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GHSA-g4h2-gqm3-c9wq

Segfault in tf.raw_ops.ImmutableConst

Source: GitHub Advisory Database (reviewed) Low CVE-2021-29539

Packages

EcosystemPackageAffectedFixed in
PyPI tensorflow < 2.1.4 2.1.4
PyPI tensorflow >= 2.2.0, < 2.2.3 2.2.3
PyPI tensorflow >= 2.3.0, < 2.3.3 2.3.3
PyPI tensorflow >= 2.4.0, < 2.4.2 2.4.2
PyPI tensorflow-cpu < 2.1.4 2.1.4
PyPI tensorflow-cpu >= 2.2.0, < 2.2.3 2.2.3
PyPI tensorflow-cpu >= 2.3.0, < 2.3.3 2.3.3
PyPI tensorflow-cpu >= 2.4.0, < 2.4.2 2.4.2
PyPI tensorflow-gpu < 2.1.4 2.1.4
PyPI tensorflow-gpu >= 2.2.0, < 2.2.3 2.2.3
PyPI tensorflow-gpu >= 2.3.0, < 2.3.3 2.3.3
PyPI tensorflow-gpu >= 2.4.0, < 2.4.2 2.4.2

Details

As written in the advisory (Markdown source, shown as plain text).

### Impact Calling [`tf.raw_ops.ImmutableConst`](https://www.tensorflow.org/api_docs/python/tf/raw_ops/ImmutableConst) with a `dtype` of `tf.resource` or `tf.variant` results in a segfault in the implementation as code assumes that the tensor contents are pure scalars. ```python >>> import tensorflow as tf >>> tf.raw_ops.ImmutableConst(dtype=tf.resource, shape=[], memory_region_name="/tmp/test.txt") ... Segmentation fault ``` ### Patches We have patched the issue in 4f663d4b8f0bec1b48da6fa091a7d29609980fa4 and will release TensorFlow 2.5.0 containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved. ### Workarounds If using `tf.raw_ops.ImmutableConst` in code, you can prevent the segfault by inserting a filter for the `dtype` argument. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.

References

External links from the advisory. They lead to third-party sites.