Out-of-Bounds Read in onnx (CVE-2026-63632)
Summary
Vulnerability in onnx (CVE-2026-63632). Risk of unauthorized operations or information disclosure. Exploitable via B_shape. Mitigation: upgrade to 1.22.0 or later.
Original description
The description as published by the source.
Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. From 1.3.0 until 1.22.0, onnx.version_converter.convert_version() can perform an out-of-bounds read in Gemm_7_6::adapt_gemm_7_6() in onnx/version_converter/adapters/gemm_7_6.h when a Gemm node has input tensors with fewer than two dimensions because B_shape[1], A_shape[0], or A_shape[1] is accessed without a rank check, potentially causing a process crash during an opset 7 to 6 downgrade. This issue is fixed in version 1.22.0.
Source: GitHub Security Advisories (Global) NVD GitHub Advisory
Auto-generated summary
Assembled by SecPulse from the source data (CVSS, CWE, affected versions) using templates — no AI involved. Check the original description and references below for exact details.
A vulnerability tracked as CVE-2026-63632 has been found in onnx.
Attackers can target a specific entry point like B_shape over the network to misuse the product.
Risk of unauthorized operations or information disclosure. CVSS score: 3.3/10.
What to do: upgrade onnx to 1.22.0 or later.
If unsure, ask your IT team or search "onnx CVE-2026-63632" on the vendor's site.
CVE-2026-63632 (onnx) — CWE-125 / CVSS v3 3.3
Attack vector: local / unauthenticated
Attack surface: B_shape / InferShapes / tensorShapeProtoToDimensions
Patched: 1.22.0 — apply immediately
Plan: 1) Audit SBOM/dependencies, 2) Stage→prod upgrade, 3) Add WAF/proxy monitoring on affected endpoints, 4) Hunt IOCs in logs.
Refs: see the GHSA / vendor advisory / patched release linked on this page.
Out-of-bounds read (CWE-125) exists in onnx. Attackers reach the vulnerable code path via B_shape without authentication.
Check the vendor advisory for the affected versions of onnx. Attack surface: B_shape / InferShapes / tensorShapeProtoToDimensions.
Severity: Low (CVSS 3.3/10). Risk of unauthorized operations or information disclosure.
Update to 1.22.0.
Until the patch is applied: disable the affected feature, apply WAF rules, or restrict access via network ACLs.
Search webserver/proxy logs for unusual request patterns matching this CVE's known IOCs. Run grep -r 'onnx' . against your dependency files (package-lock.json, requirements.txt, go.sum) to find affected services.
Response actions
Concrete steps and command examples for SOC/SRE teams to execute in order
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1Identify exposure identify
grep -r 'onnx' . | grep -v node_modulesリポジトリと本番環境の依存ファイル (package-lock.json / requirements.txt / go.sum / Gemfile.lock 等) で
onnxを grep し、稼働しているサービス・バージョンを把握する。 -
2Apply patch patch
Upgrade onnx to 1.22.0ステージング環境で 1.22.0 に上げて回帰テスト → 本番反映。回帰テストはアプリの主要ハッピーパスを含めること。
-
3Post-deployment verification verify
Confirm patched version is live in productionパッチ適用後、ステージングで PoC または同等の悪用パターンを再現して脆弱性が閉じたことを確認。本番ではアクセスログ・WAF でアラート再発が無いか継続監視。
Affected packages
Fix status by distribution
Fixed packages published by each distribution for this CVE
- Debian DEBIAN-CVE-2026-63632 onnx
- Ubuntu UBUNTU-CVE-2026-63632 onnx
References
- advisory github.com
- advisory github.com
- advisory nvd.nist.gov
- advisory github.com
- package github.com
- package pypi.org
- patch github.com
- patch github.com
- web github.com