CVE-2021-29606: TensorFlow Out-of-Bounds Read Vulnerability
Summary
CVE-2021-29606: Heap OOB read in TFLite. Affects tensorflow across 4 version ranges.
< 2.1.4
>= 2.2.0, < 2.2.3
>= 2.3.0, < 2.3.3
>= 2.4.0, < 2.4.2
Fixed in 4 releases; the minimum fixed version depends 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-2021-29606 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 of tools, libraries, and resources for developing and deploying machine learning models. TensorFlow is widely used in various industries and research fields.
Vulnerability Detail
A vulnerability has been discovered in TensorFlow that could allow an attacker to trigger an out-of-bounds read on the heap. This vulnerability exists in the TFLite implementation of the Split_V function. If a specially crafted TFLite model is used with an axis_value that is not within the valid range, the SizeOfDimension function will access data outside the bounds of the tensor shape array. This can lead to information disclosure or potential crashes, depending on the specific use case.
How To Fix
Fixed versions by release line
The minimum fixed version depends on the release line you run.
-
< 2.1.42.1.4 -
>= 2.2.0, < 2.2.32.2.3 -
>= 2.3.0, < 2.3.32.3.3 -
>= 2.4.0, < 2.4.22.4.2
Tip — Not sure which release line you're on? Vulert can find the fix for the version you are using. Scan free →
Workaround
There is no known workaround for this vulnerability. It is recommended to apply the provided fix by updating to the patched versions of TensorFlow.
Conclusion
The discovered vulnerability in TensorFlow could allow an attacker to trigger an out-of-bounds read on the heap, potentially leading to information disclosure or crashes. It is crucial to update to the patched versions of TensorFlow to mitigate this vulnerability. For further support on vulnerability remediation, you can reach out to DevNack.com.
See every vulnerability recorded for tensorflow →
FAQ
TensorFlow is an open source platform for machine learning that provides tools and libraries for developing and deploying machine learning models.
This vulnerability could allow an attacker to trigger an out-of-bounds read on the heap, potentially leading to information disclosure or crashes.
The vulnerability affects TensorFlow versions 0 and 2.1.4 to 2.4.2. It has been fixed in TensorFlow 2.5.0 and backported to TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3, and TensorFlow 2.1.4.
No, there is no known workaround. It is recommended to update to the patched versions of TensorFlow.
For more information about this vulnerability, you can refer to the official TensorFlow documentation or contact the TensorFlow development team.
References
Related vulnerabilities
Recent vulnerabilities recorded for tensorflow.
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