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Missing validation causes `tf.sparse.split` to crash when `axis` is a tuple

Moderate
mihaimaruseac published GHSA-43q8-3fv7-pr5x Feb 2, 2022

Package

pip tensorflow, tensorflow-cpu, tensorflow-gpu (pip)

Affected versions

< 2.8.0

Patched versions

2.5.3, 2.6.3, 2.7.1

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.

Severity

Moderate

CVE ID

CVE-2021-41206

Weaknesses

No CWEs