CVE-2022-21731 — Type confusion leading to segfault in Tensorflow

Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `ConcatV2` can be used to trigger a denial of service attack via a segfault caused by a type confusion. The `axis` argument is translated into `concat_dim` in the `ConcatShapeHelper` helper function. Then, a value for `min_rank` is computed based on `concat_dim`. This is then used to validate that the `values` tensor has at least the required rank. However, `WithRankAtLeast` receives the lower bound as a 64-bits value and then compares it against the maximum 32-bits integer value that could be represented. Due to the fact that `min_rank` is a 32-bits value and the value of `axis`, the `rank` argument is a negative value, so the error check is bypassed. 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.

GHSA-m4hf-j54p-p353 — Type confusion leading to segfault in Tensorflow

Affected: PyPI: tensorflow, PyPI: tensorflow-cpu, PyPI: tensorflow-gpu

### Impact The [implementation of shape inference for `ConcatV2`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/framework/common_shape_fns.cc#L1961-L2059) can be used to trigger a denial of service attack via a segfault caused by a type confusion:

```python import tensorflow as tf

@tf.function def test(): y = tf.raw_ops.ConcatV2( values=[[1,2,3],[4,5,6]], axis = 0xb500005b) return y

test() ```

The `axis` argument is translated into `concat_dim` in the `ConcatShapeHelper` helper function. Then, a value for `min_rank` is computed based on `concat_dim`. This is then used to validate that the `values` tensor has at least the required rank:

```cc int64_t concat_dim; if (concat_dim_t->dtype() == DT_INT32) { concat_dim = static_cast<int64_t>(concat_dim_t->flat<int32>()(0)); } else { concat_dim = concat_dim_t->flat<int64_t>()(0); }

// Minimum required number of dimensions. const int min_rank = concat_dim < 0 ? -concat_dim : concat_dim + 1;

// ... ShapeHandle input = c->input(end_value_index - 1); TF_RETURN_IF_ERROR(c->WithRankAtLeast(input, min_rank, &input)); ```

However, [`WithRankAtLeast`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/framework/shape_inference.cc#L345-L358) receives the lower bound as a 64-bits value and then compares it against the maximum 32-bits integer value that could be represented:

```cc Status In…

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CVE-2022-21731 — Type confusion leading to segfault in Tensorflow

GHSA-m4hf-j54p-p353 — Type confusion leading to segfault in Tensorflow