TensorFlow is an end-to-end open source platform for machine… (CVE-2021-29546)

Summary

Vulnerability reported (CVE-2021-29546). Successful exploitation can lead to full system takeover. Exploitable via tf.raw_ops.QuantizedBiasAdd.

Original description

The description as published by the source.

TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger an integer division by zero undefined behavior in tf.raw_ops.QuantizedBiasAdd. This is because the implementation of the Eigen kernel(https://github.com/tensorflow/tensorflow/blob/61bca8bd5ba8a68b2d97435ddfafcdf2b85672cd/tensorflow/core/kernels/quantization_utils.h#L812-L849) does a division by the number of elements of the smaller input (based on shape) without checking that this is not zero. 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 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-2021-29546 has been found.
Attackers can target a specific entry point like tf.raw_ops.QuantizedBiasAdd over the network to misuse the product.
Successful exploitation can lead to full system takeover.
What to do: apply the vendor's official patched release.
If unsure, ask your IT team or search "CVE-2021-29546" on the vendor's site.

CVE-2021-29546
Attack vector: local / no user interaction
Attack surface: tf.raw_ops.QuantizedBiasAdd
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 (unclassified) has been reported. Attackers reach the vulnerable code path via tf.raw_ops.QuantizedBiasAdd.

📍 Affected scope

Check the vendor advisory for the affected versions. Attack surface: tf.raw_ops.QuantizedBiasAdd.

🔥 Severity

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

🔧 How to fix

Update to the patched release per vendor advisory.

🛡️ 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. Audit SBOM/dependencies to find affected services.

Response actions

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

1
Identify exposure identify
```
Audit SBOM/dependencies for affected components.
```
資産台帳・SBOM・依存マニフェストで影響コンポーネントを特定する。
2
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。

References

patch github.com
patch github.com