PyTorch torch.lstm_cell memory corruption (CVE-2025-3001)
A critical vulnerability in PyTorch 2.6.0 affecting the torch.lstm_cell function allows local attackers to cause memory corruption. The vulnerability requires local access to exploit and has been publicly disclosed. A patch is available to remediate this issue.
AI Analysis
Technical Summary
CVE-2025-3001 is a vulnerability in PyTorch version 2.6.0 where the torch.lstm_cell function can be manipulated locally to cause memory corruption. This flaw could potentially lead to instability or other unintended behavior in applications using this function. The vulnerability has been publicly disclosed, but there are no known exploits in the wild. A patch addressing this issue is available.
Potential Impact
The vulnerability enables local attackers to cause memory corruption via the torch.lstm_cell function, which may lead to application crashes or other unpredictable behavior. There is no evidence of remote exploitation or active exploitation in the wild at this time.
Mitigation Recommendations
A patch is available for this vulnerability. Users should upgrade PyTorch to a fixed version beyond 2.6.0 to remediate the issue. Since the vulnerability requires local access, limiting local user permissions can also reduce risk.
PyTorch torch.lstm_cell memory corruption (CVE-2025-3001)
Description
A critical vulnerability in PyTorch 2.6.0 affecting the torch.lstm_cell function allows local attackers to cause memory corruption. The vulnerability requires local access to exploit and has been publicly disclosed. A patch is available to remediate this issue.
Affected software
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AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
CVE-2025-3001 is a vulnerability in PyTorch version 2.6.0 where the torch.lstm_cell function can be manipulated locally to cause memory corruption. This flaw could potentially lead to instability or other unintended behavior in applications using this function. The vulnerability has been publicly disclosed, but there are no known exploits in the wild. A patch addressing this issue is available.
Potential Impact
The vulnerability enables local attackers to cause memory corruption via the torch.lstm_cell function, which may lead to application crashes or other unpredictable behavior. There is no evidence of remote exploitation or active exploitation in the wild at this time.
Mitigation Recommendations
A patch is available for this vulnerability. Users should upgrade PyTorch to a fixed version beyond 2.6.0 to remediate the issue. Since the vulnerability requires local access, limiting local user permissions can also reduce risk.
Technical Details
- Gcve Source
- db.gcve.eu
- Osv Id
- BIT-pytorch-2025-3001
- Osv Schema Version
- 1.6.2
- Aliases
- ["CVE-2025-3001"]
- Ecosystems
- ["Bitnami"]
- Database Specific Severity
- Medium
Threat ID: 6aa005ceacd9273b49ab5e14
Added to database: 09/08/2026, 12:55:42 UTC
Last enriched: 09/08/2026, 13:23:49 UTC
Last updated: 09/10/2026, 19:36:50 UTC
Views: 3
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