Runtime crash via tensor-size integer overflow
Published Jul 11, 2025 · Updated Jul 11, 2025
Heap-buffer overflow in ExecuTorch 0.6.0 and earlier allows context-dependent attackers to crash the runtime through a crafted program file. The calculate_nbytes routine multiplies tensor dimensions and element size without overflow checks, allowing a wrapped allocation size during method loading. A host application must load attacker-controlled method metadata; the published assessment reports confidentiality loss and a runtime crash without data modification.
Summary
What happened
Heap-buffer overflow in ExecuTorch 0.6.0 and earlier allows context-dependent attackers to crash the runtime through a crafted program file. The calculate_nbytes routine multiplies tensor dimensions and element size without overflow checks, allowing a wrapped allocation size during method loading. A host application must load attacker-controlled method metadata; the published assessment reports confidentiality loss and a runtime crash without data modification.
The record
- CVE
- CVE-2025-30402
- Published
- Jul 11, 2025
- Updated
- Jul 11, 2025
- Vendor
- Meta Platforms, Inc.
- Product
- ExecuTorch
- Classifications
- CWE-122, T1203
- Attack vector
- network
- Privileges
- unauthenticated
Timeline
How it unfolded
- Jul 11, 2025CVE publishedPublication date reported by the CVE source.
- Jul 11, 2025Record updatedLatest update available in the CVE record.
Exploitability
Present is not the same as exploitable
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Is a vulnerable build present?
Compare these published version ranges with your installed build and any vendor patches.
- Affected versionversion=0 <https://github.com/pytorch/executorch/commit/93b1a0c15f7eda49b2bc46b5b4c49557b4e9810f
What conditions does exploitation require?
What is affected?
Published CVSS scores
CVSS describes severity. EPSS estimates exploitation probability.
Attacks
What attackers are doing with it
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Public exploit references
No public exploit references are available in this record.
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Technologies
Your stack
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Your stack
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