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GHSA-xmq7-7fxm-rr79

Denial of Service in Tensorflow

Source: GitHub Advisory Database (reviewed) High CVE-2020-15203

Packages

EcosystemPackageAffectedFixed in
PyPI tensorflow < 1.15.4 1.15.4
PyPI tensorflow >= 2.0.0, < 2.0.3 2.0.3
PyPI tensorflow >= 2.1.0, < 2.1.2 2.1.2
PyPI tensorflow >= 2.2.0, < 2.2.1 2.2.1
PyPI tensorflow >= 2.3.0, < 2.3.1 2.3.1
PyPI tensorflow-cpu < 1.15.4 1.15.4
PyPI tensorflow-cpu >= 2.0.0, < 2.0.3 2.0.3
PyPI tensorflow-cpu >= 2.1.0, < 2.1.2 2.1.2
PyPI tensorflow-cpu >= 2.2.0, < 2.2.1 2.2.1
PyPI tensorflow-cpu >= 2.3.0, < 2.3.1 2.3.1
PyPI tensorflow-gpu < 1.15.4 1.15.4
PyPI tensorflow-gpu >= 2.0.0, < 2.0.3 2.0.3
PyPI tensorflow-gpu >= 2.1.0, < 2.1.2 2.1.2
PyPI tensorflow-gpu >= 2.2.0, < 2.2.1 2.2.1
PyPI tensorflow-gpu >= 2.3.0, < 2.3.1 2.3.1

Details

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

### Impact By controlling the `fill` argument of [`tf.strings.as_string`](https://www.tensorflow.org/api_docs/python/tf/strings/as_string), a malicious attacker is able to trigger a format string vulnerability due to the way the internal format use in a `printf` call is constructed: https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/as_string_op.cc#L68-L74 This can result in unexpected output: ```python In [1]: tf.strings.as_string(input=[1234], width=6, fill='-') Out[1]: <tf.Tensor: shape=(1,), dtype=string, numpy=array(['1234 '], dtype=object)> In [2]: tf.strings.as_string(input=[1234], width=6, fill='+') Out[2]: <tf.Tensor: shape=(1,), dtype=string, numpy=array([' +1234'], dtype=object)> In [3]: tf.strings.as_string(input=[1234], width=6, fill="h") Out[3]: <tf.Tensor: shape=(1,), dtype=string, numpy=array(['%6d'], dtype=object)> In [4]: tf.strings.as_string(input=[1234], width=6, fill="d") Out[4]: <tf.Tensor: shape=(1,), dtype=string, numpy=array(['12346d'], dtype=object)> In [5]: tf.strings.as_string(input=[1234], width=6, fill="o") Out[5]: <tf.Tensor: shape=(1,), dtype=string, numpy=array(['23226d'], dtype=object)> In [6]: tf.strings.as_string(input=[1234], width=6, fill="x") Out[6]: <tf.Tensor: shape=(1,), dtype=string, numpy=array(['4d26d'], dtype=object)> In [7]: tf.strings.as_string(input=[1234], width=6, fill="g") Out[7]: <tf.Tensor: shape=(1,), dtype=string, numpy=array(['8.67458e-3116d'], dtype=object)> In [8]: tf.strings.as_string(input=[1234], width=6, fill="a") Out[8]: <tf.Tensor: shape=(1,), dtype=string, numpy=array(['0x0.00ff7eebb4d4p-10226d'], dtype=object)> In [9]: tf.strings.as_string(input=[1234], width=6, fill="c") Out[9]: <tf.Tensor: shape=(1,), dtype=string, numpy=array(['\xd26d'], dtype=object)> In [10]: tf.strings.as_string(input=[1234], width=6, fill="p") Out[10]: <tf.Tensor: shape=(1,), dtype=string, numpy=array(['0x4d26d'], dtype=object)> In [11]: tf.strings.as_string(input=[1234], width=6, fill='m') Out[11]: <tf.Tensor: shape=(1,), dtype=string, numpy=array(['Success6d'], dtype=object)> ``` However, passing in `n` or `s` results in segmentation fault. ### Patches We have patched the issue in 33be22c65d86256e6826666662e40dbdfe70ee83 and will release patch releases for all versions between 1.15 and 2.3. We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1. ### 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. ### Attribution This vulnerability has been reported by members of the Aivul Team from Qihoo 360.

References

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