PYSEC-2020-116

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Import Source
https://github.com/pypa/advisory-database/blob/main/vulns/tensorflow/PYSEC-2020-116.yaml
JSON Data
https://api.osv.dev/v1/vulns/PYSEC-2020-116
Aliases
Published
2020-09-25T19:15:00Z
Modified
2023-12-06T01:00:16.213136Z
Summary
[none]
Details

In Tensorflow before versions 2.2.1 and 2.3.1, the implementation of dlpack.to_dlpack can be made to use uninitialized memory resulting in further memory corruption. This is because the pybind11 glue code assumes that the argument is a tensor. However, there is nothing stopping users from passing in a Python object instead of a tensor. The uninitialized memory address is due to a reinterpret_cast Since the PyObject is a Python object, not a TensorFlow Tensor, the cast to EagerTensor fails. The issue is patched in commit 22e07fb204386768e5bcbea563641ea11f96ceb8 and is released in TensorFlow versions 2.2.1, or 2.3.1.

References

Affected packages

PyPI / tensorflow

Package

Affected ranges

Type
GIT
Repo
https://github.com/tensorflow/tensorflow
Events
Introduced
0 Unknown introduced commit / All previous commits are affected
Fixed
Type
ECOSYSTEM
Events
Introduced
0Unknown introduced version / All previous versions are affected
Fixed
2.2.1
Introduced
2.3.0rc0
Fixed
2.3.1

Affected versions

0.*

0.12.0rc0
0.12.0rc1
0.12.0
0.12.1

1.*

1.0.0
1.0.1
1.1.0rc0
1.1.0rc1
1.1.0rc2
1.1.0
1.2.0rc0
1.2.0rc1
1.2.0rc2
1.2.0
1.2.1
1.3.0rc0
1.3.0rc1
1.3.0rc2
1.3.0
1.4.0rc0
1.4.0rc1
1.4.0
1.4.1
1.5.0rc0
1.5.0rc1
1.5.0
1.5.1
1.6.0rc0
1.6.0rc1
1.6.0
1.7.0rc0
1.7.0rc1
1.7.0
1.7.1
1.8.0rc0
1.8.0rc1
1.8.0
1.9.0rc0
1.9.0rc1
1.9.0rc2
1.9.0
1.10.0rc0
1.10.0rc1
1.10.0
1.10.1
1.11.0rc0
1.11.0rc1
1.11.0rc2
1.11.0
1.12.0rc0
1.12.0rc1
1.12.0rc2
1.12.0
1.12.2
1.12.3
1.13.0rc0
1.13.0rc1
1.13.0rc2
1.13.1
1.13.2
1.14.0rc0
1.14.0rc1
1.14.0
1.15.0rc0
1.15.0rc1
1.15.0rc2
1.15.0rc3
1.15.0
1.15.2
1.15.3
1.15.4
1.15.5

2.*

2.0.0a0
2.0.0b0
2.0.0b1
2.0.0rc0
2.0.0rc1
2.0.0rc2
2.0.0
2.0.1
2.0.2
2.0.3
2.0.4
2.1.0rc0
2.1.0rc1
2.1.0rc2
2.1.0
2.1.1
2.1.2
2.1.3
2.1.4
2.2.0rc0
2.2.0rc1
2.2.0rc2
2.2.0rc3
2.2.0rc4
2.2.0
2.3.0rc0
2.3.0rc1
2.3.0rc2
2.3.0