https://cve.radiocsirt.org Contains only the most 10 recent entries. http://www.rssboard.org/rss-specification python-feedgen en Fri, 23 Oct 2026 23:48:19 +0000 https://cve.radiocsirt.org/vuln/cve-2022-29211 <p><strong>Affected:</strong> tensorflow</p> <p>TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.histogram_fixed_width` is vulnerable to a crash when the values array contain `Not a Number` (`NaN`) elements. The implementation assumes that all floating point operations are defined and then converts a floating point result to an integer index. If `values` contains `NaN` then the result of the division is still `NaN` and the cast to `int32` would result in a crash. This only occurs on the CPU implementation. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.</p> <p><strong>Affected:</strong> tensorflow</p> <p>TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.histogram_fixed_width` is vulnerable to a crash when the values array contain `Not a Number` (`NaN`) elements. The implementation assumes that all floating point operations are defined and then converts a floating point result to an integer index. If `values` contains `NaN` then the result of the division is still `NaN` and the cast to `int32` would result in a crash. This only occurs on the CPU implementation. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.</p> https://cve.radiocsirt.org/vuln/cve-2022-29211 https://cve.radiocsirt.org/vuln/ghsa-xrp2-fhq4-4q3w <p><strong>Affected:</strong> PyPI: tensorflow, PyPI: tensorflow-cpu, PyPI: tensorflow-gpu</p> <p>### Impact The implementation of [`tf.histogram_fixed_width`](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/histogram_op.cc) is vulnerable to a crash when the values array contain `NaN` elements:</p> <p>```python import tensorflow as tf import numpy as np</p> <p>tf.histogram_fixed_width(values=np.nan, value_range=[1,2]) ```</p> <p>The [implementation](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/histogram_op.cc#L35-L74) assumes that all floating point operations are defined and then converts a floating point result to an integer index:</p> <p>```cc index_to_bin.device(d) = ((values.cwiseMax(value_range(0)) - values.constant(value_range(0))) .template cast&lt;double&gt;() / step) .cwiseMin(nbins_minus_1) .template cast&lt;int32&gt;(); ```</p> <p>If `values` contains `NaN` then the result of the division is still `NaN` and the cast to `int32` would result in a crash.</p> <p>This only occurs on the CPU implementation.</p> <p>### Patches We have patched the issue in GitHub commit [e57fd691c7b0fd00ea3bfe43444f30c1969748b5](https://github.com/tensorflow/tensorflow/commit/e57fd691c7b0fd00ea3bfe43444f30c1969748b5).</p> <p>The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, as these are also affected and still in supported range.</p> <p>### For more information Please consult [our security guide](…</p> <p><strong>Affected:</strong> PyPI: tensorflow, PyPI: tensorflow-cpu, PyPI: tensorflow-gpu</p> <p>### Impact The implementation of [`tf.histogram_fixed_width`](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/histogram_op.cc) is vulnerable to a crash when the values array contain `NaN` elements:</p> <p>```python import tensorflow as tf import numpy as np</p> <p>tf.histogram_fixed_width(values=np.nan, value_range=[1,2]) ```</p> <p>The [implementation](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/histogram_op.cc#L35-L74) assumes that all floating point operations are defined and then converts a floating point result to an integer index:</p> <p>```cc index_to_bin.device(d) = ((values.cwiseMax(value_range(0)) - values.constant(value_range(0))) .template cast&lt;double&gt;() / step) .cwiseMin(nbins_minus_1) .template cast&lt;int32&gt;(); ```</p> <p>If `values` contains `NaN` then the result of the division is still `NaN` and the cast to `int32` would result in a crash.</p> <p>This only occurs on the CPU implementation.</p> <p>### Patches We have patched the issue in GitHub commit [e57fd691c7b0fd00ea3bfe43444f30c1969748b5](https://github.com/tensorflow/tensorflow/commit/e57fd691c7b0fd00ea3bfe43444f30c1969748b5).</p> <p>The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, as these are also affected and still in supported range.</p> <p>### For more information Please consult [our security guide](…</p> https://cve.radiocsirt.org/vuln/ghsa-xrp2-fhq4-4q3w