Dmc1778

**Name of the Vulnerable Software and Affected Versions** TensorFlow versions prior to 2.13 TensorFlow versions 2.12 and earlier **Description** The issue is caused by `array ops.upper bound` when not given a rank 2 tensor, resulting in a segfault. The estimated number of potentially affected devices worldwide is not provided. There is no information about real-world incidents where this issue was exploited. Technical details about exploitation include: - `array ops.upper bound` causes a segfault when not given a rank 2 tensor. **Recommendations** For TensorFlow versions prior to 2.13, update to version 2.13 or later to resolve the issue. For TensorFlow versions 2.12 and earlier, update to version 2.12.1 or later to resolve the issue. As a temporary workaround, consider avoiding the use of `array ops.upper bound` with tensors that are not rank 2 until a patch is available.

**Name of the Vulnerable Software and Affected Versions** TensorFlow versions prior to 2.12.0 and 2.11.1 **Description** The issue concerns the `nn ops.fractional avg pool v2` and `nn ops.fractional max pool v2` functions, which require the first and fourth elements of their `pooling ratio` parameter to be equal to 1.0, as pooling on batch and channel dimensions is not supported. **Recommendations** For versions prior to 2.12.0, update to version 2.12.0 to resolve the issue. For versions prior to 2.11.1, update to version 2.11.1 to resolve the issue. As a temporary workaround, consider restricting the use of the `nn ops.fractional avg pool v2` and `nn ops.fractional max pool v2` functions until a patch is available, by ensuring the first and fourth elements of the `pooling ratio` parameter are set to 1.0.