Categories
CVE-2021-29521

TensorFlow is an end-to-end open source platform for machine learning. Specifying a negative dense shape in…

Summary

Vulnerability reported (CVE-2021-29521). Risk of unauthorized operations or information disclosure. Exploitable via tf.raw_ops.SparseCountSparseOutput.

Original description

The description as published by the source.

TensorFlow is an end-to-end open source platform for machine learning. Specifying a negative dense shape in tf.raw_ops.SparseCountSparseOutput results in a segmentation fault being thrown out from the standard library as std::vector invariants are broken. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/8f7b60ee8c0206a2c99802e3a4d1bb55d2bc0624/tensorflow/core/kernels/count_ops.cc#L199-L213) assumes the first element of the dense shape is always positive and uses it to initialize a BatchedMap (i.e., std::vector>(https://github.com/tensorflow/tensorflow/blob/8f7b60ee8c0206a2c99802e3a4d1bb55d2bc0624/tensorflow/core/kernels/count_ops.cc#L27)) data structure. If the shape tensor has more than one element, num_batches is the first value in shape. Ensuring that the dense_shape argument is a valid tensor shape (that is, all elements are non-negative) solves this issue. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 and TensorFlow 2.3.3.

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-2021-29521 has been found.
Attackers can target a specific entry point like tf.raw_ops.SparseCountSparseOutput over the network to misuse the product.
Risk of unauthorized operations or information disclosure.
What to do: apply the vendor's official patched release.
If unsure, ask your IT team or search "CVE-2021-29521" on the vendor's site.

CVE-2021-29521
Attack vector: local / no user interaction
Attack surface: tf.raw_ops.SparseCountSparseOutput / shape / num_batches / dense_shape
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.SparseCountSparseOutput.

📍 Affected scope

Check the vendor advisory for the affected versions. Attack surface: tf.raw_ops.SparseCountSparseOutput / shape / num_batches / dense_shape.

🔥 Severity

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

🔧 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. 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. 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。

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":"2.3.0"},{"fixed":"2.3.3"},{"introduced":"2.4.0"},{"fixed":"2.4.2"}]}]

References

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