8.6
CVE-2026-34445
- EPSS 0.06%
- Veröffentlicht 01.04.2026 17:30:19
- Zuletzt bearbeitet 15.04.2026 15:08:13
- Quelle security-advisories@github.com
- CVE-Watchlists
- Unerledigt
Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. Prior to version 1.21.0, the ExternalDataInfo class in ONNX was using Python’s setattr() function to load metadata (like file paths or data lengths) directly from an ONNX model file. It didn’t check if the "keys" in the file were valid. Due to this, an attacker could craft a malicious model that overwrites internal object properties. This issue has been patched in version 1.21.0.
Verknüpft mit AI von unstrukturierten Daten zu bestehenden CPE der NVD
Daten sind bereitgestellt durch National Vulnerability Database (NVD)
Linuxfoundation ≫ Onnx Version < 1.21.0
| Typ | Quelle | Score | Percentile |
|---|---|---|---|
| EPSS | FIRST.org | 0.06% | 0.176 |
| Quelle | Base Score | Exploit Score | Impact Score | Vector String |
|---|---|---|---|---|
| security-advisories@github.com | 8.6 | 3.9 | 4.7 |
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:H
|
CWE-20 Improper Input Validation
The product receives input or data, but it does not validate or incorrectly validates that the input has the properties that are required to process the data safely and correctly.
CWE-400 Uncontrolled Resource Consumption
The product does not properly control the allocation and maintenance of a limited resource, thereby enabling an actor to influence the amount of resources consumed, eventually leading to the exhaustion of available resources.
CWE-915 Improperly Controlled Modification of Dynamically-Determined Object Attributes
The product receives input from an upstream component that specifies multiple attributes, properties, or fields that are to be initialized or updated in an object, but it does not properly control which attributes can be modified.