---
id: CVE-2023-25675
aliases:
  - GHSA-7x4v-9gxg-9hwj
  - BIT-tensorflow-2023-25675
  - PYSEC-2026-3131
  - PYSEC-2026-3294
  - PYSEC-2026-967
title: TensorFlow has Segfault in Bincount with XLA
summary: TensorFlow has Segfault in Bincount with XLA
severity: high
cvss: 7.5
cvssVector: 'CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H'
vendor: tensorflow
product: tensorflow
ecosystem: pip
affected:
  - tensorflow < 2.11.1
  - tensorflow-cpu < 2.11.1
  - tensorflow-gpu < 2.11.1
patched:
  - tensorflow 2.11.1
  - tensorflow-cpu 2.11.1
  - tensorflow-gpu 2.11.1
published: '2023-03-24'
updated: '2026-09-10'
sourceUpdated: '2026-09-10T03:49:52.795020507Z'
source: OSV
sourceUrl: 'https://osv.dev/vulnerability/GHSA-7x4v-9gxg-9hwj'
references:
  - url: >-
      https://github.com/tensorflow/tensorflow/security/advisories/GHSA-7x4v-9gxg-9hwj
  - url: 'https://nvd.nist.gov/vuln/detail/CVE-2023-25675'
  - url: >-
      https://github.com/tensorflow/tensorflow/commit/8ae76cf085f4be26295d2ecf2081e759e04b8acf
  - url: 'https://github.com/tensorflow/tensorflow'
tags:
  - osv
  - pip
epss: 0.00394
epssPercentile: 0.33432
ingestedAt: '2026-07-08T18:25:47.246Z'
---

## Overview

### 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


## Affected packages

- `tensorflow < 2.11.1`
- `tensorflow-cpu < 2.11.1`
- `tensorflow-gpu < 2.11.1`

## Remediation

Upgrade to a patched release:

- `tensorflow 2.11.1`
- `tensorflow-cpu 2.11.1`
- `tensorflow-gpu 2.11.1`