Null pointer dereference in TensorFlow
### Impact The [implementation of `QuantizedMaxPool`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/quantized_pooling_ops.cc#L114-L130) has an undefined behavior where user controlled inputs can trigger a reference binding to null pointer. ```python import tensorflow as tf tf.raw_ops.QuantizedMaxPool( input = tf.constant([[[[4]]]], dtype=tf.quint8), min_input = [], max_input = [1], ksize = [1, 1, 1, 1], strides = [1, 1, 1, 1], padding = "SAME", name=None ) ``` ### Patches We have patched the issue in GitHub commit [53b0dd6dc5957652f35964af16b892ec9af4a559](https://github.com/tensorflow/tensorflow/commit/53b0dd6dc5957652f35964af16b892ec9af4a559). The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. ### 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. ### Attribution This vulnerability has been reported by Faysal Hossain Shezan from University of Virginia.
02 / AFFECTED SOFTWARE
Affected packages
26 explicit affected versions
61 explicit affected versions
62 explicit affected versions
27 explicit affected versions
62 explicit affected versions
62 explicit affected versions
18 explicit affected versions
03 / CONNECTIONS
Connected vulnerabilities
04 / EVIDENCE
Source records
Tensorflow is an Open Source Machine Learning Framework. The implementation of `QuantizedMaxPool` has an undefined behavior where user controlled inputs can trigger a reference binding to null pointer. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Tensorflow is an Open Source Machine Learning Framework. The implementation of `QuantizedMaxPool` has an undefined behavior where user controlled inputs can trigger a reference binding to null pointer. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Tensorflow is an Open Source Machine Learning Framework. The implementation of `QuantizedMaxPool` has an undefined behavior where user controlled inputs can trigger a reference binding to null pointer. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Tensorflow is an Open Source Machine Learning Framework. The implementation of `QuantizedMaxPool` has an undefined behavior where user controlled inputs can trigger a reference binding to null pointer. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
### Impact The [implementation of `QuantizedMaxPool`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/quantized_pooling_ops.cc#L114-L130) has an undefined behavior where user controlled inputs can trigger a reference binding to null pointer. ```python import tensorflow as tf tf.raw_ops.QuantizedMaxPool( input = tf.constant([[[[4]]]], dtype=tf.quint8), min_input = [], max_input = [1], ksize = [1, 1, 1, 1], strides = [1, 1, 1, 1], padding = "SAME", name=None ) ``` ### Patches We have patched the issue in GitHub commit [53b0dd6dc5957652f35964af16b892ec9af4a559](https://github.com/tensorflow/tensorflow/commit/53b0dd6dc5957652f35964af16b892ec9af4a559). The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. ### 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. ### Attribution This vulnerability has been reported by Faysal Hossain Shezan from University of Virginia.
### Impact The [implementation of `QuantizedMaxPool`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/quantized_pooling_ops.cc#L114-L130) has an undefined behavior where user controlled inputs can trigger a reference binding to null pointer. ```python import tensorflow as tf tf.raw_ops.QuantizedMaxPool( input = tf.constant([[[[4]]]], dtype=tf.quint8), min_input = [], max_input = [1], ksize = [1, 1, 1, 1], strides = [1, 1, 1, 1], padding = "SAME", name=None ) ``` ### Patches We have patched the issue in GitHub commit [53b0dd6dc5957652f35964af16b892ec9af4a559](https://github.com/tensorflow/tensorflow/commit/53b0dd6dc5957652f35964af16b892ec9af4a559). The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. ### 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. ### Attribution This vulnerability has been reported by Faysal Hossain Shezan from University of Virginia.
05 / REFERENCES
Further evidence
- https://github.com/CVEProject/cvelistV5/tree/main/cves/2022/21xxx/CVE-2022-21739.json
- https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/quantized_pooling_ops.cc#L114-L130
- https://github.com/tensorflow/tensorflow/commit/53b0dd6dc5957652f35964af16b892ec9af4a559
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3mw4-6rj6-74g5
- https://nvd.nist.gov/vuln/detail/CVE-2022-21739
- https://github.com/advisories/GHSA-3mw4-6rj6-74g5
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-63.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-118.yaml
- https://github.com/tensorflow/tensorflow
- https://pypi.org/project/tensorflow