PyTorch torch.jit.script memory corruption (CVE-2025-3000)
A critical vulnerability in PyTorch 2.6.0 affecting the torch.jit.script function can lead to memory corruption. The vulnerability can be exploited locally. Although the exploit has been publicly disclosed, no known exploits are reported in the wild. A patch is available to address this issue.
AI Analysis
Technical Summary
CVE-2025-3000 is a vulnerability in PyTorch version 2.6.0 that impacts the torch.jit.script function, resulting in memory corruption. The vulnerability allows an attacker with local access to potentially corrupt memory, which could lead to undefined behavior or crashes. The exploit details have been publicly disclosed, but there is no evidence of active exploitation in the wild. The vulnerability affects versions from 2.6.0 up to but not including 2.7.0. A patch is available to remediate this issue.
Potential Impact
Successful exploitation of this vulnerability can cause memory corruption on the local host, which may lead to application crashes or other unpredictable behavior. No remote exploitation or widespread attacks have been reported.
Mitigation Recommendations
A patch is available for this vulnerability. Users should upgrade PyTorch to version 2.7.0 or later to mitigate the risk. Since the vulnerability requires local access, limiting access to trusted users and environments can reduce exposure until patched.
PyTorch torch.jit.script memory corruption (CVE-2025-3000)
Description
A critical vulnerability in PyTorch 2.6.0 affecting the torch.jit.script function can lead to memory corruption. The vulnerability can be exploited locally. Although the exploit has been publicly disclosed, 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
CVE-2025-3000 is a vulnerability in PyTorch version 2.6.0 that impacts the torch.jit.script function, resulting in memory corruption. The vulnerability allows an attacker with local access to potentially corrupt memory, which could lead to undefined behavior or crashes. The exploit details have been publicly disclosed, but there is no evidence of active exploitation in the wild. The vulnerability affects versions from 2.6.0 up to but not including 2.7.0. A patch is available to remediate this issue.
Potential Impact
Successful exploitation of this vulnerability can cause memory corruption on the local host, which may lead to application crashes or other unpredictable behavior. No remote exploitation or widespread attacks have been reported.
Mitigation Recommendations
A patch is available for this vulnerability. Users should upgrade PyTorch to version 2.7.0 or later to mitigate the risk. Since the vulnerability requires local access, limiting access to trusted users and environments can reduce exposure until patched.
Technical Details
- Gcve Source
- db.gcve.eu
- Osv Id
- BIT-pytorch-2025-3000
- Osv Schema Version
- 1.6.2
- Aliases
- ["CVE-2025-3000"]
- Ecosystems
- ["Bitnami"]
- Database Specific Severity
- Medium
Threat ID: 6aa005ceacd9273b49ab5e16
Added to database: 09/08/2026, 12:55:42 UTC
Last enriched: 09/08/2026, 13:23:56 UTC
Last updated: 09/10/2026, 19:36:50 UTC
Views: 3
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