CVE-2020-15205: TensorFlow Heap Overflow and Memory Leak Vulnerability
Summary
CVE-2020-15205: Data leak in Tensorflow. Affects tensorflow across 5 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
Fixed in 5 releases; the minimum fixed version depends on the release line you run. How to fix ↓
Also tracked for
- tensorflow · PyPI
- tensorflow-cpu · PyPI
- tensorflow-gpu · PyPI
- tensorflow · PyPI
The same CVE-2020-15205 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, academia, and industry. However, versions before 1.15.4, 2.0.3, 2.1.2, 2.2.1, and 2.3.1 are vulnerable to a critical heap overflow and memory leak issue.
Vulnerability Detail
The vulnerability (CVE-2020-15205) exists in the data_splits argument of the tf.raw_ops.StringNGrams function in TensorFlow. This argument lacks proper validation, allowing an attacker to pass malicious values that can trigger heap overflow errors and potentially leak sensitive information from the memory stack. The leaked data may include return addresses, which can be used to bypass Address Space Layout Randomization (ASLR) protections. This vulnerability can have severe consequences, including remote code execution and unauthorized access to sensitive data.
How To Fix
Fixed versions by release line
The minimum fixed version depends on the release line you run.
-
< 1.15.41.15.4 -
>= 2.0.0, < 2.0.32.0.3 -
>= 2.1.0, < 2.1.22.1.2 -
>= 2.2.0, < 2.2.12.2.1 -
>= 2.3.0, < 2.3.12.3.1
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Workaround
There is no known workaround for this vulnerability. It is essential to update TensorFlow to the patched versions mentioned above.
Conclusion
The vulnerability in TensorFlow versions before 1.15.4, 2.0.3, 2.1.2, 2.2.1, and 2.3.1 can lead to heap overflow errors and memory leaks, potentially enabling remote code execution and unauthorized access to sensitive information. It is crucial to update TensorFlow to the patched versions to mitigate this vulnerability. For further assistance and support in 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.
This vulnerability can lead to heap overflow errors and memory leaks, potentially enabling remote code execution and unauthorized access to sensitive information.
To fix this vulnerability, update TensorFlow to versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.
No, there are no known workarounds for this vulnerability. Updating TensorFlow is the recommended solution.
For more information, you can refer to the CVE-2020-15205 entry or consult the TensorFlow documentation and release notes.
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