Incorrect tensor results via Inductor integer overflow
Published Sep 25, 2025 · Updated Sep 25, 2025
Integer overflow in PyTorch 2.8.0 and earlier allows remote attackers to produce incorrect tensor results through compiled models. CPU Inductor mishandles positive infinity processed by torch.nan_to_num before a long conversion, producing the opposite signed 64-bit boundary value from eager execution. The flaw requires CPU Inductor compilation of that operation sequence and an infinite input; the bounded consequence is silent calculation corruption.
Summary
What happened
Integer overflow in PyTorch 2.8.0 and earlier allows remote attackers to produce incorrect tensor results through compiled models. CPU Inductor mishandles positive infinity processed by torch.nan_to_num before a long conversion, producing the opposite signed 64-bit boundary value from eager execution. The flaw requires CPU Inductor compilation of that operation sequence and an infinite input; the bounded consequence is silent calculation corruption.
The record
- CVE
- CVE-2025-55554
- Published
- Sep 25, 2025
- Updated
- Sep 25, 2025
- Vendor
- Unknown vendor
- Product
- Unknown product
- Classifications
- CWE-190
- 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 is affected?
Affected products and versions are unavailable in this record.
Published CVSS scores
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Attacks
What attackers are doing with it
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Weakness, pattern, technique
Public exploit references
- PyTorch issue 151510 reproducerproof of concept · demonstrated
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Technologies
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Your stack
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