CVE-2022-29195: Denial of Service Vulnerability in TensorFlow
Summary
CVE-2022-29195: Missing validation causes denial of service via StagePeek. Affects tensorflow across 3 version ranges.
< 2.6.4
>= 2.7.0, < 2.7.2
>= 2.8.0, < 2.8.1
Fixed in 2.6.4, 2.7.2 or 2.8.1, depending on the release line you run. How to fix ↓
Also tracked for
- tensorflow-cpu · PyPI
- tensorflow-gpu · PyPI
- tensorflow · Bitnami
The same CVE-2022-29195 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 is widely used in various domains, including research, industry, and academia. However, a vulnerability has been discovered in TensorFlow that can lead to a denial of service attack.
Vulnerability Detail
The vulnerability, identified as CVE-2022-29195, is caused by missing validation in the implementation of tf.raw_ops.StagePeek function. This function is used to peek at the contents of a TensorFlow stage. The code does not properly validate the input arguments, specifically the index parameter, which is assumed to be a scalar. As a result, an attacker can exploit this vulnerability by providing a malicious input, triggering a CHECK failure and causing a denial of service attack. The impact of this vulnerability can be significant, as it can disrupt the availability of TensorFlow-based applications and services.
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.
-
< 2.6.42.6.4pip install --upgrade "tensorflow==2.6.4" -
>= 2.7.0, < 2.7.22.7.2pip install --upgrade "tensorflow==2.7.2" -
>= 2.8.0, < 2.8.12.8.1pip install --upgrade "tensorflow==2.8.1"
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Workaround
As a workaround, users can implement input validation before calling the tf.raw_ops.StagePeek function. This can be done by ensuring that the index parameter is a scalar value. Here is an example of how to perform the validation in Python:
import tensorflow as tf
index = tf.constant([], shape=[0], dtype=tf.int32)
if tf.rank(index) != 0:
raise ValueError('Index must be a scalar')
# Call the StagePeek function
# ...
By validating the input, the vulnerability can be mitigated.
Conclusion
In conclusion, TensorFlow is affected by a denial of service vulnerability that can be exploited by providing a malicious input to the tf.raw_ops.StagePeek function. To mitigate the risk, it is crucial to update TensorFlow to the latest patched version. Implementing input validation can also help reduce the impact of this vulnerability. For further support and assistance in vulnerability remediation, please contact DevNack.com.
See every vulnerability recorded for tensorflow →
FAQ
The vulnerability can be exploited to trigger a denial of service attack, leading to the unavailability of TensorFlow-based applications and services.
To fix the vulnerability, it is recommended to update TensorFlow to the latest patched version (2.6.4, 2.7.2, or 2.8.1).
Yes, a workaround is to implement input validation before calling the vulnerable function. This can help mitigate the risk.
Yes, this vulnerability can be exploited remotely by providing a malicious input to the vulnerable function.
This vulnerability was reported by Neophytos Christou from Secure Systems Lab at Brown University.
References
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