Out-of-Bounds Write in tensorflow (CVE-2022-29208)
Summary
Out-of-bounds write in tensorflow (CVE-2022-29208). Data can be tampered with by attackers. Exploitable via tf.raw_ops.EditDistance. Mitigation: upgrade to 2.8.1 or later.
Original description
The description as published by the source.
TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of tf.raw_ops.EditDistance has incomplete validation. Users can pass negative values to cause a segmentation fault based denial of service. In multiple places throughout the code, one may compute an index for a write operation. However, the existing validation only checks against the upper bound of the array. Hence, it is possible to write before the array by massaging the input to generate negative values for loc. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this 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-2022-29208 has been found in tensorflow.
Attackers can target a specific entry point like tf.raw_ops.EditDistance over the network to misuse the product.
Data can be tampered with by attackers.
What to do: upgrade tensorflow to 2.8.1 or later.
If unsure, ask your IT team or search "tensorflow CVE-2022-29208" on the vendor's site.
CVE-2022-29208 (tensorflow) — CWE-787
Attack vector: local / no user interaction
Attack surface: tf.raw_ops.EditDistance / loc
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.
Out-of-bounds write (CWE-787) exists in tensorflow. Attackers reach the vulnerable code path via tf.raw_ops.EditDistance.
Check the vendor advisory for the affected versions of tensorflow. Attack surface: tf.raw_ops.EditDistance / loc.
Severity: ?. Data can be tampered with by attackers.
Update to 2.8.1.
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 '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
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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。 -
2Apply 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。
-
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
References
- advisory github.com
- advisory nvd.nist.gov
- advisory github.com
- package github.com
- patch github.com
- web github.com
- web github.com
- web github.com
- web github.com