https://cve.radiocsirt.org Contains only the most 10 recent entries. http://www.rssboard.org/rss-specification python-feedgen en Wed, 07 Oct 2026 18:27:34 +0000 https://cve.radiocsirt.org/vuln/cve-2022-35973 <p><strong>Affected:</strong> tensorflow</p> <p>TensorFlow is an open source platform for machine learning. If `QuantizedMatMul` is given nonscalar input for: `min_a`, `max_a`, `min_b`, or `max_b` It gives a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit aca766ac7693bf29ed0df55ad6bfcc78f35e7f48. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.</p> <p><strong>Affected:</strong> tensorflow</p> <p>TensorFlow is an open source platform for machine learning. If `QuantizedMatMul` is given nonscalar input for: `min_a`, `max_a`, `min_b`, or `max_b` It gives a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit aca766ac7693bf29ed0df55ad6bfcc78f35e7f48. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.</p> https://cve.radiocsirt.org/vuln/cve-2022-35973 https://cve.radiocsirt.org/vuln/ghsa-689c-r7h2-fv9v <p><strong>Affected:</strong> PyPI: tensorflow, PyPI: tensorflow-cpu, PyPI: tensorflow-gpu</p> <p>### Impact If `QuantizedMatMul` is given nonscalar input for: - `min_a` - `max_a` - `min_b` - `max_b` It gives a segfault that can be used to trigger a denial of service attack. ```python import tensorflow as tf</p> <p>Toutput = tf.qint32 transpose_a = False transpose_b = False Tactivation = tf.quint8 a = tf.constant(7, shape=[3,4], dtype=tf.quint8) b = tf.constant(1, shape=[2,3], dtype=tf.quint8) min_a = tf.constant([], shape=[0], dtype=tf.float32) max_a = tf.constant(0, shape=[1], dtype=tf.float32) min_b = tf.constant(0, shape=[1], dtype=tf.float32) max_b = tf.constant(0, shape=[1], dtype=tf.float32) tf.raw_ops.QuantizedMatMul(a=a, b=b, min_a=min_a, max_a=max_a, min_b=min_b, max_b=max_b, Toutput=Toutput, transpose_a=transpose_a, transpose_b=transpose_b, Tactivation=Tactivation) ```</p> <p>### Patches We have patched the issue in GitHub commit [aca766ac7693bf29ed0df55ad6bfcc78f35e7f48](https://github.com/tensorflow/tensorflow/commit/aca766ac7693bf29ed0df55ad6bfcc78f35e7f48).</p> <p>The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, 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 to contact us with issues and questions.</p> <p>### Attribution This vulnerability has been reported by Neophytos Christou, Secure S…</p> <p><strong>Affected:</strong> PyPI: tensorflow, PyPI: tensorflow-cpu, PyPI: tensorflow-gpu</p> <p>### Impact If `QuantizedMatMul` is given nonscalar input for: - `min_a` - `max_a` - `min_b` - `max_b` It gives a segfault that can be used to trigger a denial of service attack. ```python import tensorflow as tf</p> <p>Toutput = tf.qint32 transpose_a = False transpose_b = False Tactivation = tf.quint8 a = tf.constant(7, shape=[3,4], dtype=tf.quint8) b = tf.constant(1, shape=[2,3], dtype=tf.quint8) min_a = tf.constant([], shape=[0], dtype=tf.float32) max_a = tf.constant(0, shape=[1], dtype=tf.float32) min_b = tf.constant(0, shape=[1], dtype=tf.float32) max_b = tf.constant(0, shape=[1], dtype=tf.float32) tf.raw_ops.QuantizedMatMul(a=a, b=b, min_a=min_a, max_a=max_a, min_b=min_b, max_b=max_b, Toutput=Toutput, transpose_a=transpose_a, transpose_b=transpose_b, Tactivation=Tactivation) ```</p> <p>### Patches We have patched the issue in GitHub commit [aca766ac7693bf29ed0df55ad6bfcc78f35e7f48](https://github.com/tensorflow/tensorflow/commit/aca766ac7693bf29ed0df55ad6bfcc78f35e7f48).</p> <p>The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, 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 to contact us with issues and questions.</p> <p>### Attribution This vulnerability has been reported by Neophytos Christou, Secure S…</p> https://cve.radiocsirt.org/vuln/ghsa-689c-r7h2-fv9v