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Improper Validation of Integrity Check Value in TensorFlowGHSA-43q8-3fv7-pr5x

HIGHFix: tensorflow/tensorflow#53695

GHSA-43q8-3fv7-pr5x is a high-severity (CVSS 7) vulnerability in tensorflow. A fix is available for tensorflow — see the affected versions and patch details below.

Published
Updated
Affected
9 pkgs
Patched
9 / 9
Exploits
None indexed
Exploitation data as of Dec 5, 2024 · OSV.dev, FIRST.org (EPSS)

Real-World Exposure

9 pkgs affected
🐍tensorflow🐍tensorflow🐍tensorflow🐍tensorflow-cpu🐍tensorflow-cpu🐍tensorflow-cpu🐍tensorflow-gpu🐍tensorflow-gpu+1 more

Real-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.

Description

Impact

The implementation of tf.sparse.split does not fully validate the input arguments. Hence, a malicious user can trigger a denial of service via a segfault or a heap OOB read:

import tensorflow as tf
data = tf.random.uniform([1, 32, 32], dtype=tf.float32)
axis = [1, 2]
x = tf.sparse.from_dense(data)
result = tf.sparse.split(x,3, axis=axis)

The code assumes axis is a scalar. This is another instance of TFSA-2021-190 (CVE-2021-41206).

Patches

We have patched the issue in GitHub commit 61bf91e768173b001d56923600b40d9a95a04ad5 (merging #53695).

The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

For more information

Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.

Attribution

This vulnerability has been reported externally via a GitHub issue.

Affected Packages

9 total 9 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPItensorflowall versions2.5.3pip install --upgrade 'tensorflow==2.5.3'
🐍PyPItensorflow≥ 2.6.0&&< 2.6.32.6.3pip install --upgrade 'tensorflow==2.6.3'
🐍PyPItensorflow≥ 2.7.0&&< 2.7.12.7.1pip install --upgrade 'tensorflow==2.7.1'
🐍PyPItensorflow-cpuall versions2.5.3pip install --upgrade 'tensorflow-cpu==2.5.3'
🐍PyPItensorflow-cpu≥ 2.6.0&&< 2.6.32.6.3pip install --upgrade 'tensorflow-cpu==2.6.3'
🐍PyPItensorflow-cpu≥ 2.7.0&&< 2.7.12.7.1pip install --upgrade 'tensorflow-cpu==2.7.1'

Detection & mitigation playbook

Open-source dependency
  1. Detect

    Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for tensorflow, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.

  2. Fix

    Update tensorflow to 2.5.3 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-43q8-3fv7-pr5x is resolved across your whole dependency graph.

  3. Workarounds

    Stop feeding it untrusted input: reject or quarantine files and payloads from unverified sources until you can upgrade, restrict accepted formats to the ones you actually need, and run the parsing or decoding step in a least-privileged sandbox or short-lived worker so a crash or corrupted read cannot reach the rest of the process.

Frequently Asked Questions

### Impact The implementation of [`tf.sparse.split`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/sparse_split_op.cc#L26-L102) does not fully validate the input arguments. Hence, a malicious user can trigger a denial of service via a segfault or a heap OOB read: ```python import tensorflow as tf data = tf.random.uniform([1, 32, 32], dtype=tf.float32) axis = [1, 2] x = tf.sparse.from_dense(data) result = tf.sparse.split(x,3, axis=axis) ``` The code assumes `axis` is a scalar. This is another instance of [TFSA-2021-190](https://g
O3 Security · Impact-Aware SCA

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Improper Validation of Integrity Check Value in TensorFlow