CVE-2026-40448
Integer Overflow in Samsung Open Source ONE Tensor Allocation
Publication date: 2026-04-22
Last updated on: 2026-04-27
Assigner: Samsung TV & Appliance
Description
Description
CVSS Scores
EPSS Scores
| Probability: | |
| Percentile: |
Meta Information
Affected Vendors & Products
| Vendor | Product | Version / Range |
|---|---|---|
| samsung | one | to 1.30.0 (exc) |
Helpful Resources
Exploitability
| CWE ID | Description |
|---|---|
| CWE-190 | The product performs a calculation that can produce an integer overflow or wraparound when the logic assumes that the resulting value will always be larger than the original value. This occurs when an integer value is incremented to a value that is too large to store in the associated representation. When this occurs, the value may become a very small or negative number. |
Attack-Flow Graph
AI Powered Q&A
Can you explain this vulnerability to me?
This vulnerability is an integer overflow issue in the memory size calculation for tensors within the Samsung Open Source ONE framework. The original code used a 32-bit signed integer to represent the number of elements in a tensor, which could overflow when handling very large tensors. This overflow causes incorrect memory allocation sizes, potentially leading to insufficient memory allocation.
The problem was fixed by changing the data type to a 64-bit integer, adding explicit overflow checks before size calculations, and using safer functions and casting methods to handle large tensor sizes. The fix was applied to key components responsible for tensor operations and memory management.
How can this vulnerability impact me? :
This vulnerability can lead to insufficient memory allocation for large tensors, which may cause memory corruption or security breaches. Specifically, because the memory size calculation can overflow, the system might allocate less memory than needed, potentially resulting in crashes, data corruption, or exploitable conditions that could compromise the integrity or availability of the application using Samsung ONE.
How can this vulnerability be detected on my network or system? Can you suggest some commands?
This vulnerability relates to an integer overflow in tensor allocation size calculation within the Samsung Open Source ONE framework. Detection would primarily involve inspecting the version of Samsung ONE in use to determine if it is prior to commit 1.30.0, which is affected.
Since the issue is internal to tensor memory allocation and not network-exposed, direct network detection commands are not applicable.
To detect if your system is vulnerable, you can check the installed Samsung ONE version or source code commit. For example, if you have access to the source repository, you can run:
- git log -1 --oneline
- git show 1.30.0
If the version or commit is older than 1.30.0, your system is vulnerable.
What immediate steps should I take to mitigate this vulnerability?
The immediate mitigation step is to update Samsung Open Source ONE to version 1.30.0 or later, where the integer overflow vulnerability has been fixed.
The fix includes changing the data type for tensor element counts to 64-bit integers, adding explicit overflow checks, and using safer functions for large tensor size calculations.
If updating is not immediately possible, avoid processing very large tensors that could trigger the overflow condition.
How does this vulnerability affect compliance with common standards and regulations (like GDPR, HIPAA)?:
The provided information does not specify any direct impact of this vulnerability on compliance with common standards and regulations such as GDPR or HIPAA.