CVE-2024-31580 (High) detected in torch-1.5.0-cp36-cp36m-manylinux1_x86_64.whl

[mend-bolt-for-github]

CVE-2024-31580 - High Severity Vulnerability

Vulnerable Library - torch-1.5.0-cp36-cp36m-manylinux1_x86_64.whl

Tensors and Dynamic neural networks in Python with strong GPU acceleration

Library home page: https://files.pythonhosted.org/packages/13/70/54e9fb010fe1547bc4774716f11ececb81ae5b306c05f090f4461ee13205/torch-1.5.0-cp36-cp36m-manylinux1_x86_64.whl

Path to dependency file: /pytorch-metric-learning

Path to vulnerable library: /pytorch-metric-learning

Dependency Hierarchy:

• ❌ torch-1.5.0-cp36-cp36m-manylinux1_x86_64.whl (Vulnerable Library)

Found in HEAD commit: 50a539d66e7a2f790cf8a8d8d1471993698c9adc

Found in base branch: master

Vulnerability Details

PyTorch before v2.2.0 was discovered to contain a heap buffer overflow vulnerability in the component /runtime/vararg_functions.cpp. This vulnerability allows attackers to cause a Denial of Service (DoS) via a crafted input.

Publish Date: 2024-04-17

URL: CVE-2024-31580

CVSS 3 Score Details (7.5)

Base Score Metrics:

• Exploitability Metrics:
  • Attack Vector: Network
  • Attack Complexity: Low
  • Privileges Required: None
  • User Interaction: None
  • Scope: Unchanged
• Impact Metrics:
  • Confidentiality Impact: None
  • Integrity Impact: None
  • Availability Impact: High

For more information on CVSS3 Scores, click here.

Suggested Fix

Type: Upgrade version

Origin: https://www.cve.org/CVERecord?id=CVE-2024-31580

Release Date: 2024-04-17

Fix Resolution: 2.2.0

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