PyTorch CUDACachingAllocator.cpp torch.cuda.memory.caching_allocator_delete memory corruption (CVE-2025-3136)
A memory corruption vulnerability exists in PyTorch version 2.6.0 affecting the function torch.cuda.memory.caching_allocator_delete in the file c10/cuda/CUDACachingAllocator.cpp. The issue requires local access to exploit and has been publicly disclosed. A patch is available to address this vulnerability.
AI Analysis
Technical Summary
CVE-2025-3136 is a memory corruption vulnerability in PyTorch 2.6.0 specifically within the CUDA memory caching allocator's deletion function. The flaw allows local attackers to manipulate memory, potentially causing corruption. The vulnerability has been publicly disclosed, but there are no known exploits in the wild. A fix has been made available for versions starting from 2.7.0 onward.
Potential Impact
The vulnerability can lead to memory corruption when the affected function is invoked, which may cause application instability or crashes. Exploitation requires local access, limiting remote attack vectors. No active exploitation has been reported.
Mitigation Recommendations
Apply the official patch by upgrading PyTorch to version 2.7.0 or later, as the vulnerability affects versions >=2.6.0 and <2.7.0. Since a patch is available, updating to a fixed version is the recommended remediation.
PyTorch CUDACachingAllocator.cpp torch.cuda.memory.caching_allocator_delete memory corruption (CVE-2025-3136)
Description
A memory corruption vulnerability exists in PyTorch version 2.6.0 affecting the function torch.cuda.memory.caching_allocator_delete in the file c10/cuda/CUDACachingAllocator.cpp. The issue requires local access to exploit and has been publicly disclosed. A patch is available to address this vulnerability.
Affected software
Run on your own infrastructure? Check whether these packages are installed with threat-finder — our free open-source scanner.
AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
CVE-2025-3136 is a memory corruption vulnerability in PyTorch 2.6.0 specifically within the CUDA memory caching allocator's deletion function. The flaw allows local attackers to manipulate memory, potentially causing corruption. The vulnerability has been publicly disclosed, but there are no known exploits in the wild. A fix has been made available for versions starting from 2.7.0 onward.
Potential Impact
The vulnerability can lead to memory corruption when the affected function is invoked, which may cause application instability or crashes. Exploitation requires local access, limiting remote attack vectors. No active exploitation has been reported.
Mitigation Recommendations
Apply the official patch by upgrading PyTorch to version 2.7.0 or later, as the vulnerability affects versions >=2.6.0 and <2.7.0. Since a patch is available, updating to a fixed version is the recommended remediation.
Technical Details
- Gcve Source
- db.gcve.eu
- Osv Id
- BIT-pytorch-2025-3136
- Osv Schema Version
- 1.6.2
- Aliases
- ["CVE-2025-3136"]
- Ecosystems
- ["Bitnami"]
- Database Specific Severity
- Medium
Threat ID: 6aa005ceacd9273b49ab5e10
Added to database: 09/08/2026, 12:55:42 UTC
Last enriched: 09/08/2026, 13:23:29 UTC
Last updated: 09/10/2026, 19:36:50 UTC
Views: 6
Community Reviews
0 reviewsCrowdsource mitigation strategies, share intel context, and vote on the most helpful responses. Sign in to add your voice and help keep defenders ahead.
Want to contribute mitigation steps or threat intel context? Sign in or create an account to join the community discussion.
Actions
Updates to AI analysis require Pro Console access. Upgrade inside Console → Billing.
Need more coverage?
Upgrade to Pro Console for AI refresh and higher limits.
For incident response and remediation, OffSeq services can help resolve threats faster.
Latest Threats
Check if your credentials are on the dark web
Instant breach scanning across billions of leaked records. Free tier available.