CVE-2025-2149
Linuxfoundation Pytorch 2.6.0
Raw vector
CVSS:4.0/AV:L/AC:H/AT:N/PR:L/UI:N/VC:N/VI:L/VA:N/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:XSummary
CVE-2025-2149 is a low-severity Improper Initialization (CWE-665) vulnerability in Linuxfoundation Pytorch. Its CVSS base score is 2.0 (Low).
Operationally, ranked at the 17th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
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 SA-11 (Developer Testing and Evaluation) and SA-8 (Security and Privacy Engineering Principles) — see the control section below for these in your framework.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-7523
Vulnerability Data
A vulnerability was found in PyTorch 2.6.0+cu124. It has been rated as problematic. Affected by this issue is the function nnq_Sigmoid of the component Quantized Sigmoid Module. The manipulation of the argument scale/zero_point leads to improper initialization. The attack needs…
more
to be approached locally. The complexity of an attack is rather high. The exploitation is known to be difficult. The exploit has been disclosed to the public and may be used.
- 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
- Matched keywords: pytorch
Related Threats
CVEs Like This One
Affected Assets
Mitigating Controls
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation directly exercises initialization paths and can reveal missing or incorrect resource setup.
Engineering principles applied during design and implementation can require explicit initialization to a known state.
Requiring the system to fail to a known state structurally reduces the chance that uninitialized resources remain reachable.
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 enforce proper resource initialization during coding and testing.
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 can detect uninitialized variables but does not itself enforce initialization practices.
Configuration management can enforce secure defaults and initialization settings but is not the primary control for code-level initialization.
Secure development life cycle mandates initialization checks and secure defaults that directly prevent improper resource initialization.
Secure system architecture and engineering principles require explicit initialization of resources and secure state management.
Secure coding standards explicitly forbid uninitialized variables and mandate proper resource initialization before use.