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Total 7 CVE
CVE Vendors Products Updated CVSS v3.1
CVE-2026-34445 1 Onnx 1 Onnx 2026-04-02 8.6 High
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.
CVE-2026-27489 1 Onnx 1 Onnx 2026-04-02 8.6 High
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.
CVE-2026-34446 1 Onnx 1 Onnx 2026-04-02 4.7 Medium
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.
CVE-2026-34447 1 Onnx 1 Onnx 2026-04-02 5.5 Medium
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.
CVE-2026-28500 2 Linuxfoundation, Onnx 2 Onnx, Onnx 2026-03-24 8.6 High
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 exfiltrate sensitive files (SSH keys, cloud credentials) from the victim's machine the moment the model is loaded. As of time of publication, no known patched versions are available.
CVE-2025-51480 2 Linuxfoundation, Onnx 2 Onnx, Onnx 2025-10-08 8.8 High
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.
CVE-2024-7776 1 Onnx 1 Onnx 2025-03-26 9.1 Critical
A vulnerability in the `download_model` function of the onnx/onnx framework, before and including version 1.16.1, allows for arbitrary file overwrite due to inadequate prevention of path traversal attacks in malicious tar files. This vulnerability can be exploited by an attacker to overwrite files in the user's directory, potentially leading to remote command execution.