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ONNX CVE-2026-44512

| EUVDEUVD-2026-42355 MEDIUM
NULL Pointer Dereference (CWE-476)
2026-07-07 https://github.com/onnx/onnx GHSA-hwpq-hmq9-wj77
5.5
CVSS 3.1 · Vendor: https://github.com/onnx/onnx
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Severity by source

Vendor (https://github.com/onnx/onnx) PRIMARY
5.5 MEDIUM
AV:L/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:H
vuln.today AI
5.5 MEDIUM

File-based local delivery with required user invocation of convert_version(); crash-only impact means C:N/I:N, PR:N because no credentials are needed to supply a file.

3.1 AV:L/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:H
4.0 AV:L/AC:L/AT:N/PR:N/UI:A/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N
SUSE
MEDIUM
qualitative
Red Hat
6.5 MEDIUM
qualitative

Primary rating from Vendor (https://github.com/onnx/onnx).

CVSS VectorVendor: https://github.com/onnx/onnx

Attack Vector
Local
Attack Complexity
Low
Privileges Required
None
User Interaction
Required
Scope
Unchanged
Confidentiality
None
Integrity
None
Availability
High

Lifecycle Timeline

1
Analysis Generated
Jul 07, 2026 - 13:43 vuln.today

Blast Radius

ecosystem impact
† from your stack dependencies † transitive graph · vuln.today resolves 4-path depth
  • 6 pypi packages depend on onnx (6 direct, 0 indirect)

Ecosystem-wide dependent count for version 1.9.0.

DescriptionCVE.org

Summary

Null pointer dereference (SIGSEGV) in Upsample_6_7::adapt_upsample_6_7() (onnx/version_converter/adapters/upsample_6_7.h:31) when convert_version() processes a model with an Upsample node that has zero inputs. The adapter accesses node->inputs()[0]->sizes() without checking input count. 107-byte PoC crashes on Release build.

This is the same class of bug as the Cast adapter advisory (separate report) but in a different adapter, different file, and different operator.

Details

The Upsample 6→7 adapter validates attributes but not inputs:

cpp
// upsample_6_7.h:20-33
void adapt_upsample_6_7(..., Node* node) const {
    ONNX_ASSERTM(
        node->hasAttribute(width_scale_symbol) && node->hasAttribute(height_scale_symbol),
        "...")  // Attribute check PASSES

    auto width_scale = node->f(width_scale_symbol);
    auto height_scale = node->f(height_scale_symbol);

    auto input_shape = node->inputs()[0]->sizes();
    //                 ^^^^^^^^^^^^^^^^^^^^
    //                 OOB when inputs().size() == 0 → SIGSEGV
}

The PoC has an Upsample node at opset 6 with the required width_scale and height_scale attributes but zero inputs. The attribute assertions pass, then node->inputs()[0] on an empty ArrayRef:

  • Release builds (NDEBUG): bounds-check assertion compiled out → reads garbage pointer → SIGSEGV
  • Debug builds: assert(Index < Length) at array_ref.h:159 → SIGABRT

An Upsample node with zero inputs passes graphProtoToGraph() because the import code only resolves input names present in the protobuf.

PoC

python
import base64
import onnx
from onnx import version_converter

poc_b64 = "CAI6YQo8EgFZIghVcHNhbXBsZSoVCgt3aWR0aF9zY2FsZRUAAABAoAEBKhYKDGhlaWdodF9zY2FsZRUAAABAoAEBEgR0ZXN0YhsKAVkSFgoUCAESEAoCCAEKAggBCgIIBAoCCARCBAoAEAY="

model = onnx.load_from_string(base64.b64decode(poc_b64))
# CRASHES - Upsample_6_7 adapter dereferences empty inputs array
version_converter.convert_version(model, 7)
# SIGSEGV

107-byte PoC. Confirmed SIGSEGV on both onnx 1.21.0 (pip) and 1.22.0 (source build).

Impact

Any application that uses onnx.version_converter.convert_version() on untrusted models is vulnerable. This includes model conversion pipelines and tools that auto-upgrade opset versions for compatibility. The crash is unrecoverable (SIGSEGV).

This vulnerability is part of a systemic pattern across multiple version converter adapters. A full audit of all ~45 adapters was performed as part of the fix; eight adapters were found with the same class of unguarded indexed access (cast_9_8, softmax_12_13, softmax_13_12, upsample_6_7, upsample_9_10, group_normalization_20_21, broadcast_forward_compatibility, upsample_9_8) and all have been fixed in PR #7813.

AnalysisAI

Null pointer dereference in the ONNX Python library's version converter crashes any application that calls onnx.version_converter.convert_version() on a crafted model containing an Upsample node with zero inputs, producing an unrecoverable SIGSEGV. Affected versions include at minimum onnx 1.21.0 and 1.22.0, confirmed by a 107-byte public proof-of-concept; the vulnerability is part of a systemic pattern spanning eight adapters. No public active exploitation is confirmed in CISA KEV, but the trivially small PoC eliminates any meaningful exploitation barrier for threat actors targeting ML model conversion pipelines.

Technical ContextAI

The ONNX Python package (pkg:pip/onnx) ships a C++ version-conversion framework with per-operator adapters that upgrade ONNX models between opset versions. The affected adapter Upsample_6_7::adapt_upsample_6_7() in onnx/version_converter/adapters/upsample_6_7.h handles the opset 6-to-7 transition for the Upsample operator. CWE-476 (Null Pointer Dereference) describes the root cause: the adapter validates the presence of width_scale and height_scale attributes but unconditionally dereferences node->inputs()[0] without first checking that the inputs array is non-empty. In release builds compiled with NDEBUG, LLVM ArrayRef's bounds assertion is elided, so an empty-array access reads a garbage pointer and faults with SIGSEGV; debug builds trigger SIGABRT via assert(Index < Length) at array_ref.h:159. The graph import path graphProtoToGraph() permits nodes with zero inputs because it only resolves input names explicitly listed in the protobuf, allowing the malformed node to pass graph loading and reach the adapter unchecked. The same unguarded indexed-access pattern was independently confirmed in seven additional adapters (cast_9_8, softmax_12_13, softmax_13_12, upsample_9_10, group_normalization_20_21, broadcast_forward_compatibility, upsample_9_8), all remediated together in PR #7813 and the associated fix PR #7916.

RemediationAI

Upgrade the onnx Python package to the first release that incorporates PR #7916 (https://github.com/onnx/onnx/pull/7916); check https://github.com/onnx/onnx/releases for the tagged release following that merge, as the exact patched version is not independently confirmed from available data - the v1.22.0 release tag is referenced but that version was confirmed vulnerable, so verify the changelog before treating it as fixed. As a compensating control where immediate upgrade is not feasible, restrict onnx.version_converter.convert_version() to models sourced exclusively from internal, trusted repositories; do not invoke the converter on user-uploaded, network-received, or third-party ONNX files. Running the conversion step in an isolated subprocess with a hard timeout and restart-on-crash logic provides crash containment at the cost of added latency and operational complexity, preventing a single malformed model from taking down a shared conversion service. Note that onnx.check_model() does not currently guard against this specific graph malformation and should not be relied upon as a standalone filter.

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Vendor StatusVendor

SUSE

Severity: Moderate

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CVE-2026-44512 vulnerability details – vuln.today

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