CVE-2018-7576: Null Pointer Dereference in Google TensorFlow
Summary
CVE-2018-7576: Google TensorFlow 1.6.x and earlier is affected by: Null Pointer Dereference. The type of exploitation is: context-dependent. Affects tensorflow-cpu versions < 1.7.0rc0. Fixed in 1.7.0rc0. How to fix ↓
Also tracked for
- tensorflow · PyPI
- tensorflow · PyPI
- tensorflow-gpu · PyPI
The same CVE-2018-7576 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
Google TensorFlow is an open-source machine learning framework used for building and training neural networks. It provides a comprehensive ecosystem of tools, libraries, and resources for developing and deploying machine learning models. TensorFlow is widely adopted and utilized in various domains, including research, industry, and academia. However, versions 1.6.x and earlier of TensorFlow are affected by a vulnerability known as Null Pointer Dereference.
Vulnerability Detail
The Null Pointer Dereference vulnerability in TensorFlow arises from a context-dependent issue. It occurs when a null pointer is accessed, leading to a program crash or unexpected behavior. Exploiting this vulnerability could potentially allow an attacker to execute arbitrary code, cause a denial of service, or gain unauthorized access to sensitive information. The vulnerability was assigned the CVE identifier CVE-2018-7576.
How To Fix
Latest published version: 2.21.0 as of 22 Oct 2026
pip install --upgrade "tensorflow-cpu==2.21.0"Upgrading to it may include breaking changes; the version below is the minimum fixed release for this vulnerability.
If you need the minimum change
1.7.0rc0
This is the first release that contains the fix.
pip install --upgrade "tensorflow-cpu==1.7.0rc0"Tip — Not sure which version your app runs? Vulert can match this fix to it. Scan free →
Workaround
There is no specific workaround available for this vulnerability. It is crucial to apply the recommended fix by upgrading to a patched version of TensorFlow.
Conclusion
The Null Pointer Dereference vulnerability in Google TensorFlow can have severe consequences, including arbitrary code execution, denial of service, or unauthorized access to sensitive information. It is crucial for users of TensorFlow to upgrade to version 1.7.0rc0 or later to mitigate this vulnerability. For further support and assistance in vulnerability remediation, please contact DevNack.com.
See every vulnerability recorded for tensorflow-cpu →
FAQ
TensorFlow is an open-source machine learning framework developed by Google. It provides a platform for building and training neural networks.
A Null Pointer Dereference vulnerability occurs when a program attempts to access a memory address that is null (i.e., does not point to any valid object or data). This can lead to crashes, unexpected behavior, or security vulnerabilities.
Exploiting this vulnerability in TensorFlow could allow an attacker to execute arbitrary code, cause a denial of service, or gain unauthorized access to sensitive information.
To fix the vulnerability, it is recommended to upgrade to version 1.7.0rc0 or later of TensorFlow. This version includes the necessary patches and fixes to mitigate the vulnerability.
No, there is no specific workaround available for this vulnerability. It is essential to apply the recommended fix by upgrading to a patched version of TensorFlow.
References
Related vulnerabilities
Recent vulnerabilities recorded for tensorflow-cpu.
