TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can trigger a read from outside of bounds of heap allocated data by sending invalid arguments to `tf.raw_ops.ResourceScatterUpdate`. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/resource_variable_ops.cc#L919-L923) has an incomplete validation of the relationship between the shapes of `indices` and `updates`: instead of checking that the shape of `indices` is a prefix of the shape of `updates` (so that broadcasting can happen), code only checks that the number of elements in these two tensors are in a divisibility relationship. We have patched the issue in GitHub commit 01cff3f986259d661103412a20745928c727326f. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, 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 an attacker
    can trigger a read from outside of bounds of heap allocated data by sending invalid arguments to
    `tf.raw_ops.ResourceScatterUpdate`. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24
    faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/resource_variable_ops.cc#L919-L923) has an
    incomplete validation of the relationship between the shapes of `indices` and `updates`: instead of
    checking that the shape of `indices` is a prefix of the shape of `updates` (so that broadcasting can
    happen), code only checks that the number of elements in these two tensors are in a divisibility
    relationship. We have patched the issue in GitHub commit 01cff3f986259d661103412a20745928c727326f. The fix
    will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow
    2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. (CVE-2021-37655)

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
412039	SCA: security update for tensorflow, tensorflow-cpu, tensorflow-gpu (GHSA-7fvx-3jfc-2cpc)	Tenable Cloud Security	SCA Checks	Local	high
412039	SCA: security update for tensorflow, tensorflow-cpu, tensorflow-gpu (GHSA-7fvx-3jfc-2cpc)	Tenable Self-Hosted Container Security	SCA Checks	Local	high
162400	openSUSE 15 Security Update : tensorflow2 (openSUSE-SU-2022:10014-1)	Nessus	SuSE Local Security Checks	Local	high

Detections

Analytics

CVE-2021-37655

high

Tenable Plugins

high

high

high