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    <item>
      <title>CVE-2022-21727 — Integer overflow in Tensorflow</title>
      <link>https://vulnerability.circl.lu/vuln/cve-2022-21727</link>
      <description>&lt;p&gt;Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `Dequantize` is vulnerable to an integer overflow weakness. The `axis` argument can be `-1` (the default value for the optional argument) or any other positive value at most the number of dimensions of the input. Unfortunately, the upper bound is not checked, and, since the code computes `axis + 1`, an attacker can trigger an integer overflow. 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.&lt;/p&gt;</description>
      <content:encoded>&lt;p&gt;Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `Dequantize` is vulnerable to an integer overflow weakness. The `axis` argument can be `-1` (the default value for the optional argument) or any other positive value at most the number of dimensions of the input. Unfortunately, the upper bound is not checked, and, since the code computes `axis + 1`, an attacker can trigger an integer overflow. 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.&lt;/p&gt;</content:encoded>
      <guid isPermaLink="false">https://vulnerability.circl.lu/vuln/cve-2022-21727</guid>
    </item>
    <item>
      <title>GHSA-c6fh-56w7-fvjw — Integer overflow in Tensorflow</title>
      <link>https://vulnerability.circl.lu/vuln/ghsa-c6fh-56w7-fvjw</link>
      <description>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; PyPI: tensorflow, PyPI: tensorflow-cpu, PyPI: tensorflow-gpu&lt;/p&gt;
&lt;p&gt;### Impact 
The [implementation of shape inference for `Dequantize`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/ops/array_ops.cc#L3001-L3034) is vulnerable to an integer overflow weakness:&lt;/p&gt;
&lt;p&gt;```python
import tensorflow as tf&lt;/p&gt;
&lt;p&gt;input = tf.constant([1,1],dtype=tf.qint32)&lt;/p&gt;
&lt;p&gt;@tf.function
def test():
  y = tf.raw_ops.Dequantize(
    input=input,
    min_range=[1.0],
    max_range=[10.0],
    mode=&amp;#39;MIN_COMBINED&amp;#39;,
    narrow_range=False,
    axis=2**31-1,
    dtype=tf.bfloat16)
  return y&lt;/p&gt;
&lt;p&gt;test()
```&lt;/p&gt;
&lt;p&gt;The `axis` argument can be `-1` (the default value for the optional argument) or any other positive value at most the number of dimensions of the input. Unfortunately, the upper bound is not checked, and, since the code computes `axis + 1`, an attacker can trigger an integer overflow:&lt;/p&gt;
&lt;p&gt;```cc
  int axis = -1; 
  Status s = c-&amp;gt;GetAttr(&amp;#34;axis&amp;#34;, &amp;amp;axis);
  // ...
  if (axis &amp;lt; -1) {
    return errors::InvalidArgument(&amp;#34;axis should be at least -1, got &amp;#34;,
                                   axis);
  }
  // ...
  if (axis != -1) {
    ShapeHandle input;
    TF_RETURN_IF_ERROR(c-&amp;gt;WithRankAtLeast(c-&amp;gt;input(0), axis + 1, &amp;amp;input));
    // ...
  }
```
  
### Patches
We have patched the issue in GitHub commit [b64638ec5ccaa77b7c1eb90958e3d85ce381f91b](https://github.com/tensorflow/tensorflow/commit/b64638ec5ccaa77b7c1eb90958e3d85ce381f91b).&lt;/p&gt;
&lt;p&gt;The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, Ten…&lt;/p&gt;</description>
      <content:encoded>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; PyPI: tensorflow, PyPI: tensorflow-cpu, PyPI: tensorflow-gpu&lt;/p&gt;
&lt;p&gt;### Impact 
The [implementation of shape inference for `Dequantize`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/ops/array_ops.cc#L3001-L3034) is vulnerable to an integer overflow weakness:&lt;/p&gt;
&lt;p&gt;```python
import tensorflow as tf&lt;/p&gt;
&lt;p&gt;input = tf.constant([1,1],dtype=tf.qint32)&lt;/p&gt;
&lt;p&gt;@tf.function
def test():
  y = tf.raw_ops.Dequantize(
    input=input,
    min_range=[1.0],
    max_range=[10.0],
    mode=&amp;#39;MIN_COMBINED&amp;#39;,
    narrow_range=False,
    axis=2**31-1,
    dtype=tf.bfloat16)
  return y&lt;/p&gt;
&lt;p&gt;test()
```&lt;/p&gt;
&lt;p&gt;The `axis` argument can be `-1` (the default value for the optional argument) or any other positive value at most the number of dimensions of the input. Unfortunately, the upper bound is not checked, and, since the code computes `axis + 1`, an attacker can trigger an integer overflow:&lt;/p&gt;
&lt;p&gt;```cc
  int axis = -1; 
  Status s = c-&amp;gt;GetAttr(&amp;#34;axis&amp;#34;, &amp;amp;axis);
  // ...
  if (axis &amp;lt; -1) {
    return errors::InvalidArgument(&amp;#34;axis should be at least -1, got &amp;#34;,
                                   axis);
  }
  // ...
  if (axis != -1) {
    ShapeHandle input;
    TF_RETURN_IF_ERROR(c-&amp;gt;WithRankAtLeast(c-&amp;gt;input(0), axis + 1, &amp;amp;input));
    // ...
  }
```
  
### Patches
We have patched the issue in GitHub commit [b64638ec5ccaa77b7c1eb90958e3d85ce381f91b](https://github.com/tensorflow/tensorflow/commit/b64638ec5ccaa77b7c1eb90958e3d85ce381f91b).&lt;/p&gt;
&lt;p&gt;The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, Ten…&lt;/p&gt;</content:encoded>
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