Null pointer dereference via invalid Ragged Tensors
Low2.5CVE-2021-29516 · Published May 21, 2021 · updated Jul 8, 2026
### Impact Calling `tf.raw_ops.RaggedTensorToVariant` with arguments specifying an invalid ragged tensor results in a null pointer dereference: ```python import tensorflow as tf input_tensor = tf.constant([], shape=[0, 0, 0, 0, 0], dtype=tf.float32) filter_tensor = tf.constant([], shape=[0, 0, 0, 0, 0], dtype=tf.float32) tf.raw_ops.Conv3D(input=input_tensor, filter=filter_tensor, strides=[1, 56, 56, 56, 1], padding='VALID', data_format='NDHWC', dilations=[1, 1, 1, 23, 1]) ``` ```python import tensorflow as tf input_tensor = tf.constant([], shape=[2, 2, 2, 2, 0], dtype=tf.float32) filter_tensor = tf.constant([], shape=[0, 0, 2, 6, 2], dtype=tf.float32) tf.raw_ops.Conv3D(input=input_tensor, filter=filter_tensor, strides=[1, 56, 39, 34, 1], padding='VALID', data_format='NDHWC', dilations=[1, 1, 1, 1, 1]) ``` The implementation of [`RaggedTensorToVariant` operations](https://github.com/tensorflow/tensorflow/blob/904b3926ed1c6c70380d5313d282d248a776baa1/tensorflow/core/kernels/ragged_tensor_to_variant_op.cc#L39-L40) does not validate that the ragged tensor argument is non-empty: ```cc int ragged_rank = batched_ragged.ragged_rank(); auto batched_splits_top_vec = batched_ragge...
Affected versions
| Package | Affected | Fixed in |
|---|---|---|
| tensorflow PyPI | < 2.1.4 | 2.1.4 |
| >= 2.2.0, < 2.2.3 | 2.2.3 | |
| >= 2.3.0, < 2.3.3 | 2.3.3 | |
| >= 2.4.0, < 2.4.2 | 2.4.2 |
Details and references
### Impact Calling `tf.raw_ops.RaggedTensorToVariant` with arguments specifying an invalid ragged tensor results in a null pointer dereference: ```python import tensorflow as tf input_tensor = tf.constant([], shape=[0, 0, 0, 0, 0], dtype=tf.float32) filter_tensor = tf.constant([], shape=[0, 0, 0, 0, 0], dtype=tf.float32) tf.raw_ops.Conv3D(input=input_tensor, filter=filter_tensor, strides=[1, 56, 56, 56, 1], padding='VALID', data_format='NDHWC', dilations=[1, 1, 1, 23, 1]) ``` ```python import tensorflow as tf input_tensor = tf.constant([], shape=[2, 2, 2, 2, 0], dtype=tf.float32) filter_tensor = tf.constant([], shape=[0, 0, 2, 6, 2], dtype=tf.float32) tf.raw_ops.Conv3D(input=input_tensor, filter=filter_tensor, strides=[1, 56, 39, 34, 1], padding='VALID', data_format='NDHWC', dilations=[1, 1, 1, 1, 1]) ``` The implementation of [`RaggedTensorToVariant` operations](https://github.com/tensorflow/tensorflow/blob/904b3926ed1c6c70380d5313d282d248a776baa1/tensorflow/core/kernels/ragged_tensor_to_variant_op.cc#L39-L40) does not validate that the ragged tensor argument is non-empty: ```cc int ragged_rank = batched_ragged.ragged_rank(); auto batched_splits_top_vec = batched_ragged.splits(0).vec<SPLIT_TYPE>(); ``` Since `batched_ragged` contains no elements, `batched_ragged.splits` is a null vector, thus `batched_ragged.splits(0)` will result in dereferencing `nullptr`. ### Patches We have patched the issue in GitHub commit [b055b9c474cd376259dde8779908f9eeaf097d93](https://github.com/tensorflow/tensorflow/commit/b055b9c474cd376259dde8779908f9eeaf097d93). 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 Yakun Zhang and Ying Wang of Baidu X-Team.
- CVSS 3.1
- CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L
- Severity from
- GitHub (reviewed advisory)
- Weakness
- CWE-476
- Also known as
- BIT-tensorflow-2021-29516, CVE-2021-29516, PYSEC-2021-153, PYSEC-2021-444, PYSEC-2021-642
- github.com/tensorflow/tensorflow/security/advisories/GHSA-84mw-34w6-2q43
- nvd.nist.gov/vuln/detail/CVE-2021-29516
- github.com/tensorflow/tensorflow/commit/b055b9c474cd376259dde8779908f9eeaf097d93
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-444.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-642.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-153.yaml
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