Cyber Resilience

CVE-2024-27318

Path Traversal in Fedoraproject Fedora 39 … 40

Published
23 February 2024
Modified
17 June 2026
Patch / advisory
CVSS Score v3.1 7.5
Click a component to see what it means
Raw vectorCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N
EPSS Score 0.012 65th percentile
Risk Priority 60 floored blend · peak EPSS

Summary

CVE-2024-27318 is a high-severity Path Traversal (CWE-22) vulnerability in Fedoraproject Fedora. Its CVSS base score is 7.5 (High).

Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked in the top 35% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.

This vulnerability is AI-related — categorised as Deep Learning Frameworks; in the Data-Related Vulnerabilities risk domain.

The strongest mitigations our analysis identified map to AC-3 (Access Enforcement) and SI-10 (Information Input Validation) — see the control section below for these in your framework.

OWASP Top 10 for Web (2025)

EU & UK References

Vulnerability Data

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…

more

vulnerability occurs as a bypass for the patch added for CVE-2022-25882.

CWE(s)

AI Security AnalysisAI

AI Category
Deep Learning Frameworks
Risk Domain
Data-Related Vulnerabilities
OWASP Top 10 for LLMs 2025
None mapped
Classification Reason
ONNX (Open Neural Network Exchange) is a standard and library for representing and exchanging deep learning and machine learning models across frameworks like PyTorch and TensorFlow.

Related Threats

MITRE ATT&CK Enterprise Techniques

T1190 Exploit Public-Facing Application Initial Access
Adversaries may attempt to exploit a weakness in an Internet-facing host or system to initially access a network.
Derived from this CVE’s CWE(s) via the direct CWE→ATT&CK cross-walk.

CVEs Like This One

CVE-2025-51480Same product: Linuxfoundation Onnx
CVE-2024-5187Same product: Linuxfoundation Onnx
CVE-2024-25711Same product: Fedoraproject Fedora
CVE-2023-39332Same product: Fedoraproject Fedora
CVE-2023-32004Same product: Fedoraproject Fedora
CVE-2023-40587Same product: Fedoraproject Fedora
CVE-2023-32003Same product: Fedoraproject Fedora
CVE-2024-23334Same product: Fedoraproject Fedora
CVE-2023-25652Same product: Fedoraproject Fedora
CVE-2021-25282Same product: Fedoraproject Fedora

Affected Assets

linuxfoundation
onnx
≤ 1.16.0
fedoraproject
fedora
39, 40

Mitigating Controls

Control response

Prevent
Stop it (NIST 800-53)

Detect
Catch it (NIST detect / respond)

Harden
Shrink the surface (DISA STIG)

Validate
Prove the fix (OWASP ASVS)
  • V5.3.2

Mitigating Controls (NIST 800-53 r5) AI

Enforces the intended directory access authorizations that path traversal would otherwise bypass.

Input validation directly neutralizes special path elements before pathname construction occurs.

Least privilege reduces the impact of any unauthorized file access obtained via 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.

PR.PS-02 partial match
prevents

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.

PR.AA-05 none match
prevents

PR.AA-05 defines and reviews access policies but does not address code-level pathname neutralization, so neither direction prevents CWE-22.

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.

finds

Security testing in development catches path traversal via static/dynamic analysis.

prevents

Secure SDLC mandates input validation and path sanitization that directly prevent path traversal.

prevents

Application security requirements include rules for safe file handling and canonicalization.

prevents

Secure architecture principles require least-privilege file access and directory isolation.

prevents

Secure coding standards explicitly forbid unsafe path construction and mandate safe APIs.

mitigates

Information access restriction limits which files an application may read or write.

References