                "attackComplexity": "LOW",
                "attackVector": "LOCAL",
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                "baseScore": 6.2,
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                "confidentialityImpact": "NONE",
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                "privilegesRequired": "NONE",
                "scope": "UNCHANGED",
                "userInteraction": "NONE",
                "vectorString": "CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
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            "url": "https://github.com/onnx/onnx/pull/8066"
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        "vulnStatus": "Awaiting Analysis",
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      "aggregate_severity": "Moderate",
      "current_release_date": "2026-10-27T04:17:37+00:00",
      "cve": "CVE-2026-115922",
      "id": "CVE-2026-115922",
      "initial_release_date": "2026-10-26T17:31:03.716000+00:00",
      "product_status:known_affected": "17",
      "source": "Red Hat CSAF VEX",
      "status": "final",
      "title": "onnx: onnx: Denial of Service via excessive memory allocation in tensor unpacking",
      "url": "https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-115922.json",
      "version": "3"
    }
  }
}



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