Raw vector
CVSS:3.1/AV:L/AC:H/PR:N/UI:R/S:U/C:H/I:N/A:NSummary
CVE-2026-34446 is a medium-severity Path Traversal (CWE-22) vulnerability in Linuxfoundation Onnx. Its CVSS base score is 4.7 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Data from Local System (T1005); ranked at the 7th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
This vulnerability is AI-related — categorised as Machine Learning Libraries; in the Supply Chain and Deployment risk domain.
The strongest mitigations our analysis identified map to SI-10 (Information Input Validation) and SI-2 (Flaw Remediation) — see the control section below for these in your framework.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-17987
Vulnerability Data
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…
more
exactly like a regular file on the filesystem. This issue has been patched in version 1.21.0.
- CWE(s)
AI Security AnalysisAI
- AI Category
- Machine Learning Libraries
- Risk Domain
- Supply Chain and Deployment
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: machine learning, neural network, onnx
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
Hardlink-based path traversal in onnx.load directly enables unauthorized reads from the local filesystem outside intended directories.
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
Mitigating Controls (NIST 800-53 r5) AI
Directly enforces validation of file paths and link types during onnx.load to block path traversal via hardlinks (CWE-22/61).
Requires timely application of the vendor patch (v1.21.0) that adds hardlink detection to the existing symlink check.
Limits the filesystem privileges granted to the process performing onnx.load, reducing impact of any successful hardlink traversal.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Secure SDLC practices directly prevent introduction of symlink-following flaws in file-handling code.
Vulnerability identification can discover existing symlink issues but does not prevent or remediate them in code.
Least-privilege access policies can limit damage from symlink attacks but do not address the coding flaw itself.
Patching/maintenance can remediate known path-traversal flaws in deployed software (partial prevention of exploitability) but does nothing to stop the coding defect from being introduced in the first place.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Security testing in development catches path traversal via static/dynamic analysis.
Secure SDLC mandates input validation and path sanitization that directly prevent path traversal.
Application security requirements include rules for safe file handling and canonicalization.
Secure architecture principles require least-privilege file access and directory isolation.
Secure coding standards explicitly forbid unsafe path construction and mandate safe APIs.
Information access restriction limits which files an application may read or write.