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CVE-2026-115921medium6.2

ONNX: Null Pointer Dereference in ScanInferenceFunction Due to Missing Required Attribute

Impact

ONNX versions 1.4.0 through 1.21.0 have a null pointer dereference vulnerability in the ScanInferenceFunction due to a missing required attribute, potentially causing denial of service. An application processing an untrusted model can be terminated or forced into an exceptional allocation path. The vulnerability requires local access to the ONNX library API or file boundary.

Summarized by @cf/meta/llama-3.3-70b-instruct-fp8-fast. Verify details against the original sources.

Affected packages

Start with the recorded fix for your release branch. Check your installed version and test compatibility before upgrading. Fixing this advisory does not rule out other vulnerabilities in the release.

onnx PyPI
Affected range Recorded fix
From 1.4.0 before 1.22.0Ecosystem versions1.22.0

Version evidence: OSV · GHSA-m4pr-6v3c-6fgr

View original version evidence (38 explicit versions)

Affected products

Vendor version evidence. Product records are separate from automatic dependency matching.

onnx · GitHub_M

onnx

1 range

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affected

>= 1.4.0, < 1.22.0

unaffected

unknown

Other versions: unknown

Original source description

Summary

ONNX shape inference did not safely validate the required Scan num_scan_inputs attribute. Two malformed values could terminate or disrupt the process:

  1. If the attribute was missing, ctx.getAttribute("num_scan_inputs") returned null and was dereferenced.
  2. If the attribute was negative, conversion to size_t produced a very large value that reached a vector allocation and raised std::length_error.

The negative-value variant passed onnx.checker.check_model() before reaching shape inference.

Technical details

The vulnerable Scan inference implementations used the following pattern:

auto num_scan_inputs =
    narrow_cast<size_t>(ctx.getAttribute("num_scan_inputs")->i());

This code neither checked the returned pointer nor rejected a negative signed value before converting it to an unsigned size. The pattern was present in the current Scan inference function and the older opset 8 and 9 paths.

The fix uses the required-attribute helper and checked narrowing:

auto num_scan_inputs =
    narrow<size_t>(getRequiredAttributeInt(ctx, "num_scan_inputs"));

Impact

An application that performs shape inference on an untrusted model can be terminated or forced into an exceptional allocation path, causing denial of service. No confidentiality or integrity impact was demonstrated.

Affected versions

  • Affected: ONNX 1.4.0 through 1.21.0
  • Patched: ONNX 1.22.0

ONNX 1.4.0 is the first release containing the vulnerable Scan shape-inference implementation.

Remediation

Upgrade to ONNX 1.22.0 or later.

Both reported models were re-tested against the published ONNX 1.23.2 wheel and correctly raise InferenceError.

Severity

The vulnerable ONNX component processes the malicious model through a local library API or file boundary and is not itself bound to a network stack. Applications that expose ONNX model processing over a network should calculate an Environmental score with Modified Attack Vector set to Network.

The two triggers remain in one advisory because they affect the same required attribute, share the same unsafe conversion path and remediation, and were fixed in the same release.

Inside the record

Evidence available

Package identity
Version evidence
Remediation guidance · not supplied
Weakness classification
Additional publishers

Describes the evidence in this view, not whether the product is safe.

Original records

CVE-2026-115921

View the latest unmodified CVE JSON from the official source. It may be newer than this imported page.

cve.new JSON →

Underlying weaknesses

The source’s classification of what caused the vulnerability.

CWE-195 ↗

CWE-195: Signed to Unsigned Conversion Error

GitHub_M

Related →
CWE-476 ↗

CWE-476: NULL Pointer Dereference

GitHub_M

Related →
Contributing organizations · 2
GitHub_M

Assigning organization

2026-10-26
CISA-ADP

Additional data publisher

2026-10-31

What changed

Follow changes
  1. CVE · CVE-2026-115921

    Observed 2026-10-31T01:57:42.824Z · upstream updated 2026-10-31T01:40:08.161Z

    Prioritization updated

    before

    []

    after

    [
      {
        "source": "CISA-ADP",
        "type": "SSVC",
        "role": "CISA Coordinator",
        "timestamp": "2026-10-31T01:39:56.289903Z",
        "decisions": [
          {
            "name": "Exploitation",
            "value": "none"
          },
          {
            "name": "Automatable",
            "value": "no"
          },
          {
            "name": "Technical Impact",
            "value": "partial"
          }
        ]
      }
    ]

Large field values are marked as truncated previews. Original source snapshots remain retained.

Showing up to 50 most recent observed changes.

References

6 sources