CVE-2021-41215: Null Pointer Exception in TensorFlow
Summary
CVE-2021-41215: Null pointer exception in DeserializeSparse. Affects tensorflow across 3 version ranges.
< 2.4.4
>= 2.5.0, < 2.5.2
>= 2.6.0, < 2.6.1
Fixed in 2.4.4, 2.5.2 or 2.6.1, depending on the release line you run. How to fix ↓
Also tracked for
- tensorflow · Bitnami
- tensorflow-cpu · PyPI
- tensorflow-gpu · PyPI
The same CVE-2021-41215 is tracked separately for each ecosystem and vendor. Its fix information is the same; the package and affected versions differ.
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Background
TensorFlow is an open-source machine learning framework developed by Google. It provides a comprehensive ecosystem of tools, libraries, and resources for building and deploying machine learning models. TensorFlow supports various platforms and is widely used in both research and production environments. However, a vulnerability has been identified in TensorFlow that can lead to a null pointer exception.
Vulnerability Detail
The vulnerability, identified as CVE-2021-41215, originates from a null pointer dereference in the DeserializeSparse function of TensorFlow. This vulnerability can be triggered when the shape inference code assumes that the serialize_sparse tensor has a positive rank and a specific last dimension. However, if the argument passed to the function is a scalar (rank 0), a null pointer exception occurs. This vulnerability can potentially be exploited by an attacker to cause a denial of service or execute arbitrary code.
How To Fix
Latest published version: 2.21.0 as of 22 Oct 2026
pip install --upgrade "tensorflow==2.21.0"Upgrading to it may include breaking changes; the versions below are the minimum fixed release for this vulnerability.
If you can't move to the latest
The minimum fixed version depends on the release line you run.
-
< 2.4.42.4.4pip install --upgrade "tensorflow==2.4.4" -
>= 2.5.0, < 2.5.22.5.2pip install --upgrade "tensorflow==2.5.2" -
>= 2.6.0, < 2.6.12.6.1pip install --upgrade "tensorflow==2.6.1"
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Workaround
If updating TensorFlow is not immediately possible, a workaround for this vulnerability is to ensure that the serialize_sparse tensor passed to the DeserializeSparse function has a positive rank and a valid last dimension. This can be achieved by reshaping the tensor or providing a tensor with the expected shape. Here is an example workaround in Python:
import tensorflow as tf
dataset = tf.data.Dataset.range(3)
@tf.function
def test():
serialized_sparse = tf.data.experimental.to_variant(dataset)
reshaped_sparse = tf.reshape(serialized_sparse, [1])
y = tf.raw_ops.DeserializeSparse(reshaped_sparse, dtype=tf.int32)
test()
Conclusion
The vulnerability CVE-2021-41215 in TensorFlow has been addressed by the TensorFlow team in versions 2.6.1, 2.5.2, and 2.4.4. Users are advised to update their TensorFlow installation to one of the patched versions to mitigate the risk of exploitation. It is recommended to always stay up to date with the latest stable version of TensorFlow for improved security. For further support on vulnerability remediation, please contact DevNack.com.
See every vulnerability recorded for tensorflow →
FAQ
TensorFlow is an open-source machine learning framework developed by Google. It provides tools and resources for building and deploying machine learning models.
The vulnerability can lead to a null pointer exception, potentially causing a denial of service or arbitrary code execution.
The vulnerability affects TensorFlow versions 2.4.4, 2.5.2, and 2.6.0.
To fix the vulnerability, update your TensorFlow installation to one of the patched versions: TensorFlow 2.6.1, TensorFlow 2.5.2, or TensorFlow 2.4.4.
Yes, a workaround is to ensure that the serialize_sparse tensor passed to the DeserializeSparse function has a positive rank and a valid last dimension.
References
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