CVE-2018-10055: TensorFlow XLA Compiler Heap Buffer Overflow
Summary
CVE-2018-10055: Invalid memory access and/or a heap buffer overflow in the TensorFlow XLA compiler in Google TensorFlow before 1.7.1 could cause a crash or read from other parts of process memory via a crafted configuration file. Affects tensorflow-cpu versions < 1.7.1. Fixed in 1.7.1. How to fix ↓
Also tracked for
- tensorflow · PyPI
- tensorflow · PyPI
- tensorflow-gpu · PyPI
The same CVE-2018-10055 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. The TensorFlow XLA compiler is responsible for optimizing and accelerating TensorFlow computations. However, versions prior to 1.7.1 are vulnerable to an invalid memory access and/or a heap buffer overflow. This vulnerability can be exploited by a crafted configuration file, leading to crashes or unauthorized access to process memory.
Vulnerability Detail
The vulnerability in the TensorFlow XLA compiler arises from an invalid memory access and/or a heap buffer overflow. An attacker can exploit this by providing a specially crafted configuration file. This can result in crashes or unauthorized access to other parts of the process memory. The impact of this vulnerability can be severe, potentially leading to information disclosure or remote code execution.
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
1.7.1
This is the first release that contains the fix.
pip install --upgrade "tensorflow-cpu==1.7.1"Tip — Not sure which version your app runs? Vulert can match this fix to it. Scan free →
Workaround
There is no known workaround for this vulnerability. It is crucial to update to the patched version of TensorFlow to ensure the security of the system.
Conclusion
The TensorFlow XLA compiler in versions prior to 1.7.1 is vulnerable to an invalid memory access and/or a heap buffer overflow. This can be exploited by a crafted configuration file, potentially leading to crashes or unauthorized access to process memory. To mitigate this vulnerability, it is essential to update to TensorFlow version 1.7.1 or later. For further assistance or support 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 tools and resources for building and deploying machine learning models.
The TensorFlow XLA compiler is responsible for optimizing and accelerating TensorFlow computations.
This vulnerability can lead to crashes or unauthorized access to process memory, potentially resulting in information disclosure or remote code execution.
To fix this vulnerability, it is recommended to upgrade to TensorFlow version 1.7.1 or later.
There is no known workaround for this vulnerability. It is crucial to update to the patched version of TensorFlow.
References
Related vulnerabilities
Recent vulnerabilities recorded for tensorflow-cpu.
