CVE-2025-55553
Linuxfoundation Pytorch ≤ 2.7.0
Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:HSummary
CVE-2025-55553 is a high-severity Uncaught Exception (CWE-248) vulnerability in Linuxfoundation Pytorch. Its CVSS base score is 7.5 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Endpoint Denial of Service (T1499); ranked at the 31th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
This vulnerability is AI-related — categorised as Deep Learning Frameworks; in the Not Applicable risk domain.
The strongest mitigations our analysis identified map to SA-8 (Security and Privacy Engineering Principles) and SC-24 (Fail in Known State) — see the control section below for these in your framework.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-31131
Vulnerability Data
A syntax error in the component proxy_tensor.py of pytorch v2.7.0 allows attackers to cause a Denial of Service (DoS).
- CWE(s)
AI Security AnalysisAI
- AI Category
- Deep Learning Frameworks
- Risk Domain
- Not Applicable
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: pytorch
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Mitigating Controls (NIST 800-53 r5) AI
Security engineering principles include robust exception management to keep the system in a defined state.
Fail-in-known-state reduces the impact when an uncaught exception occurs by preserving a safe condition.
Error handling requirements force structured catching and response to exceptions instead of allowing them to propagate uncaught.
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 explicitly require structured exception handling to prevent uncaught exceptions from reaching production.
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 uncaught exceptions before production deployment.
Secure development lifecycle includes exception-handling standards that reduce uncaught exceptions.
Application security requirements typically mandate robust error and exception handling.
Secure architecture principles call for centralized, comprehensive exception management.
Secure coding standards directly require catching and handling exceptions to prevent crashes or leaks.