CVE-2021-37659: TensorFlow - Undefined Behavior via Null Pointer Reference in Binary Cwise Operations
Summary
CVE-2021-37659: Out of bounds read via null pointer dereference in TensorFlow. Affects tensorflow across 3 version ranges.
>= 2.3.0, < 2.3.4
>= 2.4.0, < 2.4.3
>= 2.5.0, < 2.5.1
Fixed in 2.3.4, 2.4.3 or 2.5.1, depending on the release line you run. How to fix ↓
Also tracked for
- tensorflow · PyPI
- tensorflow · PyPI
- tensorflow-cpu · PyPI
- tensorflow-gpu · PyPI
The same CVE-2021-37659 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 end-to-end open source platform for machine learning. It provides a comprehensive ecosystem for building and deploying machine learning models. TensorFlow is widely used in various industries and research domains for tasks such as image classification, natural language processing, and recommendation systems. This vulnerability affects versions 2.3.0 to 2.6.0-rc2 of TensorFlow.
Vulnerability Detail
The vulnerability (CVE-2021-37659) in TensorFlow allows an attacker to cause undefined behavior by binding a reference to a null pointer in binary cwise operations that don't require broadcasting. The implementation assumes that the two inputs have the same number of elements but does not check for this. As a result, when the eigen functor executes, it triggers out-of-bounds reads and undefined behavior due to binding to nullptr. This vulnerability can be exploited to execute arbitrary code or crash the application, leading to a denial of service (DoS) condition. The issue has been patched in TensorFlow 2.6.0 and will also be fixed in TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4.
How To Fix
Fixed versions by release line
The minimum fixed version depends on the release line you run.
-
>= 2.3.0, < 2.3.42.3.4 -
>= 2.4.0, < 2.4.32.4.3 -
>= 2.5.0, < 2.5.12.5.1
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Workaround
There is no known workaround for this vulnerability. It is recommended to apply the patch or upgrade to the fixed versions of TensorFlow as mentioned in the 'how_to_fix' section.
Conclusion
The vulnerability in TensorFlow (CVE-2021-37659) allows an attacker to cause undefined behavior by binding a reference to a null pointer in binary cwise operations. This can lead to arbitrary code execution or a denial of service (DoS) condition. It is crucial to update TensorFlow to the latest patched version or upgrade to the fixed versions to mitigate this vulnerability. For further support on vulnerability remediation, please contact DevNack.com.
See every vulnerability recorded for tensorflow →
FAQ
TensorFlow is an open source platform for machine learning that provides a comprehensive ecosystem for building and deploying machine learning models.
This vulnerability allows an attacker to cause undefined behavior in TensorFlow, potentially leading to arbitrary code execution or a denial of service (DoS) condition.
Versions 2.3.0 to 2.6.0-rc2 of TensorFlow are affected by this vulnerability.
To fix this vulnerability, update TensorFlow to the latest patched version. Upgrade to TensorFlow 2.6.0 if possible, or upgrade to the respective fixed versions (2.5.1, 2.4.3, or 2.3.4) if you are using an older version.
There is no known workaround for this vulnerability. It is recommended to apply the patch or upgrade to the fixed versions of TensorFlow.
References
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