CVE-2018-8825: Buffer Overflow in Google TensorFlow
Summary
CVE-2018-8825: Improper Restriction of Operations within the Bounds of a Memory Buffer in Google TensorFlow. Affects tensorflow versions >= 1.5.0, < 1.7.1. Fixed in 1.7.1. How to fix ↓
Also tracked for
- tensorflow-cpu · PyPI
- tensorflow-gpu · PyPI
The same CVE-2018-8825 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 set of tools and libraries for numerical computation and large-scale machine learning. TensorFlow is widely adopted and used in various industries for a range of applications, including image recognition, natural language processing, and recommendation systems. However, versions 1.7 and below of TensorFlow are vulnerable to a buffer overflow issue.
Vulnerability Detail
The buffer overflow vulnerability in Google TensorFlow 1.7 and below allows for the execution of arbitrary code in a local context. This vulnerability arises due to improper restriction of operations within the bounds of a memory buffer. An attacker could exploit this vulnerability to execute malicious code, potentially leading to unauthorized access, data leakage, or system compromise. The severity of this vulnerability is rated as HIGH with a CVSS score of 8.8.
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 version below is the minimum fixed release for this vulnerability.
If you need the minimum change
1.7.1
This is the first release that contains the fix.
pip install --upgrade "tensorflow==1.7.1"Tip — Not sure which version your app runs? Vulert can match this fix to it. Scan free →
Workaround
There is no specific workaround mentioned for this vulnerability. However, users can follow the recommended fix by upgrading to TensorFlow version 1.7.1 or above.
Conclusion
In conclusion, the buffer overflow vulnerability in Google TensorFlow 1.7 and below poses a significant risk to the security and integrity of systems using this framework. It is crucial for users to upgrade to the latest stable release of TensorFlow and regularly apply updates to mitigate the risk. For further support and assistance in vulnerability remediation, please contact DevNack.com.
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FAQ
Google TensorFlow is an open-source machine learning framework used for building and training neural networks. It provides a comprehensive set of tools and libraries for numerical computation and large-scale machine learning.
A buffer overflow vulnerability occurs when a program writes data beyond the boundaries of a fixed-size buffer, potentially overwriting adjacent memory areas. This can lead to the execution of arbitrary code or the manipulation of program behavior.
The impact of this vulnerability is the ability for an attacker to execute arbitrary code in a local context. This can lead to unauthorized access, data leakage, or system compromise.
To fix this vulnerability, it is recommended to upgrade to TensorFlow version 1.7.1 or above. Apply patches and updates provided by the TensorFlow development team.
There is no specific workaround mentioned for this vulnerability. Upgrading to TensorFlow version 1.7.1 or above is the recommended fix.
References
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