CVE-2026-115922
ONNX: Denial of service via unchecked expansion of packed sub-byte tensors in ONNX Python APIs
Description
Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. Prior to 1.22.0, _unpack_2bit() and _unpack_4bit() resize unpacked arrays according to attacker-controlled TensorProto.dims without verifying that raw_data or int32_data encodes the declared number of elements. Materializing an untrusted UINT2, INT2, UINT4, INT4, or FLOAT4E2M1 tensor through onnx.numpy_helper.to_array() or onnx.reference.ReferenceEvaluator can therefore expand a small packed payload into a disproportionately large allocation and exhaust memory. This issue is fixed in version 1.22.0.
INFO
Published Date :
Oct. 26, 2026, 6:17 p.m.
Last Modified :
Oct. 26, 2026, 6:34 p.m.
Remotely Exploit :
No
Source :
[email protected]
CVSS Scores
| Score | Version | Severity | Vector | Exploitability Score | Impact Score | Source |
|---|---|---|---|---|---|---|
| CVSS 3.1 | MEDIUM | MITRE-CVE | ||||
| CVSS 3.1 | MEDIUM | [email protected] |
Solution
- Update ONNX to version 1.22.0 or later.
- Avoid using older versions of ONNX.
- Validate tensor data before processing.
References to Advisories, Solutions, and Tools
Here, you will find a curated list of external links that provide in-depth
information, practical solutions, and valuable tools related to
CVE-2026-115922.
CWE - Common Weakness Enumeration
While CVE identifies
specific instances of vulnerabilities, CWE categorizes the common flaws or
weaknesses that can lead to vulnerabilities. CVE-2026-115922 is
associated with the following CWEs:
Common Attack Pattern Enumeration and Classification (CAPEC)
Common Attack Pattern Enumeration and Classification
(CAPEC)
stores attack patterns, which are descriptions of the common attributes and
approaches employed by adversaries to exploit the CVE-2026-115922
weaknesses.
We scan GitHub repositories to detect new proof-of-concept exploits. Following list is a collection of public exploits and proof-of-concepts, which have been published on GitHub (sorted by the most recently updated).
Results are limited to the first 15 repositories due to potential performance issues.
The following list is the news that have been mention
CVE-2026-115922 vulnerability anywhere in the article.
The following table lists the changes that have been made to the
CVE-2026-115922 vulnerability over time.
Vulnerability history details can be useful for understanding the evolution of a vulnerability, and for identifying the most recent changes that may impact the vulnerability's severity, exploitability, or other characteristics.
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New CVE Received by [email protected]
Oct. 26, 2026
Action Type Old Value New Value Added Description Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. Prior to 1.22.0, _unpack_2bit() and _unpack_4bit() resize unpacked arrays according to attacker-controlled TensorProto.dims without verifying that raw_data or int32_data encodes the declared number of elements. Materializing an untrusted UINT2, INT2, UINT4, INT4, or FLOAT4E2M1 tensor through onnx.numpy_helper.to_array() or onnx.reference.ReferenceEvaluator can therefore expand a small packed payload into a disproportionately large allocation and exhaust memory. This issue is fixed in version 1.22.0. Added CVSS V3.1 AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H Added CWE CWE-789 Added Affected New affected value received. <a href="https://github.com/CVEProject/cvelistV5/blob/main/cves/2026/115xxx/CVE-2026-115922.json">CVE-2026-115922</a> Added Reference https://github.com/onnx/onnx/commit/05c1bc3bceceb8d3cf11e9e7fc7f19f971c44988 Added Reference https://github.com/onnx/onnx/commit/8de2cf6aa47928e6515ac6d9e1a8b4758886a7df Added Reference https://github.com/onnx/onnx/commit/dce5876d6cc6cc30157af7d26a752ef44976da8e Added Reference https://github.com/onnx/onnx/pull/8033 Added Reference https://github.com/onnx/onnx/pull/8038 Added Reference https://github.com/onnx/onnx/pull/8066 Added Reference https://github.com/onnx/onnx/releases/tag/v1.22.0 Added Reference https://github.com/onnx/onnx/security/advisories/GHSA-q69g-f4f5-v8m7