CVE-2021-29559: TensorFlow - Out-of-Bounds Heap Access in tf.raw_ops.UnicodeEncode
Summary
CVE-2021-29559: Heap OOB access in unicode ops. 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-2021-29559 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 developing and deploying machine learning models. TensorFlow is widely used in various industries and research fields.
Vulnerability Detail
The vulnerability (CVE-2021-29559) in TensorFlow allows an attacker to access data outside the bounds of a heap-allocated array in the tf.raw_ops.UnicodeEncode function. This vulnerability arises from the assumption made in the implementation that the input_value/input_splits pair specifies a valid sparse tensor. As a result, an attacker can exploit this vulnerability to read sensitive data or execute arbitrary code. The impact of this vulnerability is considered high.
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
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Workaround
There is no known workaround for this vulnerability at the moment.
Conclusion
The vulnerability in TensorFlow (CVE-2021-29559) allows an attacker to access data outside the bounds of a heap-allocated array. This can lead to unauthorized access to sensitive information or the execution of arbitrary code. It is crucial to update to the latest patched version of TensorFlow 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 developing and deploying machine learning models.
The impact of this vulnerability is considered high, as it allows an attacker to access data outside the bounds of a heap-allocated array and potentially read sensitive information or execute arbitrary code.
The vulnerability affects TensorFlow versions 2.1.4, 2.2.3, 2.3.3, and 2.4.2. The fix will be included in TensorFlow 2.5.0.
No, there is currently no known workaround for this vulnerability.
To mitigate this vulnerability, it is recommended to update to the latest patched version of TensorFlow once it becomes available.
References
Related vulnerabilities
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