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.
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.
A vulnerability in the download_model_with_test_data function of the onnx/onnx framework, versions before 1.16.2, allow for arbitrary file overwrite due to inadequate prevention of path traversal attacks in malicious tar files. This vulnerability enables attackers to overwrite any file on the system, potentially leading to remote code execution, deletion of system, personal, or application files, thus impacting the integrity and availability of the system. The issue arises from the function's handling …
Versions of the package onnx before and including 1.15.0 are vulnerable to Out-of-bounds Read as the ONNX_ASSERT and ONNX_ASSERTM functions have an off by one string copy.
Versions of the package onnx before and including 1.15.0 are vulnerable to Directory Traversal as the external_data field of the tensor proto can have a path to the file which is outside the model current directory or user-provided directory. The vulnerability occurs as a bypass for the patch added for CVE-2022-25882.
Versions of the package onnx before 1.13.0 are vulnerable to Directory Traversal as the external_data field of the tensor proto can have a path to the file which is outside the model current directory or user-provided directory, for example "../../../etc/passwd"