TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.QuantizeAndDequantizeV4Grad` is vulnerable to an integer overflow issue caused by converting a signed integer value to an unsigned one and then allocating memory based on this value. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L126) uses the `axis` value as the size argument to `absl::InlinedVector` constructor. But, the constructor uses an unsigned type for the argument, so the implicit conversion transforms the negative value to a large integer. We have patched the issue in GitHub commit 96f364a1ca3009f98980021c4b32be5fdcca33a1. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, and TensorFlow 2.4.3, as these are also affected and still in supported range.

There are packages installed that are affected by a vulnerability referenced in the following CVE:

  - TensorFlow is an end-to-end open source platform for machine learning. In affected versions the
    implementation of `tf.raw_ops.QuantizeAndDequantizeV4Grad` is vulnerable to an integer overflow issue
    caused by converting a signed integer value to an unsigned one and then allocating memory based on this
    value. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14
    f5f49698/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L126) uses the `axis` value as the size
    argument to `absl::InlinedVector` constructor. But, the constructor uses an unsigned type for the
    argument, so the implicit conversion transforms the negative value to a large integer. We have patched the
    issue in GitHub commit 96f364a1ca3009f98980021c4b32be5fdcca33a1. The fix will be included in TensorFlow
    2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, and TensorFlow 2.4.3, as these are also
    affected and still in supported range. (CVE-2021-37645)

The remote openSUSE 15 host has packages installed that are affected by multiple vulnerabilities as referenced in the openSUSE-SU-2022:10014-1 advisory.

    Update to TF2 2.6.0 which fixes multiple CVEs (boo#1189423).

    - Introduction of bazel6.3 and basel-skylib1.0.3 as build       dependencies.
      The latter has been adapted to all a version in its package       name (if %set_ver_suffix is set to 1). This allows multiple       versions to exist for one product (not installed).
      NOTE: basel-skylib1.0.3 does not exist in oS:Factory:
      basel-skylib in oS:Factory - the base version - is 1.0.3.

Tenable has extracted the preceding description block directly from the SUSE security advisory.

Note that Nessus has not tested for these issues but has instead relied only on the application's self-reported version number.

ID	Name	Product	Family	Type	Severity
413489	SCA: security update for tensorflow, tensorflow-cpu, tensorflow-gpu (GHSA-9w2p-5mgw-p94c)	Tenable Cloud Security	SCA Checks	Local	medium
413489	SCA: security update for tensorflow, tensorflow-cpu, tensorflow-gpu (GHSA-9w2p-5mgw-p94c)	Tenable Self-Hosted Container Security	SCA Checks	Local	medium
162400	openSUSE 15 Security Update : tensorflow2 (openSUSE-SU-2022:10014-1)	Nessus	SuSE Local Security Checks	Local	high

Detections

Analytics

CVE-2021-37645

medium

Tenable Plugins

medium

medium

high