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CVE-2022-41894
Vulnerability in tensorflow (CVE-2022-41894)
Summary
vulnerability in tensorflow (CVE-2022-41894). Successful exploitation can lead to full system takeover. Exploitable via ``CONV_3D_TRANSPOSE``. Mitigation: upgrade to `2.8.4, 2.9.3, 2.10.1` or later.
AI summary snake-internal / snake-material-v2
A vulnerability tracked as **CVE-2022-41894** has been found in tensorflow.
Attackers can target a specific entry point like ``CONV_3D_TRANSPOSE`` over the network to misuse the product.
Successful exploitation can lead to full system takeover. CVSS score: ?/10.
What to do: upgrade tensorflow to **2.8.4, 2.9.3, 2.10.1** or later.
If unsure, ask your IT team or search "tensorflow CVE-2022-41894" on the vendor's site.
CVE-2022-41894 (tensorflow) — CWE-120 /
Attack vector: remote (network-reachable)
Attack surface: `CONV_3D_TRANSPOSE`
Patched: `2.8.4, 2.9.3, 2.10.1` — 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.
❓ What is the problem
**A vulnerability** (CWE-120) exists in tensorflow. Attackers reach the vulnerable code path via ``CONV_3D_TRANSPOSE`` without authentication.
📍 Affected scope
tensorflow — . Attack surface: `CONV_3D_TRANSPOSE`.
🔥 Severity
Severity: ?. Successful exploitation can lead to full system takeover
🔧 How to fix
Update to **2.8.4, 2.9.3, 2.10.1**.
🛡️ Workaround
Until the patch is applied: disable the affected feature, apply WAF rules, or restrict access via network ACLs.
🔍 Detection
Search webserver/proxy logs for unusual request patterns matching this CVE's known IOCs. Run `grep -r 'tensorflow' .` against your dependency files (package-lock.json, requirements.txt, go.sum) to find affected services.
Response Actions (7 steps)
Concrete steps and command examples for SOC/SRE teams to execute in order
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1Identify exposure identify
grep -r 'tensorflow' . | 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 `tensorflow` を grep し、稼働しているサービス・バージョンを把握する。
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6Apply patch patch
Upgrade tensorflow to 2.8.4, 2.9.3, 2.10.1ステージング環境で 2.8.4, 2.9.3, 2.10.1 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と、Step 3 で見つけた異常検知の続報チェックを含めること。
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7Post-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 Step 3 と同じログクエリでアラート再発が無いか継続監視。
Affected packages
Bitnami
tensorflow
[{"type":"SEMVER","events":[{"introduced":"0"},{"fixed":"2.8.4"},{"introduced":"2.9.0"},{"fixed":"2.9.3"},{"introduced":"2.10.0"},{"fixed":"2.10.1"}]}]
PyPI
tensorflow
[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"2.8.4"},{"introduced":"2.9.0"},{"fixed":"2.9.3"},{"introduced":"2.10.0"},{"fixed":"2.10.1"}]}]
References
- advisory https://nvd.nist.gov/vuln/detail/CVE-2022-41894
- advisory https://github.com/advisories/GHSA-h6q3-vv32-2cq5
- package https://github.com/tensorflow/tensorflow
- package https://pypi.org/project/tensorflow
- web https://github.com/tensorflow/tensorflow/blob/091e63f0ea33def7ecad661a5ac01dcafbafa90b/tensorflow/lite/kernels/internal/reference/conv3d_transpose.h#L121
- web https://github.com/tensorflow/tensorflow/commit/72c0bdcb25305b0b36842d746cc61d72658d2941
- web https://github.com/tensorflow/tensorflow/security/advisories/GHSA-h6q3-vv32-2cq5