Integer overflow in TFLite
Vulnerability Description
Tensorflow is an Open Source Machine Learning Framework. An attacker can craft a TFLite model that would cause an integer overflow in embedding lookup operations. Both `embedding_size` and `lookup_size` are products of values provided by the user. Hence, a malicious user could trigger overflows in the multiplication. In certain scenarios, this can then result in heap OOB read/write. Users are advised to upgrade to a patched version.
Impact Analysis
Refer to official advisory for detailed impact metrics.
Remediation
Ensure systems are updated to the latest vendor-supplied patch levels.
Am I Vulnerable?
Launch our assessment wizard to check if your infrastructure is exposed to • CVE-2022-23559
Credits & Attribution
No credits recorded in the NVD database.
References
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-98p5-x8x4-c9m5
- https://github.com/tensorflow/tensorflow/commit/1de49725a5fc4e48f1a3b902ec3599ee99283043
- https://github.com/tensorflow/tensorflow/commit/a4e401da71458d253b05e41f28637b65baf64be4
- https://github.com/tensorflow/tensorflow/commit/f19be71717c497723ba0cea0379e84f061a75e01
- https://github.com/tensorflow/tensorflow/blob/ca6f96b62ad84207fbec580404eaa7dd7403a550/tensorflow/lite/kernels/embedding_lookup_sparse.cc#L179-L189
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