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CWE-1176

Inefficient CPU Computation

2 CVEs Avg CVSS 3.8 MITRE
0
CRITICAL
0
HIGH
1
MEDIUM
1
LOW
0
POC
0
KEV

Monthly

CVE-2026-18503 Aug 10, 13:45 LOW PATCH Monitor

Super-linear regular-expression complexity in CPython's csv.Sniffer.sniff() allows CPU exhaustion when applications pass attacker-controlled, unbounded CSV input to dialect detection. Any Python application that auto-detects CSV formats from user-supplied data without input length limits is potentially affected across all CPython versions predating the 3.16 fix. No public exploit is identified at time of analysis, and the CVSS 4.0 score of 2.4 reflects a low-severity, local-context vulnerability with limited availability impact.

Information Disclosure Cpython Python Software Foundation
NVD GitHub VulDB
CVSS 4.0
2.4
EPSS
0.1%
CVE-2025-46153 Sep 25, 15:16 PyPI MEDIUM PATCH This Month

PyTorch before 3.7.0 has a bernoulli_p decompose function in decompositions.py even though it lacks full consistency with the eager CPU implementation, negatively affecting nn.Dropout1d,. Rated medium severity (CVSS 5.3), this vulnerability is remotely exploitable, no authentication required, low attack complexity.

Information Disclosure Red Hat AI / ML Pytorch Suse +1
NVD GitHub
CVSS 3.1
5.3
EPSS
0.1%
EPSS 0% CVSS 2.4
LOW PATCH Monitor

Super-linear regular-expression complexity in CPython's csv.Sniffer.sniff() allows CPU exhaustion when applications pass attacker-controlled, unbounded CSV input to dialect detection. Any Python application that auto-detects CSV formats from user-supplied data without input length limits is potentially affected across all CPython versions predating the 3.16 fix. No public exploit is identified at time of analysis, and the CVSS 4.0 score of 2.4 reflects a low-severity, local-context vulnerability with limited availability impact.

Information Disclosure Cpython Python Software Foundation
NVD GitHub VulDB
EPSS 0% CVSS 5.3
MEDIUM PATCH This Month

PyTorch before 3.7.0 has a bernoulli_p decompose function in decompositions.py even though it lacks full consistency with the eager CPU implementation, negatively affecting nn.Dropout1d,. Rated medium severity (CVSS 5.3), this vulnerability is remotely exploitable, no authentication required, low attack complexity.

Information Disclosure Red Hat AI / ML +3
NVD GitHub

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