Medium · CVSS 6.2CVE-2026-115921

ONNX: Null Pointer Dereference in ScanInferenceFunction Due to Missing Required AttributeCVE-2026-115921

Answer in brief

CVE-2026-115921 records a Medium severity (CVSS 6.2) vulnerability in ONNX: Null Pointer Dereference in ScanInferenceFunction Due to Missing Required Attribute. The current sources do not mark it as known exploited. The current feed maps onnx/onnx (generic). Check affected ranges and fixed versions before updating.

Analysis pending evidence review

HOL Guard separates source facts from reviewed analysis. See the methodology.

Published Oct 26, 2026Updated Oct 26, 2026Source checked Oct 26, 2026First seen by HOL Oct 26, 2026Material review Oct 26, 2026

Upstream Advisory

Key facts

Risk: Medium · CVSS 6.2
Exploitation: Not marked as known exploited
Affected software: 1 mapped package or product
Fix availability: Available

Why this deserves its current priority

CVSS is 6.2. The current sources do not mark it as known exploited. Treat this as a source-backed prioritization signal, not a statement about your environment.

Analysis status

Analysis pending evidence review

Factual feed record only; HOL analysis is not approved for indexing. Read the methodology.

Affected scope and exposure questions

The current feed maps onnx/onnx (generic). Check affected ranges and fixed versions before updating.

Mapped affected packages and fixed versions
Package	Affected range	Fixed version
onnx/onnxgeneric	>=1.4.0 <1.22.0	1.22.0

Recommended response

Check inventory. Check lockfiles and deployed manifests for onnx/onnx.
Review the reported fix. Update onnx/onnx to 1.22.0 if you use the affected versions. Test the change in a non-production environment first.

Evidence timeline and material changes

Published upstream
Oct 26, 2026
Evidence: source:cvelist:source_dates:source-dates:record
Source modified
Oct 26, 2026
Evidence: source:cvelist:source_dates:source-dates:record
First seen by HOL
Oct 26, 2026

Sources and claim methodology

Upstream source description

Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. From 1.4.0 until 1.22.0, ScanInferenceFunction, ScanInferenceFunction_opset8, and ScanInferenceFunction_opset9 do not safely validate the required num_scan_inputs attribute. A missing attribute is dereferenced as a null pointer, while a negative value is converted to size_t and can reach an exceptional oversized allocation path. An untrusted model can therefore terminate or disrupt shape inference, including a negative-value model that can pass onnx.checker.check_model(). This issue is fixed in version 1.22.0.

Quoted source text, attributed separately from HOL analysis.