CVE-2023-25675
TensorFlow has Segfault in Bincount with XLA
Description
### Impact When running with XLA, `tf.raw_ops.Bincount` segfaults when given a parameter `weights` that is neither the same shape as parameter `arr` nor a length-0 tensor. ```python import tensorflow as tf func = tf.raw_ops.Bincount para={'arr': 6, 'size': 804, 'weights': [52, 351]} @tf.function(jit_compile=True) def fuzz_jit(): y = func(**para) return y print(fuzz_jit()) ``` ### Patches We have patched the issue in GitHub commit [8ae76cf085f4be26295d2ecf2081e759e04b8acf](https://github.com/tensorflow/tensorflow/commit/8ae76cf085f4be26295d2ecf2081e759e04b8acf). 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
How to fix CVE-2023-25675
To remediate CVE-2023-25675, upgrade the affected package to a fixed version below.
- —upgrade to 2.12.0 or later
- —upgrade to 2.11.1 or later
- —upgrade to 2.11.1 or later
- —upgrade to 2.11.1 or later
Is CVE-2023-25675 being exploited?
Low — EPSS is 0.2%, meaning exploitation activity has not been observed at scale.
Affected packages (4)
- from 0, < 2.12.0
- from 0, < 2.11.1
- from 0, < 2.11.1
- from 0, < 2.11.1
CVSS scores
| Source | Version | Severity | Vector |
|---|---|---|---|
| osv | CVSS 3.1 | HIGH7.5 | CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H |