In Tensorflow before version 2.3.1, the `RaggedCountSparseOutput` implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the `splits` tensor generate a valid partitioning of the `values` tensor. Hence, the code is prone to heap buffer overflow. If `split_values` does not end with a value at least `num_values` then the `while` loop condition will trigger a read outside of the bounds of `split_values` once `batch_idx` grows too large. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.
The product receives input or data, but it does not validate or incorrectly validates that the input has the properties that are required to process the data safely and correctly.
The product writes data past the end, or before the beginning, of the intended buffer.
| Link | Tags |
|---|---|
| https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1 | third party advisory |
| https://github.com/tensorflow/tensorflow/commit/3cbb917b4714766030b28eba9fb41bb97ce9ee02 | third party advisory patch |
| https://github.com/tensorflow/tensorflow/security/advisories/GHSA-p5f8-gfw5-33w4 | third party advisory exploit |