CVE-2022-29192: TensorFlow - Missing validation crashes QuantizeAndDequantizeV4Grad
Summary
CVE-2022-29192: Missing validation crashes QuantizeAndDequantizeV4Grad. 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-2022-29192 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 that provides a comprehensive ecosystem of tools, libraries, and community resources. It allows developers to build and deploy machine learning models for various applications. TensorFlow includes a wide range of operations and functions to manipulate and process data efficiently. However, a vulnerability has been discovered in the implementation of the tf.raw_ops.QuantizeAndDequantizeV4Grad function, which can lead to a denial of service attack.
Vulnerability Detail
The vulnerability arises from the lack of proper validation in the QuantizeAndDequantizeV4Grad function of TensorFlow. This function is responsible for quantizing and dequantizing gradients. However, it does not adequately validate the input arguments, specifically input_min and input_max. As a result, an attacker can trigger a CHECK-failure, causing the program to crash and potentially leading to a denial of service attack. The code assumes that input_min and input_max are scalars, but there is no validation to ensure this.
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
There is no specific workaround mentioned for this vulnerability.
Conclusion
The vulnerability in TensorFlow's QuantizeAndDequantizeV4Grad function can be exploited to crash the program and potentially lead to a denial of service attack. It is crucial for users to update their TensorFlow installations to the fixed versions mentioned in the 'how_to_fix' section. For further support and assistance with 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 by crashing the program.
You can use Vulert's playground at Vulert Scanner to check if your application is affected by this vulnerability. Vulert monitors and alerts in real-time for open-source vulnerabilities without requiring access to the code or installation.
The vulnerability affects TensorFlow versions 2.6.4, 2.7.2, 2.8.1, and earlier. Users are advised to update to the fixed versions mentioned in the 'how_to_fix' section.
Yes, the CVSS score for this vulnerability is 5.5, indicating a moderate severity.
This vulnerability was reported by Neophytos Christou from the Secure Systems Lab at Brown University.
References
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