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CVE-2022-29209

Vulnerability in tensorflow (CVE-2022-29209)

Summary

Vulnerability in tensorflow (CVE-2022-29209). Risk of unauthorized operations or information disclosure. Exploitable via CHECK_LT. Mitigation: upgrade to 2.8.1 or later.

Original description

The description as published by the source.

Impact

The macros that TensorFlow uses for writing assertions (e.g., CHECK_LT, CHECK_GT, etc.) have an incorrect logic when comparing size_t and int values. Due to type conversion rules, several of the macros would trigger incorrectly.

Patches

We have patched the issue in GitHub commit b917181c29b50cb83399ba41f4d938dc369109a1 (merging GitHub PR #55730).

The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, as these are also affected and still in supported range.

For more information

Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.

Attribution

This vulnerability has been reported externally via a GitHub issue.

Source: OSV.dev (Open Source Vulnerabilities) NVD GitHub Advisory OSV

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-2022-29209 has been found in tensorflow.
Attackers can target a specific entry point like CHECK_LT over the network to misuse the product.
Risk of unauthorized operations or information disclosure.
What to do: upgrade tensorflow to 2.8.1 or later.
If unsure, ask your IT team or search "tensorflow CVE-2022-29209" on the vendor's site.

CVE-2022-29209 (tensorflow) — CWE-843
Attack vector: local / no user interaction
Attack surface: CHECK_LT / CHECK_GT / size_t / int
Patched: 2.8.1 — 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-843) exists in tensorflow. Attackers reach the vulnerable code path via CHECK_LT.

📍 Affected scope

Check the vendor advisory for the affected versions of tensorflow. Attack surface: CHECK_LT / CHECK_GT / size_t / int.

🔥 Severity

Severity: ?. Risk of unauthorized operations or information disclosure.

🔧 How to fix

Update to 2.8.1.

🛡️ 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

Concrete steps and command examples for SOC/SRE teams to execute in order

  1. 1
    Identify 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。

  2. 2
    Apply patch patch 
    Upgrade tensorflow to 2.8.1

    ステージング環境で 2.8.1 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を含めること。

  3. 3
    Post-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

PyPI tensorflow
[{"type":"ECOSYSTEM","events":[{"introduced":"2.8.0"},{"fixed":"2.8.1"}]}]
PyPI tensorflow-cpu
[{"type":"ECOSYSTEM","events":[{"introduced":"2.8.0"},{"fixed":"2.8.1"}]}]
PyPI tensorflow-gpu
[{"type":"ECOSYSTEM","events":[{"introduced":"2.8.0"},{"fixed":"2.8.1"}]}]

References

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