PyTorch torch.nn.utils.rnn.unpack_sequence memory corruption (CVE-2025-2999)
A critical vulnerability exists in PyTorch version 2.6.0 through versions before 2.7.0 in the function torch.nn.utils.rnn.unpack_sequence. This flaw can lead to memory corruption when exploited locally. The vulnerability has been publicly disclosed, but no known exploits are reported in the wild. A patch is available to address this issue.
AI Analysis
Technical Summary
The PyTorch library versions from 2.6.0 up to but not including 2.7.0 contain a vulnerability in the torch.nn.utils.rnn.unpack_sequence function that allows local attackers to cause memory corruption. This vulnerability has been assigned CVE-2025-2999 and is rated as critical. Exploitation requires local access. The vulnerability details have been publicly disclosed, and a patch is available to remediate the issue.
Potential Impact
Successful exploitation of this vulnerability can lead to memory corruption, which may cause application crashes or potentially allow execution of arbitrary code with local privileges. However, exploitation requires local access, limiting the attack surface. There are no reports of active exploitation in the wild at this time.
Mitigation Recommendations
A patch is available for this vulnerability. Users should upgrade PyTorch to version 2.7.0 or later to remediate the issue. Since this is not a cloud service, remediation is the responsibility of the user. No additional mitigation steps are indicated by the vendor advisory.
PyTorch torch.nn.utils.rnn.unpack_sequence memory corruption (CVE-2025-2999)
Description
A critical vulnerability exists in PyTorch version 2.6.0 through versions before 2.7.0 in the function torch.nn.utils.rnn.unpack_sequence. This flaw can lead to memory corruption when exploited locally. The vulnerability has been publicly disclosed, but no known exploits are reported in the wild. A patch is available to address this issue.
Affected software
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AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
The PyTorch library versions from 2.6.0 up to but not including 2.7.0 contain a vulnerability in the torch.nn.utils.rnn.unpack_sequence function that allows local attackers to cause memory corruption. This vulnerability has been assigned CVE-2025-2999 and is rated as critical. Exploitation requires local access. The vulnerability details have been publicly disclosed, and a patch is available to remediate the issue.
Potential Impact
Successful exploitation of this vulnerability can lead to memory corruption, which may cause application crashes or potentially allow execution of arbitrary code with local privileges. However, exploitation requires local access, limiting the attack surface. There are no reports of active exploitation in the wild at this time.
Mitigation Recommendations
A patch is available for this vulnerability. Users should upgrade PyTorch to version 2.7.0 or later to remediate the issue. Since this is not a cloud service, remediation is the responsibility of the user. No additional mitigation steps are indicated by the vendor advisory.
Technical Details
- Gcve Source
- db.gcve.eu
- Osv Id
- BIT-pytorch-2025-2999
- Osv Schema Version
- 1.6.2
- Aliases
- ["CVE-2025-2999"]
- Ecosystems
- ["Bitnami"]
- Database Specific Severity
- Medium
Threat ID: 6aa005ceacd9273b49ab5e18
Added to database: 09/08/2026, 12:55:42 UTC
Last enriched: 09/08/2026, 13:24:03 UTC
Last updated: 09/10/2026, 19:36:49 UTC
Views: 4
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