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Уязвимости onnx

За последние 30 дней в onnx опубликовано уязвимостей: 0; в каталоге KEV: 0.

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Уязвимостей: 8

  1. CVE-2026-44512

    Средний · CVSS 5.5EPSS 0,19%Нет опубликованного исправления

    ONNX: Null Pointer Dereference in Upsample Version Converter Adapter (Zero Inputs)

    Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. From 1.9.0 before 1.22.0, onnx.version_converter.convert_version() can dereference a null pointer in Upsample_6_7::adapt_upsample_6_7() in onnx/version_converter/adapters/upsample_6_7.h when processing an untrusted model with an Upsample node that has zero inputs, causing an unrecoverable denial of service. This issue is fixed in version 1.22.0.

  2. CVE-2026-14647

    Средний · CVSS 5.3EPSS 0,43%Нет опубликованного исправления

    onnx onnxruntime old.cc convPoolShapeInference_opset19 out-of-bounds

    A weakness has been identified in onnx up to 1.21.x. This vulnerability affects the function convPoolShapeInference_opset19 of the file onnx/defs/nn/old.cc of the component onnxruntime. This manipulation causes out-of-bounds read. It is possible to initiate the attack remotely. The exploit has been made available to the public and could be used for attacks. Patch name: a7bf3a0f1d18bb62575236ef6e4944980c40e045. It is recommended to apply a patch to fix this issue.

  3. CVE-2026-34447

    Средний · CVSS 5.5EPSS 0,26%Нет опубликованного исправления

    ONNX: External Data Symlink Traversal

    Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. Prior to version 1.21.0, there is a symlink traversal vulnerability in external data loading allows reading files outside the model directory. This issue has been patched in version 1.21.0.

    Опубликовано Обновлено
  4. CVE-2026-34446

    Средний · CVSS 4.7EPSS 0,18%Нет опубликованного исправления

    ONNX: Arbitrary File Read via ExternalData Hardlink Bypass in ONNX load

    Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. Prior to version 1.21.0, there is an issue in onnx.load, the code checks for symlinks to prevent path traversal, but completely misses hardlinks because a hardlink looks exactly like a regular file on the filesystem. This issue has been patched in version 1.21.0.

    Опубликовано Обновлено
  5. CVE-2026-27489

    Высокий · CVSS 8.7EPSS 0,62%Нет опубликованного исправления

    ONNX: Path Traversal via Symlink

    Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. Prior to version 1.21.0, a path traversal vulnerability via symlink allows to read arbitrary files outside model or user-provided directory. This issue has been patched in version 1.21.0.

  6. CVE-2026-34445

    Высокий · CVSS 8.6EPSS 0,29%Нет опубликованного исправления

    ONNX: Malicious ONNX models can crash servers by exploiting unprotected object settings.

    Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. Prior to version 1.21.0, the ExternalDataInfo class in ONNX was using Python’s setattr() function to load metadata (like file paths or data lengths) directly from an ONNX model file. It didn’t check if the "keys" in the file were valid. Due to this, an attacker could craft a malicious model that overwrites internal object properties. This issue has been patched in version 1.21.0.

    Опубликовано Обновлено
  7. CVE-2026-28500

    Высокий · CVSS 8.6EPSS 0,32%Нет опубликованного исправления

    ONNX Untrusted Model Repository Warnings Suppressed by silent=True in onnx.hub.load() — Silent Supply-Chain Attack

    Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. In versions up to and including 1.20.1, a security control bypass exists in onnx.hub.load() due to improper logic in the repository trust verification mechanism. While the function is designed to warn users when loading models from non-official sources, the use of the silent=True parameter completely suppresses all security warnings and confirmation prompts. This vulnerability transforms a standard model-loading function into a vector for Zero-Interaction Supply-Chain Attacks. When chained with file-system vulnerabilities, an attacker can silently e

  8. CVE-2025-51480

    Высокий · CVSS 8.8EPSS 0,68%Нет опубликованного исправления

    CVE-2025-51480

    Path Traversal vulnerability in onnx.external_data_helper.save_external_data in ONNX 1.17.0 allows attackers to overwrite arbitrary files by supplying crafted external_data.location paths containing traversal sequences, bypassing intended directory restrictions.

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