Memory exhaustion in Tensorflow

Open Source Vulnerabilities CVE-2022-21733

Tensorflow is an Open Source Machine Learning Framework. The implementation of `StringNGrams` can be used to trigger a denial of service attack by causing an out of memory condition after an integer overflow. We are missing a validation on `pad_witdh` and that result in computing a negative value for `ngram_width` which is later used to allocate parts of the output. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Open Source Vulnerabilities BIT-tensorflow-2022-21733

Tensorflow is an Open Source Machine Learning Framework. The implementation of `StringNGrams` can be used to trigger a denial of service attack by causing an out of memory condition after an integer overflow. We are missing a validation on `pad_witdh` and that result in computing a negative value for `ngram_width` which is later used to allocate parts of the output. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Open Source Vulnerabilities PYSEC-2022-112

Tensorflow is an Open Source Machine Learning Framework. The implementation of `StringNGrams` can be used to trigger a denial of service attack by causing an out of memory condition after an integer overflow. We are missing a validation on `pad_witdh` and that result in computing a negative value for `ngram_width` which is later used to allocate parts of the output. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Open Source Vulnerabilities PYSEC-2022-57

Tensorflow is an Open Source Machine Learning Framework. The implementation of `StringNGrams` can be used to trigger a denial of service attack by causing an out of memory condition after an integer overflow. We are missing a validation on `pad_witdh` and that result in computing a negative value for `ngram_width` which is later used to allocate parts of the output. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Open Source Vulnerabilities GHSA-98j8-c9q4-r38g

### Impact The [implementation of `StringNGrams`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/string_ngrams_op.cc#L29-L161) can be used to trigger a denial of service attack by causing an OOM condition after an integer overflow: ```python import tensorflow as tf tf.raw_ops.StringNGrams( data=['123456'], data_splits=[0,1], separator='a'*15, ngram_widths=[], left_pad='', right_pad='', pad_width=-5, preserve_short_sequences=True) ``` We are missing a validation on `pad_witdh` and that result in computing a negative value for `ngram_width` which is later used to allocate parts of the output. ### Patches We have patched the issue in GitHub commit [f68fdab93fb7f4ddb4eb438c8fe052753c9413e8](https://github.com/tensorflow/tensorflow/commit/f68fdab93fb7f4ddb4eb438c8fe052753c9413e8). The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions. ### Attribution This vulnerability has been reported by Yu Tian of Qihoo 360 AIVul Team.

Open Source Vulnerabilities PYSEC-2026-3145

### Impact The [implementation of `StringNGrams`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/string_ngrams_op.cc#L29-L161) can be used to trigger a denial of service attack by causing an OOM condition after an integer overflow: ```python import tensorflow as tf tf.raw_ops.StringNGrams( data=['123456'], data_splits=[0,1], separator='a'*15, ngram_widths=[], left_pad='', right_pad='', pad_width=-5, preserve_short_sequences=True) ``` We are missing a validation on `pad_witdh` and that result in computing a negative value for `ngram_width` which is later used to allocate parts of the output. ### Patches We have patched the issue in GitHub commit [f68fdab93fb7f4ddb4eb438c8fe052753c9413e8](https://github.com/tensorflow/tensorflow/commit/f68fdab93fb7f4ddb4eb438c8fe052753c9413e8). The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions. ### Attribution This vulnerability has been reported by Yu Tian of Qihoo 360 AIVul Team.