Denial of service via compiled LU slice TypeError
Published Sep 25, 2025 · Updated Sep 25, 2025
Type error in torch.linalg.lu in PyTorch 2.8.0 and earlier allows remote attackers to interrupt model compilation with a sliced LU result. Under compiled execution with AOT Eager or Inductor, slicing the operation's tuple output passes an unsupported dynamic_attributes argument to VariableTracker, raising TypeError. Exploitation requires an application that accepts attacker-controlled models for compilation; the demonstrated consequence is a compilation failure rather than memory corruption.
Summary
What happened
Type error in torch.linalg.lu in PyTorch 2.8.0 and earlier allows remote attackers to interrupt model compilation with a sliced LU result. Under compiled execution with AOT Eager or Inductor, slicing the operation's tuple output passes an unsupported dynamic_attributes argument to VariableTracker, raising TypeError. Exploitation requires an application that accepts attacker-controlled models for compilation; the demonstrated consequence is a compilation failure rather than memory corruption.
The record
- CVE
- CVE-2025-55551
- Published
- Sep 25, 2025
- Updated
- Sep 25, 2025
- Vendor
- Unknown vendor
- Product
- Unknown product
- Classifications
- CWE-400, T1499
- Attack vector
- network
- Privileges
- unauthenticated
Timeline
How it unfolded
- Sep 25, 2025CVE publishedPublication date reported by the CVE source.
- Sep 25, 2025Record updatedLatest update available in the CVE record.
Exploitability
Present is not the same as exploitable
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What conditions does exploitation require?
What is affected?
Affected products and versions are unavailable in this record.
Attacks
What attackers are doing with it
Daily unique IPs observed by Shadowserver honeypots for known exploited vulnerabilities (KEVs). Missing observations do not establish an absence of attacks.
Public exploit references
- torch.linalg.lu compiled-slice reproductionproof of concept · demonstrated
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Technologies
Your stack
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Your stack
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