In PyTorch through 2.6.0, when eager is used, nn.PairwiseDistance(p=2) produces incorrect results.

AI summary snake-internal / snake-template-v1

A weakness called CVE-2025-46148 was discovered in In PyTorch through. Severity is Info. Low severity or not yet rated. What you should do: update the affected software to the latest version. If unsure, ask your IT team or search the vendor's site for "In PyTorch through CVE-2025-46148".

CVE-2025-46148 (In PyTorch through). Severity: Info. Response plan: 1. Check the vendor advisory for affected versions and the patched release. 2. If a vulnerable version is running in production, schedule maintenance (urgency from KEV/CVSS). 3. If no patch yet, mitigate via WAF rule, disabling the affected feature, etc. 4. Monitor logs / SIEM for known IOC and PoC signatures of this CVE. PoCs and fix commits: see the 'References' section, MITRE, and NVD.

❓ What is the problem

A weakness (CVE-2025-46148) in In PyTorch through. A serious software flaw has been identified.

📍 Affected scope

Target versions of In PyTorch through (see vendor advisory). If running in production, identify exposure immediately.

🔥 Severity

Severity: Info. Low severity or not yet rated.

🔧 How to fix

Update to the patched release as listed in the vendor advisory.

🛡️ Workaround

If a patch is not yet available, consider disabling the affected feature, applying WAF rules, blocking via network ACLs, or isolating the vulnerable version.

🔍 Detection

Check version information, scan dependencies via SBOM, and monitor SIEM for IOC and PoC signatures related to this CVE.

Affected packages

Bitnami pytorch

[{"type":"SEMVER","events":[{"introduced":"0"},{"fixed":"2.7.0"}]}]

PyPI torch

[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.7.0"}]}]

AI summary snake-internal / snake-template-v1

Affected packages

References

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