Categories
CVE-2021-37648

Vulnerability in tensorflow (CVE-2021-37648)

Summary

Vulnerability in tensorflow (CVE-2021-37648). Successful exploitation can lead to full system takeover. Exploitable via tf.raw_ops.SaveV2. Mitigation: upgrade to 2.5.1 or later.

Original description

The description as published by the source.

TensorFlow is an end-to-end open source platform for machine learning. In affected versions the code for tf.raw_ops.SaveV2 does not properly validate the inputs and an attacker can trigger a null pointer dereference. The implementation uses ValidateInputs to check that the input arguments are valid. This validation would have caught the illegal state represented by the reproducer above. However, the validation uses OP_REQUIRES which translates to setting the Status object of the current OpKernelContext to an error status, followed by an empty return statement which just terminates the execution of the function it is present in. However, this does not mean that the kernel execution is finalized: instead, execution continues from the next line in Compute that follows the call to ValidateInputs. This is equivalent to lacking the validation. We have patched the issue in GitHub commit 9728c60e136912a12d99ca56e106b7cce7af5986. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

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-2021-37648 has been found in tensorflow.
Attackers can target a specific entry point like tf.raw_ops.SaveV2 over the network to misuse the product.
Successful exploitation can lead to full system takeover.
What to do: upgrade tensorflow to 2.5.1 or later.
If unsure, ask your IT team or search "tensorflow CVE-2021-37648" on the vendor's site.

CVE-2021-37648 (tensorflow) — CWE-476
Attack vector: local / no user interaction
Attack surface: tf.raw_ops.SaveV2 / ValidateInputs / OP_REQUIRES / Status
Patched: 2.5.1 — 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-476) exists in tensorflow. Attackers reach the vulnerable code path via tf.raw_ops.SaveV2.

📍 Affected scope

Check the vendor advisory for the affected versions of tensorflow. Attack surface: tf.raw_ops.SaveV2 / ValidateInputs / OP_REQUIRES / Status.

🔥 Severity

Severity: ?. Successful exploitation can lead to full system takeover.

🔧 How to fix

Update to 2.5.1.

🛡️ 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 2.5.1

    ステージング環境で 2.5.1 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":"2.5.0"},{"fixed":"2.5.1"}]}]
PyPI tensorflow-cpu
[{"type":"ECOSYSTEM","events":[{"introduced":"2.5.0"},{"fixed":"2.5.1"}]}]
PyPI tensorflow-gpu
[{"type":"ECOSYSTEM","events":[{"introduced":"2.5.0"},{"fixed":"2.5.1"}]}]

References

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