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  <updated>2026-10-06T14:14:50.817972+00:00</updated>
  <author>
    <name>Vulnerability-Lookup</name>
    <email>csirt@opendfir.org</email>
  </author>
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  <entry>
    <id>https://cve.radiocsirt.org/vuln/cve-2021-37646</id>
    <title>CVE-2021-37646 — Bad alloc in `StringNGrams` caused by integer conversion in TensorFlow</title>
    <updated>2026-10-06T14:14:50.820483+00:00</updated>
    <content type="xhtml">
      <div xmlns="http://www.w3.org/1999/xhtml"><p><strong>Affected:</strong> tensorflow</p>
<p>TensorFlow is an end-to-end open source platform for machine learning. In affected versions 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. 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. We have patched the issue in GitHub 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.</p></div>
    </content>
    <link href="https://cve.radiocsirt.org/vuln/cve-2021-37646"/>
  </entry>
  <entry>
    <id>https://cve.radiocsirt.org/vuln/ghsa-h6jh-7gv5-28vg</id>
    <title>GHSA-h6jh-7gv5-28vg — Bad alloc in `StringNGrams` caused by integer conversion</title>
    <updated>2026-10-06T14:14:50.820545+00:00</updated>
    <content type="xhtml">
      <div xmlns="http://www.w3.org/1999/xhtml"><p><strong>Affected:</strong> PyPI: tensorflow, PyPI: tensorflow-cpu, PyPI: tensorflow-gpu</p>
<p>### 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.</p>
<p>```python
import tensorflow as tf</p>
<p>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)
```</p>
<p>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.</p>
<p>### Patches
We have patched the issue in GitHub commit [c283e542a3f422420cfdb332414543b62fc4e4a5](https://github.com/tensorflow/tensorflow/commit/c283e542a3f422420cfdb332414543b62fc4e4a5).</p>
<p>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.</p>
<p>### 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 t…</p></div>
    </content>
    <link href="https://cve.radiocsirt.org/vuln/ghsa-h6jh-7gv5-28vg"/>
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