CVE-2021-29616: Null dereference in Grappler's TrySimplify in TensorFlow
Summary
CVE-2021-29616: Null dereference in Grappler's TrySimplify. Affects tensorflow across 4 version ranges.
< 2.1.4
>= 2.2.0, < 2.2.3
>= 2.3.0, < 2.3.3
>= 2.4.0, < 2.4.2
Fixed in 4 releases; the minimum fixed version depends on the release line you run. How to fix ↓
Also tracked for
- tensorflow · Bitnami
- tensorflow-cpu · PyPI
- tensorflow-gpu · PyPI
The same CVE-2021-29616 is tracked separately for each ecosystem and vendor. Its fix information is the same; the package and affected versions differ.
Check if this vulnerability affects your application
Upload a manifest or SBOM and we'll show whether you're affected, plus every other risky package in the same scan.
No signup required · Results in about 60 seconds
Habilume
Habit tracker with a companion that grows with you
Complete habits, earn Lume Points, and watch your Lume grow as you stay consistent.
Background
TensorFlow is an open-source machine learning framework widely used for building and training various models. It provides a comprehensive ecosystem of tools, libraries, and resources for developing artificial intelligence applications. TensorFlow is susceptible to a null dereference vulnerability in Grappler's TrySimplify function, which can lead to undefined behavior when optimizing a node with no inputs.
Vulnerability Detail
The vulnerability arises from the implementation of TrySimplify in TensorFlow's Grappler module. In certain corner cases, when attempting to optimize a node without any inputs, a null pointer is dereferenced, resulting in undefined behavior. This vulnerability can potentially be exploited by an attacker to cause a denial-of-service (DoS) condition 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.
-
< 2.1.42.1.4pip install --upgrade "tensorflow==2.1.4" -
>= 2.2.0, < 2.2.32.2.3pip install --upgrade "tensorflow==2.2.3" -
>= 2.3.0, < 2.3.32.3.3pip install --upgrade "tensorflow==2.3.3" -
>= 2.4.0, < 2.4.22.4.2pip install --upgrade "tensorflow==2.4.2"
Tip — Not sure which release line you're on? Vulert can find the fix for the version you are using. Scan free →
Workaround
There is no specific workaround provided for this vulnerability. It is advised to update to the patched versions of TensorFlow as mentioned in the 'how_to_fix' section.
Conclusion
The null dereference vulnerability in Grappler's TrySimplify function in TensorFlow can have serious consequences, including DoS attacks and arbitrary code execution. It is crucial to update to the patched versions or apply the provided fixes to mitigate the risk. For further assistance and support in vulnerability remediation, please contact DevNack.com.
See every vulnerability recorded for tensorflow →
FAQ
TensorFlow is an open-source machine learning framework used for developing and training AI models.
The vulnerability can lead to undefined behavior, potentially resulting in a denial-of-service condition or arbitrary code execution.
To fix this vulnerability, update TensorFlow to version 2.5.0 or apply the relevant patches.
Yes, TensorFlow versions 2.1.4, 2.2.3, 2.3.3, and 2.4.2 are also affected and should be updated.
For more information, refer to the TensorFlow security guide available on GitHub.
References
Related vulnerabilities
Recent vulnerabilities recorded for tensorflow.
Habilume
Habit tracker with a companion that grows with you
Complete habits, earn Lume Points, and watch your Lume grow as you stay consistent.
