GHSA-5gqf-456p-4836

Dashboard / Vulnerabilities / GHSA-5gqf-456p-4836

GHSA-5gqf-456p-4836

Summary: Reference binding to nullptr in `SdcaOptimizer`

Details: ### Impact The implementation of `tf.raw_ops.SdcaOptimizer` triggers undefined behavior due to dereferencing a null pointer: ```python import tensorflow as tf sparse_example_indices = [tf.constant((0), dtype=tf.int64), tf.constant((0), dtype=tf.int64)] sparse_feature_indices = [tf.constant([], shape=[0, 0, 0, 0], dtype=tf.int64), tf.constant((0), dtype=tf.int64)] sparse_feature_values = [] dense_features = [] dense_weights = [] example_weights = tf.constant((0.0), dtype=tf.float32) example_labels = tf.constant((0.0), dtype=tf.float32) sparse_indices = [tf.constant((0), dtype=tf.int64), tf.constant((0), dtype=tf.int64)] sparse_weights = [tf.constant((0.0), dtype=tf.float32), tf.constant((0.0), dtype=tf.float32)] example_state_data = tf.constant([0.0, 0.0, 0.0, 0.0], shape=[1, 4], dtype=tf.float32) tf.raw_ops.SdcaOptimizer( sparse_example_indices=sparse_example_indices, sparse_feature_indices=sparse_feature_indices, sparse_feature_values=sparse_feature_values, dense_features=dense_features, example_weights=example_weights, example_labels=example_labels, sparse_indices=sparse_indices, sparse_weights=sparse_weights, dense_weights=dense_weights, example_state_data=example_state_data, loss_type="logistic_loss", l1=0.0, l2=0.0, num_loss_partitions=1, num_inner_iterations=1, adaptative=False) ``` The [implementation](https://github.com/tensorflow/tensorflow/blob/60a45c8b6192a4699f2e2709a2645a751d435cc3/tensorflow/core/kernels/sdca_internal.cc) does not validate that the user supplied arguments satisfy all [constraints expected by the op](https://www.tensorflow.org/api_docs/python/tf/raw_ops/SdcaOptimizer). ### Patches We have patched the issue in GitHub commit [f7cc8755ac6683131fdfa7a8a121f9d7a9dec6fb](https://github.com/tensorflow/tensorflow/commit/f7cc8755ac6683131fdfa7a8a121f9d7a9dec6fb). 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. ### 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 Ying Wang and Yakun Zhang of Baidu X-Team.

References: https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5gqf-456p-4836, https://nvd.nist.gov/vuln/detail/CVE-2021-29572, https://github.com/tensorflow/tensorflow/commit/f7cc8755ac6683131fdfa7a8a121f9d7a9dec6fb, https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-500.yaml, https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-698.yaml, https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-209.yaml, https://github.com/tensorflow/tensorflow