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 versions < 1.7.1. Fixed in 1.7.1. How to fix ↓
Also tracked for
- tensorflow-cpu · 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 (Accelerated Linear Algebra) compiler is a component of TensorFlow that optimizes and compiles TensorFlow computations for execution on CPUs, GPUs, and other accelerators. This vulnerability affects versions of TensorFlow prior to 1.7.1.
Vulnerability Detail
The vulnerability in the TensorFlow XLA compiler is due to an invalid memory access and/or a heap buffer overflow. An attacker can exploit this vulnerability by crafting a malicious configuration file. If successful, this could lead to a crash or unauthorized access to other parts of the process memory. The impact of this vulnerability could range from denial of service to potential information disclosure.
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 known workaround for this vulnerability. It is essential to apply the recommended fix by upgrading to TensorFlow 1.7.1 or later.
Conclusion
The vulnerability in the TensorFlow XLA compiler can be addressed by upgrading to version 1.7.1 or later. It is crucial to keep software dependencies up to date to mitigate the risk of potential security vulnerabilities. For further support on vulnerability remediation, please contact DevNack.com.
See every vulnerability recorded for tensorflow →
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 a component of TensorFlow that optimizes and compiles TensorFlow computations for execution on various hardware accelerators.
This vulnerability could result in a crash or unauthorized access to process memory, potentially leading to denial of service or information disclosure.
To fix this vulnerability, upgrade to TensorFlow version 1.7.1 or later, which includes the necessary patches and fixes.
There is no known workaround for this vulnerability. It is crucial to apply the recommended fix by upgrading TensorFlow.
References
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