Improper Validation of Specified Quantity in Input Affecting torch package, versions [,2.8.0)
Threat Intelligence
Snyk has a proof-of-concept or detailed explanation of how to exploit this vulnerability.
The probability is the direct output of the EPSS model, and conveys an overall sense of the threat of exploitation in the wild. The percentile measures the EPSS probability relative to all known EPSS scores. Note: This data is updated daily, relying on the latest available EPSS model version. Check out the EPSS documentation for more details.
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Test your applications- Snyk IDSNYK-PYTHON-TORCH-13052968
- published26 Sept 2025
- disclosed25 Sept 2025
- creditShaoyu Yang
Introduced: 25 Sep 2025
NewCVE-2025-46148 (opens in a new tab)How to fix?
Upgrade torch to version 2.8.0 or higher.
Overview
torch is a Tensors and Dynamic neural networks in Python with strong GPU acceleration
Affected versions of this package are vulnerable to Improper Validation of Specified Quantity in Input in the ModularIndexing() function when Inductor config is set to constant_and_index_propagation=False. An attacker can cause incorrect computation results by supplying crafted input data.