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A GitHub-reviewed security advisory, not necessarily under active exploitation the way our CISA KEV advisories are, but a real, disclosed vulnerability in an open-source dependency.
Affected packages
Vulnerable: >= 1.4.0, <= 1.21.0
Patched in 1.22.0
Details
ONNX shape inference did not safely validate the required Scan num_scan_inputs attribute. Two malformed values could terminate or disrupt the process:
ctx.getAttribute("num_scan_inputs") returned null and was dereferenced.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.
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"));
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.
ONNX 1.4.0 is the first release containing the vulnerable Scan shape-inference implementation.
Upgrade to ONNX 1.22.0 or later.
dd6bc92eaBoth reported models were re-tested against the published ONNX 1.23.2 wheel and correctly raise InferenceError.
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.
EPSS, exploit probability
Low0.13%
estimated chance of real-world exploitation in the next 30 days, higher than 2.7% of every CVE FIRST.org scores
Refreshed 10/28/2026, via FIRST.org's EPSS model, not CVSS, this measures likelihood of exploitation, not how severe it would be.
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A secure code review or supply chain review finds this before an advisory does.