| Package | Affected versions | Patched versions |
|---|---|---|
| tensorflow | ≥ 2.3.0, < 2.3.4≥ 2.4.0, < 2.4.3≥ 2.5.0, < 2.5.1< 2.3.4 | 2.3.42.4.32.5.1 |
| tensorflow-cpu | ≥ 2.3.0, < 2.3.4≥ 2.4.0, < 2.4.3≥ 2.5.0, < 2.5.1< 2.3.4 | 2.3.42.4.32.5.1 |
| tensorflow-gpu | ≥ 2.3.0, < 2.3.4≥ 2.4.0, < 2.4.3≥ 2.5.0, < 2.5.1< 2.3.4 | 2.3.42.4.32.5.1 |
| tensorflow | = 2.5.0= 2.6.0≥ 2.3.0, < 2.3.4≥ 2.4.0, < 2.4.3 | 2.3.42.4.3 |
The implementation for tf.raw_ops.ExperimentalDatasetToTFRecord and tf.raw_ops.DatasetToTFRecord can trigger heap buffer overflow and segmentation fault:
import tensorflow as tf
dataset = tf.data.Dataset.range(3)
dataset = tf.data.experimental.to_variant(dataset)
tf.raw_ops.ExperimentalDatasetToTFRecord(
input_dataset=dataset,
filename='/tmp/output',
compression_type='')
The implementation assumes that all records in the dataset are of string type. However, there is no check for that, and the example given above uses numeric types.
We have patched the issue in GitHub commit e0b6e58c328059829c3eb968136f17aa72b6c876.
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.
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
This vulnerability has been reported by members of the Aivul Team from Qihoo 360.
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