EUVD-2026-24620
GHSA-qjcj-728w-wq7q
Severity by source
AV:L/AC:L/PR:N/UI:R/S:U/C:L/I:L/A:H
Primary rating from NVD · only source for this CVE.
CVSS VectorNVD
CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:L/I:L/A:H
Lifecycle Timeline
4DescriptionCVE.org
Integer overflow in memory copy size calculation in Samsung Open Source ONE could lead to invalid memory operations with large tensor shapes. Affected version is prior to commit 1.30.0.
AnalysisAI
Integer overflow in memory copy size calculation in Samsung Open Source ONE prior to commit 1.30.0 allows local attackers with user privileges to trigger invalid memory operations by supplying tensors with large shapes, potentially causing information disclosure, data corruption, or denial of service. The vulnerability requires user interaction (UI:R) and operates with low attack complexity on local systems. No public exploit code or active exploitation has been identified.
Technical ContextAI
Samsung Open Source ONE is a neural network compilation framework that processes tensor operations. The vulnerability exists in memory allocation logic used for tensor data copying. When processing tensors with large shape dimensions, an integer overflow occurs in the size calculation before memory copy operations, causing the allocated buffer size to be smaller than the actual copy operation requires. This is a classic CWE-190 integer overflow condition where large input values wrap around to small values, bypassing safety checks. The affected component likely operates within the tensor shape validation and memory management subsystem of the compilation or inference pipeline.
RemediationAI
Update Samsung Open Source ONE to version 1.30.0 or later, which includes the fix for the integer overflow in memory copy size calculation. The patched version is available directly from the Samsung/ONE GitHub repository. For systems unable to immediately upgrade, implement strict validation of tensor input shapes before processing, enforcing maximum dimension limits that prevent integer overflow in size calculations, though this may limit the variety of models that can be processed. Additionally, restrict execution of ONE framework processing to sandboxed environments or containers with memory limits to prevent system-wide impact from memory corruption. Disable execution of machine learning models from untrusted sources until patching is applied. Monitor systems for crashes or memory errors in ONE-based applications, as these may indicate exploitation attempts.
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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
Leaving vuln.today