CVE-2021-37681

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Summary

CVECVE-2021-37681
StatePUBLIC
Assigner[email protected]
Source PriorityCVE Program / NVD first with legacy fallback
Published2021-08-12 22:15:00 UTC
Updated2021-08-18 20:38:00 UTC
DescriptionTensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of SVDF in TFLite is [vulnerable to a null pointer error](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/svdf.cc#L300-L313). The [`GetVariableInput` function](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/kernel_util.cc#L115-L119) can return a null pointer but `GetTensorData` assumes that the argument is always a valid tensor. Furthermore, because `GetVariableInput` calls [`GetMutableInput`](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/kernel_util.cc#L82-L90) which might return `nullptr`, the `tensor->is_variable` expression can also trigger a null pointer exception. We have patched the issue in GitHub commit 5b048e87e4e55990dae6b547add4dae59f4e1c76. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

Risk And Classification

Problem Types: CWE-476

NVD Known Affected Configurations (CPE 2.3)

TypeVendorProductVersionUpdateEditionLanguage
Application Google Tensorflow All All All All
Application Google Tensorflow 2.5.0 All All All
Application Google Tensorflow 2.6.0 rc0 All All
Application Google Tensorflow 2.6.0 rc1 All All
Application Google Tensorflow 2.6.0 rc2 All All

References

ReferenceSourceLinkTags
Fix a null pointer exception in SVDF · tensorflow/tensorflow@5b048e8 · GitHub MISC github.com
NPE in TFLite · Advisory · tensorflow/tensorflow · GitHub CONFIRM github.com
CVE Program record CVE.ORG www.cve.org canonical
NVD vulnerability detail NVD nvd.nist.gov canonical, analysis

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