CVE-2020-15203: Format String Vulnerability in TensorFlow
Summary
CVE-2020-15203: In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, by controlling the fill argument of tf.strings.as_string, a malicious attacker is able to trigger a format string vulnerability due to the way the inte... Affects tensorflow-cpu across 6 version ranges.
< 1.15.4
>= 2.0.0, < 2.0.3
>= 2.1.0, < 2.1.2
>= 2.2.0, < 2.2.1
>= 2.3.0, < 2.3.1
< 33be22c65d86256e6826666662e40dbdfe70ee83
Fixed in 5 releases; the minimum fixed version depends on the release line you run. How to fix ↓
Also tracked for
- tensorflow · Bitnami
- tensorflow · PyPI
- tensorflow-gpu · PyPI
- tensorflow · PyPI
The same CVE-2020-15203 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. TensorFlow is widely used in various domains, including research, industry, and academia. However, versions before 1.15.4, 2.0.3, 2.1.2, 2.2.1, and 2.3.1 are vulnerable to a format string vulnerability.
Vulnerability Detail
The vulnerability arises from the way the fill argument of tf.strings.as_string in TensorFlow is handled. An attacker can manipulate the fill argument to trigger a format string vulnerability. This vulnerability can lead to a segmentation fault and potentially enable an attacker to execute arbitrary code. The issue has been patched in commit 33be22c65d86256e6826666662e40dbdfe70ee83 and is addressed in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, and 2.3.1.
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 versions below are the minimum fixed release for this vulnerability.
If you can't move to the latest
The minimum fixed version depends on the release line you run.
-
< 1.15.41.15.4pip install --upgrade "tensorflow-cpu==1.15.4" -
>= 2.0.0, < 2.0.32.0.3pip install --upgrade "tensorflow-cpu==2.0.3" -
>= 2.1.0, < 2.1.22.1.2pip install --upgrade "tensorflow-cpu==2.1.2" -
>= 2.2.0, < 2.2.12.2.1pip install --upgrade "tensorflow-cpu==2.2.1" -
>= 2.3.0, < 2.3.12.3.1pip install --upgrade "tensorflow-cpu==2.3.1"
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Workaround
There is no known workaround for this vulnerability. It is crucial to update to the patched versions of TensorFlow to ensure the security of the application.
Conclusion
The format string vulnerability in TensorFlow versions before 1.15.4, 2.0.3, 2.1.2, 2.2.1, and 2.3.1 can be exploited by manipulating the fill argument of tf.strings.as_string. It is crucial to update to the patched versions to ensure the security of applications using TensorFlow. For further support on vulnerability remediation, you can 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.
A format string vulnerability occurs when a program uses user-supplied input as the format string parameter in a formatted printing function. If the input is not properly validated, an attacker can exploit this vulnerability to execute arbitrary code or cause a denial-of-service.
By manipulating the fill argument of tf.strings.as_string in TensorFlow, an attacker can trigger a format string vulnerability and potentially execute arbitrary code or cause a segmentation fault.
Yes, the vulnerability has been patched in commit 33be22c65d86256e6826666662e40dbdfe70ee83 and is addressed in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, and 2.3.1.
You can update TensorFlow by using the package manager to upgrade the package or by manually downloading and installing the updated version from the official TensorFlow repository.
References
Related vulnerabilities
Recent vulnerabilities recorded for tensorflow-cpu.
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