A buffer overflow occurs in pytorch v2.7.0 when a PyTorch model consists of torch.nn.Conv2d, torch.nn.functional.hardshrink, and… (CVE-2025-55558)
Description
A buffer overflow vulnerability exists in PyTorch version 2.7.0 when a model includes torch.nn.Conv2d, torch.nn.functional.hardshrink, and torch.Tensor.view combined with torch.mv(), and is compiled using Inductor. This flaw can lead to a Denial of Service (DoS) condition. A patch addressing this issue is available in versions 2.7.1 and later.
Affected software
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AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
CVE-2025-55558 describes a buffer overflow in PyTorch v2.7.0 triggered by specific model compositions involving torch.nn.Conv2d, torch.nn.functional.hardshrink, and tensor operations (view and mv) when compiled by the Inductor compiler. This vulnerability can cause a Denial of Service. The issue affects versions prior to 2.7.1. A fix has been released and is available via the PyTorch GitHub repository.
Potential Impact
The vulnerability can cause a Denial of Service (DoS) by triggering a buffer overflow under the specified conditions. There is no indication of remote code execution or data corruption beyond service disruption. No known exploits are reported in the wild at this time.
Mitigation Recommendations
Users should upgrade PyTorch to version 2.7.1 or later, where this buffer overflow vulnerability has been patched. Refer to the official PyTorch patch at https://github.com/pytorch/pytorch/pull/151887 for details. No additional mitigation is indicated by the vendor advisory.
Technical Details
- Gcve Source
- db.gcve.eu
- Osv Id
- BIT-pytorch-2025-55558
- Osv Schema Version
- 1.6.2
- Aliases
- CVE-2025-55558
- Ecosystems
- Bitnami
- Database Specific Severity
- High
Patch Information
Threat ID: 6aa005c7acd9273b49ab5c80
Added to database: 09/08/2026, 12:55:35 UTC
Last enriched: 09/08/2026, 13:21:43 UTC
Last updated: 10/24/2026, 08:45:09 UTC
Views: 38
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