Vulnerability in tensorflow (CVE-2021-29550)

Summary

Vulnerability in tensorflow (CVE-2021-29550). Risk of unauthorized operations or information disclosure. Exploitable via tf.raw_ops.FractionalAvgPool. Mitigation: upgrade to 2.4.2 or later.

Original description

The description as published by the source.

TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a runtime division by zero error and denial of service in tf.raw_ops.FractionalAvgPool. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/acc8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_avg_pool_op.cc#L85-L89) computes a divisor quantity by dividing two user controlled values. The user controls the values of input_size[i] and pooling_ratio_[i] (via the value.shape() and pooling_ratio arguments). If the value in input_size[i] is smaller than the pooling_ratio_[i], then the floor operation results in output_size[i] being 0. The DCHECK_GT line is a no-op outside of debug mode, so in released versions of TF this does not trigger. Later, these computed values are used as arguments(https://github.com/tensorflow/tensorflow/blob/acc8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_avg_pool_op.cc#L96-L99) to GeneratePoolingSequence(https://github.com/tensorflow/tensorflow/blob/acc8ee69f5f46f92a3f1f11230f49c6ac266f10c/tensorflow/core/kernels/fractional_pool_common.cc#L100-L108). There, the first computation is a division in a modulo operation. Since output_length can be 0, this results in runtime crashing. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected an…

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-2021-29550 has been found in tensorflow.
Attackers can target a specific entry point like tf.raw_ops.FractionalAvgPool over the network to misuse the product.
Risk of unauthorized operations or information disclosure.
What to do: upgrade tensorflow to 2.4.2 or later.
If unsure, ask your IT team or search "tensorflow CVE-2021-29550" on the vendor's site.

CVE-2021-29550 (tensorflow) — CWE-369
Attack vector: local / no user interaction
Attack surface: tf.raw_ops.FractionalAvgPool / pooling_ratio / DCHECK_GT / GeneratePoolingSequence
Patched: 2.4.2 — 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-369) exists in tensorflow. Attackers reach the vulnerable code path via tf.raw_ops.FractionalAvgPool.

📍 Affected scope

Check the vendor advisory for the affected versions of tensorflow. Attack surface: tf.raw_ops.FractionalAvgPool / pooling_ratio / DCHECK_GT / GeneratePoolingSequence.

🔥 Severity

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

🔧 How to fix

Update to 2.4.2.

🛡️ 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
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
Apply patch patch
```
Upgrade tensorflow to 2.4.2
```
ステージング環境で 2.4.2 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
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":"2.4.0"},{"fixed":"2.4.2"}]}]

PyPI tensorflow-cpu

[{"type":"ECOSYSTEM","events":[{"introduced":"2.4.0"},{"fixed":"2.4.2"}]}]

PyPI tensorflow-gpu

[{"type":"ECOSYSTEM","events":[{"introduced":"2.4.0"},{"fixed":"2.4.2"}]}]

Bitnami tensorflow

[{"type":"SEMVER","events":[{"introduced":"0"},{"fixed":"2.1.4"},{"introduced":"2.2.0"},{"fixed":"2.2.3"},{"introduced":"2.3.0"},{"fixed":"2.3.3"},{"introduced":"2.4.0"},{"fixed":"2.4.2"}]}]

References

advisory github.com
advisory github.com
package github.com
web nvd.nist.gov
web github.com
web github.com
web github.com