Описание
TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a segfault and denial of service via accessing data outside of bounds in tf.raw_ops.QuantizedBatchNormWithGlobalNormalization. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/55a97caa9e99c7f37a0bbbeb414dc55553d3ae7f/tensorflow/core/kernels/quantized_batch_norm_op.cc#L176-L189) assumes the inputs are not empty. If any of these inputs is empty, .flat<T>() is an empty buffer, so accessing the element at index 0 is accessing data outside of bounds. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
Ссылки
- PatchThird Party Advisory
- ExploitPatchThird Party Advisory
- PatchThird Party Advisory
- ExploitPatchThird Party Advisory
Уязвимые конфигурации
Одно из
EPSS
2.5 Low
CVSS3
5.5 Medium
CVSS3
2.1 Low
CVSS2
Дефекты
Связанные уязвимости
TensorFlow is an end-to-end open source platform for machine learning. ...
Heap out of bounds in `QuantizedBatchNormWithGlobalNormalization`
EPSS
2.5 Low
CVSS3
5.5 Medium
CVSS3
2.1 Low
CVSS2