Advisoriesby IbisBad alloc in `StringNGrams` caused by integer conversion
Impact
The implementation of tf.raw_ops.StringNGrams is vulnerable to an integer overflow issue caused by converting a signed integer value to an unsigned one and then allocating memory based on this value.
```python
import tensorflow as tf
tf.raw_ops.StringNGrams(
data=['',''],
data_splits=[0,2],
separator=' '*100,
ngram_widths=[-80,0,0,-60],
left_pad=' ',
right_pad=' ',
pad_width=100,
preserve_short_sequences=False)
`
The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/string_ngrams_op.cc#L184) calls reserve on a tstring with a value that sometimes can be negative if user supplies negative ngram_widths. The reserve method calls TF_TString_Reserve which has an unsigned long argument for the size of the buffer. Hence, the implicit conversion transforms the negative value to a large integer.
Patches
We have patched the issue in GitHub commit [c283e542a3f422420cfdb332414543b62fc4e4a5](https://github.com/tensorflow/tensorflow/commit/c283e542a3f422420cfdb332414543b62fc4e4a5).
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.
For more information
Please consult [our security...
Affected versions
| Package | Affected | Fixed in |
|---|---|---|
| tensorflow PyPI | < 2.3.4 | 2.3.4 |
| >= 2.4.0, < 2.4.3 | 2.4.3 | |
| >= 2.5.0, < 2.5.1 | 2.5.1 |
Details and references
### Impact The implementation of `tf.raw_ops.StringNGrams` is vulnerable to an integer overflow issue caused by converting a signed integer value to an unsigned one and then allocating memory based on this value. ```python import tensorflow as tf tf.raw_ops.StringNGrams( data=['',''], data_splits=[0,2], separator=' '*100, ngram_widths=[-80,0,0,-60], left_pad=' ', right_pad=' ', pad_width=100, preserve_short_sequences=False) ``` The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/string_ngrams_op.cc#L184) calls `reserve` on a `tstring` with a value that sometimes can be negative if user supplies negative `ngram_widths`. The `reserve` method calls `TF_TString_Reserve` which has an `unsigned long` argument for the size of the buffer. Hence, the implicit conversion transforms the negative value to a large integer. ### Patches We have patched the issue in GitHub commit [c283e542a3f422420cfdb332414543b62fc4e4a5](https://github.com/tensorflow/tensorflow/commit/c283e542a3f422420cfdb332414543b62fc4e4a5). 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. ### 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 members of the Aivul Team from Qihoo 360.
- CVSS 3.1
- CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
- Severity from
- GitHub (reviewed advisory)
- Weakness
- CWE-681
- Also known as
- BIT-tensorflow-2021-37646, CVE-2021-37646, PYSEC-2021-268, PYSEC-2021-559, PYSEC-2021-757
- github.com/tensorflow/tensorflow/security/advisories/GHSA-h6jh-7gv5-28vg
- nvd.nist.gov/vuln/detail/CVE-2021-37646
- github.com/tensorflow/tensorflow/commit/c283e542a3f422420cfdb332414543b62fc4e4a5
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-559.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-757.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-268.yaml
- github.com/tensorflow/tensorflow
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