CVE-2023-25669
TensorFlow has Floating Point Exception in AvgPoolGrad with XLA
Impact
### Impact If the stride and window size are not positive for `tf.raw_ops.AvgPoolGrad`, it can give an FPE. ```python import tensorflow as tf import numpy as np @tf.function(jit_compile=True) def test(): y = tf.raw_ops.AvgPoolGrad(orig_input_shape=[1,0,0,0], grad=[[[[0.39117979]]]], ksize=[1,0,0,0], strides=[1,0,0,0], padding="SAME", data_format="NCHW") return y print(test()) ``` ### Patches We have patched the issue in GitHub commit [1295ae4dbb52fe06b19733b0257e2340d7b63b8d](https://github.com/tensorflow/tensorflow/commit/1295ae4dbb52fe06b19733b0257e2340d7b63b8d). The fix will be included in TensorFlow 2.12. We will also cherrypick this commit on TensorFlow 2.11.1. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions. ### Attribution This vulnerability has been reported by r3pwnx of 360 AIVul Team
Affected packages
| Ecosystem | Package | Affected | Fixed in |
|---|---|---|---|
| pip | tensorflow | < 2.11.1 | 2.11.1 |
| pip | tensorflow-cpu | < 2.11.1 | 2.11.1 |
| pip | tensorflow-gpu | < 2.11.1 | 2.11.1 |
Affected products
| Vendor | Product | Affected versions |
|---|---|---|
| Tensorflow | before 2.12.0 |
Weakness classification
References
- NVD record
- CVE.org record
- GitHub advisory
- https://github.com/tensorflow/tensorflow/commit/1295ae4dbb52fe06b19733b0257e2340d7b63b8d
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rcf8-g8jv-vg6p
- https://github.com/advisories/GHSA-rcf8-g8jv-vg6p
- https://nvd.nist.gov/vuln/detail/CVE-2023-25669