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
Improper validation of STRING tensor offsets could allows malformed string metadata to trigger out of bounds access during constant tensor import in Samsung Open Source ONE Affected version is prior to commit 1.30.0.
AnalysisAI
Improper validation of STRING tensor offsets in Samsung Open Source ONE prior to commit 1.30.0 allows local attackers with user interaction to trigger out-of-bounds memory access during constant tensor import, potentially causing information disclosure, data modification, or denial of service. The vulnerability affects the tensor metadata parsing logic when processing malformed string tensor definitions.
Technical ContextAI
Samsung Open Source ONE is a neural network compiler and optimization framework. The vulnerability resides in the constant tensor import functionality, specifically in the validation logic for STRING tensor offset metadata. STRING tensors in neural network frameworks require careful offset tracking to prevent buffer overruns. The improper validation of these offsets (CWE-1284: Improper Validation of Specified Quantity in Input) allows an attacker to craft malformed tensor metadata that bypasses bounds checks, leading to out-of-bounds read or write access to memory regions adjacent to the tensor data structure. This occurs during the import phase when the framework parses and instantiates constant tensors from model files or serialized formats.
RemediationAI
Apply the fix available in commit 1.30.0 or later of the Samsung Open Source ONE repository. Users should upgrade to version 1.30.0 or newer once released as a stable version. The fix is available at https://github.com/Samsung/ONE/pull/16481. Until patching is possible, implement input validation on neural network model files before import by using a model verification tool or sandboxing the model loading process in an isolated environment. Restrict file system permissions to prevent unauthorized modification of model files that could introduce malformed tensor metadata. Disable automatic model loading from untrusted sources and require explicit user review before importing neural network models.
Arbitrary file write as SYSTEM in Samsung MagicINFO 9 Server before version 21.1050 allows remote attackers to place att
Samsung MagicINFO 9 Server contains a path traversal vulnerability allowing unauthenticated attackers to write arbitrary
Multiple stack-based buffer overflows in the BackupToAvi method in the (1) UMS_Ctrl 1.5.1.1 and (2) UMS_Ctrl_STW 2.0.1.0
Web Viewer 1.0.0.193 on Samsung SRN-1670D devices suffers from an Unrestricted file upload vulnerability: 'network_ssl_u
Web Viewer 1.0.0.193 on Samsung SRN-1670D devices allows remote attackers to read arbitrary files via a request to an un
Samsung Internet Browser 5.4.02.3 allows remote attackers to bypass the Same Origin Policy and obtain sensitive informat
Buffer overflow in the PrepareSync method in the SyncService.dll ActiveX control in Samsung Kies before 2.5.1.12123_2_7
The Samsung D6000 TV and possibly other products allow remote attackers to cause a denial of service (continuous restart
The Samsung D6000 TV and possibly other products allows remote attackers to cause a denial of service (crash) via a long
The ConnectDDNS method in the (1) STWConfigNVR 1.1.13.15 and (2) STWConfig 1.1.14.13 ActiveX controls in Samsung NET-i v
Multiple directory traversal vulnerabilities in Samsung SyncThru 6 before 1.0 allow remote attackers to delete arbitrary
Stack-based buffer overflow in the RequestScreenOptimization function in the XProcessControl.ocx ActiveX control in msls
Same technique Information Disclosure
View allShare
External POC / Exploit Code
Leaving vuln.today
EUVD-2026-24628
GHSA-mqr4-9x5m-973r