CVE-2022-35972 – Segfault in `QuantizedBiasAdd` in TensorFlow
https://notcve.org/view.php?id=CVE-2022-35972
TensorFlow is an open source platform for machine learning. If `QuantizedBiasAdd` is given `min_input`, `max_input`, `min_bias`, `max_bias` tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 785d67a78a1d533759fcd2f5e8d6ef778de849e0. 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. • https://github.com/tensorflow/tensorflow/commit/785d67a78a1d533759fcd2f5e8d6ef778de849e0 https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4pc4-m9mj-v2r9 • CWE-20: Improper Input Validation •
CVE-2022-35973 – Segfault in `QuantizedMatMul` in TensorFlow
https://notcve.org/view.php?id=CVE-2022-35973
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. • https://github.com/tensorflow/tensorflow/commit/aca766ac7693bf29ed0df55ad6bfcc78f35e7f48 https://github.com/tensorflow/tensorflow/security/advisories/GHSA-689c-r7h2-fv9v • CWE-20: Improper Input Validation •
CVE-2022-35971 – `CHECK` fail in `FakeQuantWithMinMaxVars` in TensorFlow
https://notcve.org/view.php?id=CVE-2022-35971
TensorFlow is an open source platform for machine learning. If `FakeQuantWithMinMaxVars` is given `min` or `max` tensors of a nonzero rank, it results in a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 785d67a78a1d533759fcd2f5e8d6ef778de849e0. 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. • https://github.com/tensorflow/tensorflow/commit/785d67a78a1d533759fcd2f5e8d6ef778de849e0 https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9fpg-838v-wpv7 • CWE-617: Reachable Assertion •
CVE-2022-35969 – `CHECK` fail in `Conv2DBackpropInput` in TensorFlow
https://notcve.org/view.php?id=CVE-2022-35969
TensorFlow is an open source platform for machine learning. The implementation of `Conv2DBackpropInput` requires `input_sizes` to be 4-dimensional. Otherwise, it gives a `CHECK` failure which can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 50156d547b9a1da0144d7babe665cf690305b33c. The fix will be included in TensorFlow 2.10.0. • https://github.com/tensorflow/tensorflow/commit/50156d547b9a1da0144d7babe665cf690305b33c https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q2c3-jpmc-gfjx • CWE-617: Reachable Assertion •
CVE-2022-35970 – Segfault in `QuantizedInstanceNorm` in TensorFlow
https://notcve.org/view.php?id=CVE-2022-35970
TensorFlow is an open source platform for machine learning. If `QuantizedInstanceNorm` is given `x_min` or `x_max` tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 785d67a78a1d533759fcd2f5e8d6ef778de849e0. 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. • https://github.com/tensorflow/tensorflow/commit/785d67a78a1d533759fcd2f5e8d6ef778de849e0 https://github.com/tensorflow/tensorflow/security/advisories/GHSA-g35r-369w-3fqp • CWE-20: Improper Input Validation •