CVE-2026-115922
What it is
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.
At a glance
- Exploitability
- Can be exploited locally on the machine without logging in. High risk of service disruption.
- Exploit odds
- 0.1% chance of exploitation in the next 30 days (EPSS).
- Fix
- A patch, advisory or fixed version is referenced. Upgrade or apply it.
Timeline
- ReservedThe CVE id was reserved by its CNA
- PublishedDisclosed publicly on CVE.org and NVD
- Last updatedMost recent change to the record
Why it ranks here
- Exploited in the wild: no, CISA does not list it.
- Exploit odds: 0.1% in the next 30 days (EPSS).
- Severity: 6.2 MEDIUM (CVSS).
- Fix: a patch or advisory is linked.
Details
- Published
- Last modified
- Exploit probability
- 0.1% · EPSS, next 30 days
- Weakness
- CWE-789
- Record status
- Awaiting Analysis
Attack profile CVSS 3.1 · 6.2
- Attack vector
- Local
- Complexity
- Low
- Privileges needed
- None
- User interaction
- None
- Scope
- Unchanged
- Confidentiality
- None
- Integrity
- None
- Availability
- High
Raw vector
CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
Is it in your code?
Hand this to your coding agent. It searches your project for the affected products and checks versions. Nothing leaves your machine.
Read https://cve-list.com/agent/cve/CVE-2026-115922.md and follow it. Check whether this project is affected by CVE-2026-115922. Read only. Don't change anything and don't upload my code. Tell me yes, no or not sure, with the file as proof.
Fix and advisories
- https://github.com/onnx/onnx/commit/05c1bc3bceceb8d3cf11e9e7fc7f19f971c44988
- https://github.com/onnx/onnx/commit/8de2cf6aa47928e6515ac6d9e1a8b4758886a7df
- https://github.com/onnx/onnx/commit/dce5876d6cc6cc30157af7d26a752ef44976da8e
- https://github.com/onnx/onnx/pull/8033
- https://github.com/onnx/onnx/pull/8038
- https://github.com/onnx/onnx/pull/8066
- https://github.com/onnx/onnx/releases/tag/v1.22.0
- https://github.com/onnx/onnx/security/advisories/GHSA-q69g-f4f5-v8m7
References
- https://github.com/onnx/onnx/commit/05c1bc3bceceb8d3cf11e9e7fc7f19f971c44988
- https://github.com/onnx/onnx/commit/8de2cf6aa47928e6515ac6d9e1a8b4758886a7df
- https://github.com/onnx/onnx/commit/dce5876d6cc6cc30157af7d26a752ef44976da8e
- https://github.com/onnx/onnx/pull/8033
- https://github.com/onnx/onnx/pull/8038
- https://github.com/onnx/onnx/pull/8066
- https://github.com/onnx/onnx/releases/tag/v1.22.0
- https://github.com/onnx/onnx/security/advisories/GHSA-q69g-f4f5-v8m7