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Security Advisories: MDE2OlNlY3VyaXR5QWR2aXNvcnlHSFNBLXFnNDgtODVoZy1tcWM1

Division by 0 in `DenseCountSparseOutput`


An attacker can cause a denial of service via a FPE runtime error in tf.raw_ops.DenseCountSparseOutput:

import tensorflow as tf

values = tf.constant([], shape=[0, 0], dtype=tf.int64)
weights = tf.constant([])

  values=values, weights=weights,
  minlength=-1, maxlength=58, binary_output=True)

This is because the implementation computes a divisor value from user data but does not check that the result is 0 before doing the division:

int num_batch_elements = 1;
for (int i = 0; i < num_batch_dimensions; ++i) {
  num_batch_elements *= data.shape().dim_size(i);
int num_value_elements = data.shape().num_elements() / num_batch_elements;

Since data is given by the values argument, num_batch_elements is 0.


We have patched the issue in GitHub commit da5ff2daf618591f64b2b62d9d9803951b945e9f.

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, as these are also affected.

For more information

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This vulnerability has been reported by Yakun Zhang and Ying Wang of Baidu X-Team.

Source: GitHub Advisory Database
Origin: Unspecified
Severity: Low
Classification: General
Published: over 2 years ago
Updated: 10 months ago

CVSS Score: 2.5
CVSS vector: CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L

Identifiers: GHSA-qg48-85hg-mqc5, CVE-2021-29554

Affected Packages

Versions: >= 2.4.0, < 2.4.2, >= 2.3.0, < 2.3.3
Fixed in: 2.4.2, 2.3.3
Versions: >= 2.4.0, < 2.4.2, >= 2.3.0, < 2.3.3
Fixed in: 2.4.2, 2.3.3
Versions: >= 2.4.0, < 2.4.2, >= 2.3.0, < 2.3.3
Fixed in: 2.4.2, 2.3.3