EUVD-2026-24614
GHSA-cfg6-vcc7-59p9
Severity by source
AV:L/AC:H/PR:N/UI:R/S:U/C:N/I:L/A:H
Primary rating from NVD · only source for this CVE.
CVSS VectorNVD
CVSS:3.1/AV:L/AC:H/PR:N/UI:R/S:U/C:N/I:L/A:H
Lifecycle Timeline
4DescriptionCVE.org
Potential Integer overflow in tensor allocation size calculation could lead to insufficient memory allocation for large tensors in Samsung Open Source ONE. Affected version is prior to commit 1.30.0.
AnalysisAI
Integer overflow in tensor allocation size calculation within Samsung Open Source ONE prior to version 1.30.0 allows local attackers with user interaction to cause denial of service or memory corruption. The vulnerability arises when processing large tensors, where insufficient memory allocation due to integer wraparound can lead to heap corruption. While CVSS indicates moderate severity (5.3), the high attack complexity and user interaction requirements limit practical exploitation.
Technical ContextAI
Samsung Open Source ONE is a neural network compiler framework used for mobile and edge device optimization. The vulnerability exists in the tensor memory allocation subsystem, where an integer overflow in size calculation (CWE-190) causes the allocator to reserve less memory than required for large tensor objects. This is a classic integer wraparound flaw: when computing allocation size, an arithmetic operation on large values overflows, wrapping to a smaller value. The subsequent memory allocation proceeds with this underestimated size, enabling heap buffer overflow when the tensor data is written. The CPE identifies the vulnerable product as Samsung Open Source ONE across all configurations prior to the patched version.
RemediationAI
Upgrade Samsung Open Source ONE to version 1.30.0 or later, which includes the fix for integer overflow in tensor allocation. For organizations unable to immediately upgrade, implement input validation to reject neural network models exceeding specific tensor size thresholds until patching is completed-specifically, restrict model loading to those with total tensor allocation below a safe computed limit (e.g., 2GB for 32-bit systems, adjusted per platform memory architecture). This workaround trades functionality (rejection of large-model support) for security but is practical for edge deployments where model size is typically bounded by device memory anyway. Monitor application logs for allocation failures or out-of-memory errors when processing untrusted models, as these may indicate exploitation attempts. The fix is available via GitHub and should be integrated into any downstream distributions or forks of Samsung ONE.
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Same weakness CWE-190 – Integer Overflow or Wraparound
View allSame technique Integer Overflow
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External POC / Exploit Code
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