https://cve.radiocsirt.org Contains only the most 10 recent entries. http://www.rssboard.org/rss-specification python-feedgen en Fri, 09 Oct 2026 13:23:47 +0000 https://cve.radiocsirt.org/vuln/cve-2021-29546 <p><strong>Affected:</strong> tensorflow</p> <p>TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger an integer division by zero undefined behavior in `tf.raw_ops.QuantizedBiasAdd`. This is because the implementation of the Eigen kernel(https://github.com/tensorflow/tensorflow/blob/61bca8bd5ba8a68b2d97435ddfafcdf2b85672cd/tensorflow/core/kernels/quantization_utils.h#L812-L849) does a division by the number of elements of the smaller input (based on shape) without checking that this is not zero. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.</p> <p><strong>Affected:</strong> tensorflow</p> <p>TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger an integer division by zero undefined behavior in `tf.raw_ops.QuantizedBiasAdd`. This is because the implementation of the Eigen kernel(https://github.com/tensorflow/tensorflow/blob/61bca8bd5ba8a68b2d97435ddfafcdf2b85672cd/tensorflow/core/kernels/quantization_utils.h#L812-L849) does a division by the number of elements of the smaller input (based on shape) without checking that this is not zero. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.</p> https://cve.radiocsirt.org/vuln/cve-2021-29546 https://cve.radiocsirt.org/vuln/ghsa-m34j-p8rj-wjxq <p><strong>Affected:</strong> PyPI: tensorflow, PyPI: tensorflow-cpu, PyPI: tensorflow-gpu</p> <p>### Impact An attacker can trigger an integer division by zero undefined behavior in `tf.raw_ops.QuantizedBiasAdd`:</p> <p>```python import tensorflow as tf</p> <p>input_tensor = tf.constant([], shape=[0, 0, 0, 0], dtype=tf.quint8) bias = tf.constant([], shape=[0], dtype=tf.quint8) min_input = tf.constant(-10.0, dtype=tf.float32) max_input = tf.constant(-10.0, dtype=tf.float32) min_bias = tf.constant(-10.0, dtype=tf.float32) max_bias = tf.constant(-10.0, dtype=tf.float32)</p> <p>tf.raw_ops.QuantizedBiasAdd(input=input_tensor, bias=bias, min_input=min_input, max_input=max_input, min_bias=min_bias, max_bias=max_bias, out_type=tf.qint32) ```</p> <p>This is because the [implementation of the Eigen kernel](https://github.com/tensorflow/tensorflow/blob/61bca8bd5ba8a68b2d97435ddfafcdf2b85672cd/tensorflow/core/kernels/quantization_utils.h#L812-L849) does a division by the number of elements of the smaller input (based on shape) without checking that this is not zero:</p> <p>```cc template &lt;typename T1, typename T2, typename T3&gt; void QuantizedAddUsingEigen(const Eigen::ThreadPoolDevice&amp; device, const Tensor&amp; input, float input_min, float input_max, const Tensor&amp; smaller_input, float smaller_input_min, float smaller_input_max, Tensor* output, float* output_min, float* output_max) { ... const int64 input_element_count…</p> <p><strong>Affected:</strong> PyPI: tensorflow, PyPI: tensorflow-cpu, PyPI: tensorflow-gpu</p> <p>### Impact An attacker can trigger an integer division by zero undefined behavior in `tf.raw_ops.QuantizedBiasAdd`:</p> <p>```python import tensorflow as tf</p> <p>input_tensor = tf.constant([], shape=[0, 0, 0, 0], dtype=tf.quint8) bias = tf.constant([], shape=[0], dtype=tf.quint8) min_input = tf.constant(-10.0, dtype=tf.float32) max_input = tf.constant(-10.0, dtype=tf.float32) min_bias = tf.constant(-10.0, dtype=tf.float32) max_bias = tf.constant(-10.0, dtype=tf.float32)</p> <p>tf.raw_ops.QuantizedBiasAdd(input=input_tensor, bias=bias, min_input=min_input, max_input=max_input, min_bias=min_bias, max_bias=max_bias, out_type=tf.qint32) ```</p> <p>This is because the [implementation of the Eigen kernel](https://github.com/tensorflow/tensorflow/blob/61bca8bd5ba8a68b2d97435ddfafcdf2b85672cd/tensorflow/core/kernels/quantization_utils.h#L812-L849) does a division by the number of elements of the smaller input (based on shape) without checking that this is not zero:</p> <p>```cc template &lt;typename T1, typename T2, typename T3&gt; void QuantizedAddUsingEigen(const Eigen::ThreadPoolDevice&amp; device, const Tensor&amp; input, float input_min, float input_max, const Tensor&amp; smaller_input, float smaller_input_min, float smaller_input_max, Tensor* output, float* output_min, float* output_max) { ... const int64 input_element_count…</p> https://cve.radiocsirt.org/vuln/ghsa-m34j-p8rj-wjxq