Cyber Resilience

CVE-2025-63396

Linuxfoundation Pytorch 2.5.0 … 2.7.1

Public PoC
Published
12 November 2025
Modified
05 July 2026
Patch / advisory
CVSS Score v3.1 3.3
Click a component to see what it means
Raw vectorCVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L
EPSS Score 0.0012 3th percentile
Risk Priority 27 floored blend · peak EPSS

Summary

CVE-2025-63396 is a low-severity Improper Locking (CWE-667) vulnerability in Linuxfoundation Pytorch. Its CVSS base score is 3.3 (Low).

Operationally, exploitation aligns with the MITRE ATT&CK technique Endpoint Denial of Service (T1499); ranked at the 3th 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 Not Applicable risk domain.

EU & UK References

Vulnerability Data

An issue was discovered in PyTorch v2.5 and v2.7.1. Omission of profiler.stop() can cause torch.profiler.profile (PythonTracer) to crash or hang during finalization, leading to 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

T1499 Endpoint Denial of Service Impact
Adversaries may perform Endpoint Denial of Service (DoS) attacks to degrade or block the availability of services to users.
T1499.004 Application or System Exploitation Impact
Adversaries may exploit software vulnerabilities that can cause an application or system to crash and deny availability to users.
T1068 Exploitation for Privilege Escalation Privilege Escalation
Adversaries may exploit software vulnerabilities in an attempt to elevate privileges.
T1548 Abuse Elevation Control Mechanism Privilege Escalation
Adversaries may circumvent mechanisms designed to control privilege elevation to gain higher-level permissions.
Derived from this CVE’s CWE(s) via the direct CWE→ATT&CK cross-walk.

CVEs Like This One

CVE-2025-55557Same product: Linuxfoundation Pytorch
CVE-2025-46149Same product: Linuxfoundation Pytorch
CVE-2025-55553Same product: Linuxfoundation Pytorch
CVE-2025-3730Same product: Linuxfoundation Pytorch
CVE-2025-2953Same product: Linuxfoundation Pytorch
CVE-2025-55554Same product: Linuxfoundation Pytorch
CVE-2025-55560Same product: Linuxfoundation Pytorch
CVE-2025-55558Same product: Linuxfoundation Pytorch
CVE-2024-31583Same product: Linuxfoundation Pytorch
CVE-2025-55551Same product: Linuxfoundation Pytorch

Affected Assets

linuxfoundation
pytorch
2.5.0, 2.7.1

Mitigating Controls

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-06 mostly match
prevents

Secure SDLC practices directly include code reviews, static analysis, and concurrency standards that prevent improper locking.

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 can detect race conditions and locking errors before release.

prevents

Secure development lifecycle includes concurrency and locking requirements that reduce improper locking defects.

prevents

Application security requirements can mandate proper lock acquisition/release patterns.

prevents

Secure architecture principles address thread-safety and resource synchronization.

prevents

Secure coding standards directly prohibit missing or incorrect lock usage.

prevents

Change management may catch locking issues introduced by modifications but does not prevent the weakness itself.

References