CVE-2021-29516
Null pointer dereference via invalid Ragged Tensors
TensorFlow is an end-to-end open source platform for machine learning. Calling tf.raw_ops.RaggedTensorToVariant with arguments specifying an invalid ragged tensor results in a null pointer dereference. 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. Since batched_ragged contains no elements, batched_ragged.splits is a null vector, thus batched_ragged.splits(0) will result in dereferencing nullptr. 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.
Attack profile
How easy it is to exploit
- Attack vector
- Local
- Complexity
- High
- Privileges needed
- Low
- User interaction
- None
What an attacker can affect
- Confidentiality
- None
- Integrity
- None
- Availability
- Low
Exploit likelihood
What each source reports
CVE List Score used
2.5
Null pointer dereference via invalid Ragged Tensors
TensorFlow is an end-to-end open source platform for machine learning. Calling tf.raw_ops.RaggedTensorToVariant with arguments specifying an invalid ragged tensor results in a null pointer dereference. 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. Since batched_ragged contains no elements, batched_ragged.splits is a null vector, thus batched_ragged.splits(0) will result in dereferencing nullptr. 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.
- Record
CVE-2021-29516- CVSS 3.1
- 2.5 Low
CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L - Weakness
- CWE-476
- Updated
- 2026-11-02
EUVDEUVD-2021-0257
2.5
TensorFlow is an end-to-end open source platform for machine learning. Calling tf.raw_ops.RaggedTensorToVariant with arguments specifying an invalid ragged tensor results in a null pointer dereference. 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. Since batched_ragged contains no elements, batched_ragged.splits is a null vector, thus batched_ragged.splits(0) will result in dereferencing nullptr. 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.
- Record
EUVD-2021-0257- CVSS 3.1
- 2.5 Low
CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L - Updated
- 2026-11-03
GitHub AdvisoriesGHSA-84mw-34w6-2q43
2.0
Null pointer dereference via invalid Ragged Tensors
Impact
Calling tf.raw_ops.RaggedTensorToVariant with arguments specifying an invalid ragged tensor results in a null pointer dereference:
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])
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 does not validate that the ragged tensor argument is non-empty:
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.
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 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.
- Record
GHSA-84mw-34w6-2q43- CVSS 4.0
- 2.0 Low
CVSS:4.0/AV:L/AC:L/AT:P/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N - CVSS 3.1
- 2.5 Low
CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L - Weakness
- CWE-476
- Updated
- 2026-11-02
NVD
2.5
TensorFlow is an end-to-end open source platform for machine learning. Calling tf.raw_ops.RaggedTensorToVariant with arguments specifying an invalid ragged tensor results in a null pointer dereference. 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. Since batched_ragged contains no elements, batched_ragged.splits is a null vector, thus batched_ragged.splits(0) will result in dereferencing nullptr. 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.
- Record
CVE-2021-29516- CVSS 3.1
- 2.5 Low
CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L - CVSS 3.1
- 5.5 Medium
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H - CVSS 2.0
- 2.1 Low
AV:L/AC:L/Au:N/C:N/I:N/A:P - Weakness
- CWE-476
- Updated
- 2026-11-02
OSV
5.5
TensorFlow is an end-to-end open source platform for machine learning. Calling tf.raw_ops.RaggedTensorToVariant with arguments specifying an invalid ragged tensor results in a null pointer dereference. 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. Since batched_ragged contains no elements, batched_ragged.splits is a null vector, thus batched_ragged.splits(0) will result in dereferencing nullptr. 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.
- Record
CVE-2021-29516- CVSS 3.1
- 5.5 Medium
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H - Updated
- 2026-11-02
OSVGHSA-84mw-34w6-2q43
2.0
Null pointer dereference via invalid Ragged Tensors
Impact
Calling tf.raw_ops.RaggedTensorToVariant with arguments specifying an invalid ragged tensor results in a null pointer dereference:
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])
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 does not validate that the ragged tensor argument is non-empty:
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.
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 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.
- Record
GHSA-84mw-34w6-2q43- CVSS 4.0
- 2.0 Low
CVSS:4.0/AV:L/AC:L/AT:P/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N - CVSS 3.1
- 2.5 Low
CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L - Weakness
- CWE-476
- Updated
- 2026-11-02
Show 4 moreShow less
OSVBIT-tensorflow-2021-29516 No score
Null pointer dereference via invalid Ragged Tensors
TensorFlow is an end-to-end open source platform for machine learning. Calling tf.raw_ops.RaggedTensorToVariant with arguments specifying an invalid ragged tensor results in a null pointer dereference. 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. Since batched_ragged contains no elements, batched_ragged.splits is a null vector, thus batched_ragged.splits(0) will result in dereferencing nullptr. 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.
- Record
BIT-tensorflow-2021-29516- Updated
- 2026-11-02
OSVPYSEC-2021-153 No score
TensorFlow is an end-to-end open source platform for machine learning. Calling tf.raw_ops.RaggedTensorToVariant with arguments specifying an invalid ragged tensor results in a null pointer dereference. 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. Since batched_ragged contains no elements, batched_ragged.splits is a null vector, thus batched_ragged.splits(0) will result in dereferencing nullptr. 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.
- Record
PYSEC-2021-153- Updated
- 2026-11-02
OSVPYSEC-2021-444 No score
TensorFlow is an end-to-end open source platform for machine learning. Calling tf.raw_ops.RaggedTensorToVariant with arguments specifying an invalid ragged tensor results in a null pointer dereference. 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. Since batched_ragged contains no elements, batched_ragged.splits is a null vector, thus batched_ragged.splits(0) will result in dereferencing nullptr. 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.
- Record
PYSEC-2021-444- Updated
- 2026-11-02
OSVPYSEC-2021-642 No score
TensorFlow is an end-to-end open source platform for machine learning. Calling tf.raw_ops.RaggedTensorToVariant with arguments specifying an invalid ragged tensor results in a null pointer dereference. 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. Since batched_ragged contains no elements, batched_ragged.splits is a null vector, thus batched_ragged.splits(0) will result in dereferencing nullptr. 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.
- Record
PYSEC-2021-642- Updated
- 2026-11-02
Affected products
Affected packages
| Package | Affected | Fixed |
|---|---|---|
tensorflowPyPI |
before 2.1.4 | 2.1.4 |
tensorflowPyPI |
2.2.0 up to 2.2.3 | 2.2.3 |
tensorflowPyPI |
2.3.0 up to 2.3.3 | 2.3.3 |
tensorflowPyPI |
2.4.0 up to 2.4.2 | 2.4.2 |
tensorflow-cpuPyPI |
before 2.1.4 | 2.1.4 |
tensorflow-cpuPyPI |
2.2.0 up to 2.2.3 | 2.2.3 |
tensorflow-cpuPyPI |
2.3.0 up to 2.3.3 | 2.3.3 |
tensorflow-cpuPyPI |
2.4.0 up to 2.4.2 | 2.4.2 |
tensorflow-gpuPyPI |
before 2.1.4 | 2.1.4 |
tensorflow-gpuPyPI |
2.2.0 up to 2.2.3 | 2.2.3 |
Show 18 moreShow less
| Package | Affected | Fixed |
|---|---|---|
tensorflow-gpuPyPI |
2.3.0 up to 2.3.3 | 2.3.3 |
tensorflow-gpuPyPI |
2.4.0 up to 2.4.2 | 2.4.2 |
tensorflowBitnami |
before 2.1.4, 2.2.0 up to 2.2.3, 2.3.0 up to 2.3.3, 2.4.0 up to 2.4.2 | 2.1.42.2.32.3.32.4.2 |
tensorflowPyPI |
before 2.1.4, plus listed versions 0.12.00.12.11.0.01.0.11.1.0 Show 35 moreShow less1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.3 |
2.1.4 |
tensorflowPyPI |
2.2.0 up to 2.2.3, plus listed versions 2.2.12.2.2 |
2.2.3 |
tensorflowPyPI |
2.3.0 up to 2.3.3, plus listed versions 2.3.12.3.2 |
2.3.3 |
tensorflowPyPI |
2.4.0 up to 2.4.2, plus listed versions 2.4.1 |
2.4.2 |
tensorflow-cpuPyPI |
before 2.1.4, plus listed versions 1.15.02.1.02.1.12.1.22.1.3 |
2.1.4 |
tensorflow-cpuPyPI |
2.2.0 up to 2.2.3, plus listed versions 2.2.12.2.2 |
2.2.3 |
tensorflow-cpuPyPI |
2.3.0 up to 2.3.3, plus listed versions 2.3.12.3.2 |
2.3.3 |
tensorflow-cpuPyPI |
2.4.0 up to 2.4.2, plus listed versions 2.4.1 |
2.4.2 |
tensorflow-gpuPyPI |
before 2.1.4, plus listed versions 0.12.00.12.11.0.01.0.11.1.0 Show 35 moreShow less1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.3 |
2.1.4 |
tensorflow-gpuPyPI |
2.2.0 up to 2.2.3, plus listed versions 2.2.12.2.2 |
2.2.3 |
tensorflow-gpuPyPI |
2.3.0 up to 2.3.3, plus listed versions 2.3.12.3.2 |
2.3.3 |
tensorflow-gpuPyPI |
2.4.0 up to 2.4.2, plus listed versions 2.4.1 |
2.4.2 |
tensorflowPyPI |
before 2.1.4, 2.2.0 up to 2.2.3, 2.3.0 up to 2.3.3, 2.4.0 up to 2.4.2, plus listed versions 0.12.00.12.0rc00.12.0rc10.12.11.0.0 Show 45 moreShow less1.0.11.1.01.1.0rc01.1.0rc11.1.0rc21.10.01.10.0rc01.10.0rc11.10.11.11.01.11.0rc01.11.0rc11.11.0rc21.12.01.12.0rc01.12.0rc11.12.0rc21.12.21.12.31.13.0rc01.13.0rc11.13.0rc21.13.11.13.21.14.01.14.0rc01.14.0rc11.15.01.15.0rc01.15.0rc11.15.0rc21.15.0rc31.15.21.15.31.15.41.15.51.2.01.2.0rc01.2.0rc11.2.0rc21.2.11.3.01.3.0rc01.3.0rc11.3.0rc2 |
2.1.42.2.32.3.32.4.2 |
tensorflow-cpuPyPI |
before 2.1.4, 2.2.0 up to 2.2.3, 2.3.0 up to 2.3.3, 2.4.0 up to 2.4.2, plus listed versions 1.15.02.1.02.1.12.1.22.1.3 Show 5 moreShow less2.2.12.2.22.3.12.3.22.4.1 |
2.1.42.2.32.3.32.4.2 |
tensorflow-gpuPyPI |
before 2.1.4, 2.2.0 up to 2.2.3, 2.3.0 up to 2.3.3, 2.4.0 up to 2.4.2, plus listed versions 0.12.00.12.11.0.01.0.11.1.0 Show 40 moreShow less1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.32.2.12.2.22.3.12.3.22.4.1 |
2.1.42.2.32.3.32.4.2 |
History
| Recorded | Changed | Sources |
|---|---|---|
| aliases | EUVD | |
| first indexed | CVE List, GitHub Advisories, NVD, OSV |
Dates are when Every CVE recorded each change. Upstream dates may differ.
In short
CVE-2021-29516 is a low vulnerability (CVSS 2.5) in Google Tensorflow, published May 14, 2021. No source lists public exploit code. EPSS puts the chance of exploitation in the next 30 days at 0.20%, the 9th percentile. Fixed in tensorflow 2.1.4.
References
github.com/tensorflow/tensorflow/security/advisories/GHSA-84mw-34w6-2q43
github.com/tensorflow/tensorflow/commit/b055b9c474cd376259dde8779908f9eeaf097d93
nvd.nist.gov/vuln/detail/CVE-2021-29516
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
github.com/advisories/GHSA-84mw-34w6-2q43
Left out here: 45 versions. The JSON record has them.