Vulnerabilities > CVE-2022-21730 - Out-of-bounds Read vulnerability in Google Tensorflow
Attack vector
NETWORK Attack complexity
LOW Privileges required
LOW Confidentiality impact
HIGH Integrity impact
NONE Availability impact
HIGH Summary
Tensorflow is an Open Source Machine Learning Framework. The implementation of `FractionalAvgPoolGrad` does not consider cases where the input tensors are invalid allowing an attacker to read from outside of bounds of heap. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Vulnerable Configurations
Common Weakness Enumeration (CWE)
Common Attack Pattern Enumeration and Classification (CAPEC)
- Overread Buffers An adversary attacks a target by providing input that causes an application to read beyond the boundary of a defined buffer. This typically occurs when a value influencing where to start or stop reading is set to reflect positions outside of the valid memory location of the buffer. This type of attack may result in exposure of sensitive information, a system crash, or arbitrary code execution.
References
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-vjg4-v33c-ggc4
- https://github.com/tensorflow/tensorflow/commit/002408c3696b173863228223d535f9de72a101a9
- https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/fractional_avg_pool_op.cc#L209-L360