CVE-2018-7577: Memcpy parameter overlap in Google Snappy library in TensorFlow
Summary
CVE-2018-7577: Memcpy parameter overlap in Google Snappy library 1.1.4, as used in Google TensorFlow before 1.7.1, could result in a crash or read from other parts of process memory. 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-2018-7577 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 community resources that enable researchers and developers to build and deploy machine learning models. The TensorFlow CPU package, available on PyPI, is a Python library that allows users to run TensorFlow on CPUs. The package is widely used in various applications and environments.
Vulnerability Detail
The vulnerability identified as CVE-2018-7577 affects the Google Snappy library version 1.1.4, which is utilized by Google TensorFlow prior to version 1.7.1. The issue arises from a memcpy parameter overlap, which can lead to a crash or unauthorized read access to other parts of the process memory. This vulnerability poses a significant security risk as an attacker could potentially exploit it to gain sensitive information or disrupt the functioning of the affected TensorFlow instances.
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 →
Conclusion
The vulnerability identified as CVE-2018-7577 in the Google Snappy library used by TensorFlow prior to version 1.7.1 can lead to crashes or unauthorized memory access. It is crucial to upgrade the TensorFlow CPU package to version 1.7.1 or later to mitigate this vulnerability. For further assistance or support in vulnerability remediation, please contact DevNack.com.
See every vulnerability recorded for tensorflow-cpu →
FAQ
The vulnerability can result in a crash or unauthorized read access to process memory, potentially leading to information disclosure or disruption of TensorFlow functionality.
Versions of TensorFlow prior to 1.7.1 are affected by this vulnerability.
No specific workaround has been provided for this vulnerability. It is recommended to upgrade to the fixed version of the TensorFlow CPU package.
There are no known instances of this vulnerability being exploited in the wild. However, it is crucial to apply the necessary updates to mitigate the risk.
For more information about this vulnerability, you can refer to the official advisory in the PyPI advisory database: https://github.com/pypa/advisory-database/blob/main/vulns/tensorflow-cpu/PYSEC-2019-225.yaml
References
Related vulnerabilities
Recent vulnerabilities recorded for tensorflow-cpu.
