Описание
TensorFlow is an end-to-end open source platform for machine learning. In affected versions the shape inference code for tf.raw_ops.Dequantize has a vulnerability that could trigger a denial of service via a segfault if an attacker provides invalid arguments. The shape inference implementation uses axis to select between two different values for minmax_rank which is then used to retrieve tensor dimensions. However, code assumes that axis can be either -1 or a value greater than -1, with no validation for the other values. We have patched the issue in GitHub commit da857cfa0fde8f79ad0afdbc94e88b5d4bbec764. 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.
Ссылки
- Patch
- Vendor Advisory
- Patch
- Vendor Advisory
Уязвимые конфигурации
Одно из
EPSS
5.5 Medium
CVSS3
2.1 Low
CVSS2
Дефекты
Связанные уязвимости
TensorFlow is an end-to-end open source platform for machine learning. ...
Missing validation in shape inference for `Dequantize`
EPSS
5.5 Medium
CVSS3
2.1 Low
CVSS2