Type confusion leading to segfault in Tensorflow
Résumé
Type confusion leading to segfault in Tensorflow
Description d'origine
La description telle que publiée par la source (souvent en anglais).
Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for ConcatV2 can be used to trigger a denial of service attack via a segfault caused by a type confusion. The axis argument is translated into concat_dim in the ConcatShapeHelper helper function. Then, a value for min_rank is computed based on concat_dim. This is then used to validate that the values tensor has at least the required rank. However, WithRankAtLeast receives the lower bound as a 64-bits value and then compares it against the maximum 32-bits integer value that could be represented. Due to the fact that min_rank is a 32-bits value and the value of axis, the rank argument is a negative value, so the error check is bypassed. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Source: OSV.dev (Open Source Vulnerabilities) NVD GitHub Advisory OSV
Paquets affectés
Références
- advisory github.com
- advisory nvd.nist.gov
- advisory github.com
- patch github.com
- web github.com
- web github.com
- web github.com
- web github.com
- web github.com