CVE-2022-35993: TensorFlow Denial of Service Vulnerability
Summary
CVE-2022-35993: CHECK fail in SetSize in TensorFlow. Affects tensorflow across 3 version ranges.
< 2.7.2
>= 2.8.0, < 2.8.1
>= 2.9.0, < 2.9.1
Fixed in 2.7.2, 2.8.1 or 2.9.1, depending on the release line you run. How to fix ↓
Also tracked for
- tensorflow · PyPI
- tensorflow-cpu · PyPI
- tensorflow-gpu · PyPI
- tensorflow · PyPI
The same CVE-2022-35993 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
Background
TensorFlow is an open source platform for machine learning. It provides a comprehensive ecosystem of tools, libraries, and resources for developing and deploying machine learning models. TensorFlow is widely used in various industries and research fields for tasks such as image recognition, natural language processing, and recommendation systems. However, a vulnerability has been discovered in TensorFlow that can lead to a denial of service attack.
Vulnerability Detail
The vulnerability in TensorFlow occurs when the SetSize function receives an input set_shape that is not a 1D tensor. This triggers a CHECK fails, which can be exploited to launch a denial of service attack. An attacker can craft a malicious input that triggers this vulnerability, causing the TensorFlow application to crash or become unresponsive. This can lead to service disruption and potential financial losses for affected organizations. The vulnerability has been assigned the CVE identifier CVE-2022-35993.
How To Fix
Fixed versions by release line
The minimum fixed version depends on the release line you run.
-
< 2.7.22.7.2 -
>= 2.8.0, < 2.8.12.8.1 -
>= 2.9.0, < 2.9.12.9.1
Tip — Not sure which release line you're on? Vulert can find the fix for the version you are using. Scan free →
Workaround
There are no known workarounds for this vulnerability. It is necessary to apply the provided fix by upgrading to the patched versions of TensorFlow.
Conclusion
The vulnerability in TensorFlow can be exploited to launch a denial of service attack, leading to service disruption and potential financial losses. It is crucial to upgrade to the patched versions of TensorFlow to mitigate this vulnerability. For further support on vulnerability remediation, you can contact DevNack.com.
See every vulnerability recorded for tensorflow →
FAQ
TensorFlow is an open source platform for machine learning that provides tools and libraries for developing and deploying machine learning models.
A denial of service attack is a malicious attempt to disrupt the normal functioning of a computer system or network. It aims to make a service or resource unavailable to its intended users.
The vulnerability can be exploited by providing a malicious input to the SetSize function in TensorFlow, triggering a CHECK fails and causing a denial of service attack.
The vulnerability can lead to service disruption and potential financial losses for organizations using TensorFlow. It can also impact the availability and reliability of machine learning models and applications.
To fix the vulnerability, you need to upgrade your TensorFlow installation to one of the patched versions: TensorFlow 2.10.0, TensorFlow 2.9.1, TensorFlow 2.8.1, or TensorFlow 2.7.2.
References
Related vulnerabilities
Recent vulnerabilities recorded for tensorflow.
