Raw vector
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:N/VI:H/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-2026-53875 is a high-severity Eval Injection (CWE-95) vulnerability. Its CVSS base score is 7.1 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique JavaScript (T1059.007); ranked at the 36th 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 Machine Learning Libraries.
The strongest mitigations our analysis identified map to SA-11 (Developer Testing and Evaluation) 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
- 🇪🇺 ENISA EUVD: EUVD-2026-37741
Vulnerability Data
picklescan before 1.0.3 contains a scanning bypass vulnerability in the scan_pytorch function that allows attackers to embed malicious magic numbers via dynamic eval using the __reduce__ trick. Attackers can craft malicious PyTorch payloads that evade picklescan detection while remaining executable,…
more
enabling arbitrary code execution when loaded with torch.load().
- CWE(s)
AI Security AnalysisAI
- AI Category
- Machine Learning Libraries
- Risk Domain
- N/A
- 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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V1.3.2
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and code analysis can discover eval-injection flaws but does not stop their introduction.
Input validation explicitly requires neutralizing untrusted data before it reaches dynamic evaluation constructs such as eval.
Secure-development standards and tools can mandate safe coding patterns that avoid unsafe dynamic evaluation.
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 require input neutralization and avoidance of unsafe dynamic evaluation.
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 can detect eval injection vulnerabilities before deployment.
Secure development life cycle mandates input validation and safe coding practices that directly prevent eval injection.
Application security requirements include rules against dynamic code execution of untrusted input.
Secure architecture principles discourage unsafe dynamic evaluation constructs.
Secure coding explicitly requires neutralization of input before dynamic evaluation, directly mitigating eval injection.
Separation of environments limits the blast radius if eval injection occurs in non-production.