Raw vector
CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:L/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-2025-3121 is a medium-severity Improper Restriction of Operations within the Bounds of a Memory Buffer (CWE-119) vulnerability in Linuxfoundation Pytorch. Its CVSS base score is 4.8 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Process Injection (T1055); ranked at the 18th 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-8 (Security and Privacy Engineering Principles) and SI-10 (Information Input Validation) — see the control section below for these in your framework.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-15087
Vulnerability Data
A vulnerability classified as problematic has been found in PyTorch 2.6.0. Affected is the function torch.jit.jit_module_from_flatbuffer. The manipulation leads to memory corruption. Local access is required to approach this attack. The exploit has been disclosed to the public and may…
more
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
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V17.3.2
Mitigating Controls (NIST 800-53 r5) AI
Secure engineering principles require memory-safe design and coding that structurally avoids buffer-boundary violations.
Input validation directly enforces bounds checking that stops out-of-bounds reads/writes from being introduced or reached.
Memory protection restricts exploitation impact of buffer overflows without eliminating the underlying coding flaw.
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 (bounds checking, safe APIs, reviews) directly prevent this class of flaw.
Vulnerability scanning and code analysis directly surface buffer-boundary flaws.
Receiving and triaging vulnerability disclosures commonly includes buffer-related reports.
Developer training on secure coding reduces introduction of memory-buffer errors.
Patching replaces vulnerable code containing buffer-boundary defects.
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 out-of-bounds accesses before release, covering most instances of the weakness.
Secure development lifecycle mandates memory-safety practices that directly prevent buffer-boundary violations.
Application security requirements can specify memory-safety rules, but do not prescribe implementation details.
Secure architecture and engineering principles include memory-safe design patterns that mitigate buffer overflows.
Secure coding standards explicitly forbid unsafe buffer operations, directly eliminating CWE-119.