Junglewise Threat Intelligence

CVE-2026-27489: ONNX path traversal via symlink in external data handling

CVE-2026-27489 · Severity: high · CVSS 7.5 · Published 2026-04-01

Technologies: onnx (PyPI). Vendors: PyPI, Red Hat.

Executive brief

Open Neural Network Exchange (ONNX) is an open-standard library used for machine learning model interoperability. A security flaw allows an attacker to create a malicious model file that, when loaded by a user, can read sensitive files from the user's computer or server. This could lead to the theft of private data, configuration files, or credentials stored on the system running the ONNX software.

Technical details

A path traversal vulnerability exists in ONNX's handling of external data files. The root cause is an ineffective symlink check in 'onnx/checker.cc' which uses 'std::filesystem::is_regular_file'. Because this function follows symbolic links, it returns true if a symlink points to a regular file, allowing an attacker to bypass intended directory restrictions. By providing a model with a crafted symlink (e.g., linking 'model.data' to '/etc/passwd'), an attacker can trick the library into reading arbitrary files outside the model's directory during the 'onnx.load' process. The issue is patched in version 1.21.0 by implementing canonical path containment and using 'O_NOFOLLOW' flags during file operations.

Affected products

  • onnx onnx < 1.21.0
  • Red Hat Red Hat OpenShift AI 2.25

Timeline

  • 2026-03-04: patched: Fix committed to GitHub repository
  • 2026-03-31: advisory: GitHub Security Advisory published
  • 2026-04-01: disclosed: CVE published to NVD

References

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