---
id: CVE-2021-41198
aliases:
  - GHSA-2p25-55c9-h58q
  - BIT-tensorflow-2021-41198
  - PYSEC-2021-391
  - PYSEC-2021-608
  - PYSEC-2021-806
title: Overflow/crash in `tf.tile` when tiling tensor is large
summary: Overflow/crash in `tf.tile` when tiling tensor is large
severity: medium
cvss: 5.5
cvssVector: 'CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H'
vendor: tensorflow
product: tensorflow
ecosystem: pip
affected:
  - 'tensorflow >= 2.6.0, < 2.6.1'
  - 'tensorflow >= 2.5.0, < 2.5.2'
  - tensorflow < 2.4.4
  - 'tensorflow-cpu >= 2.6.0, < 2.6.1'
  - 'tensorflow-cpu >= 2.5.0, < 2.5.2'
  - tensorflow-cpu < 2.4.4
  - 'tensorflow-gpu >= 2.6.0, < 2.6.1'
  - 'tensorflow-gpu >= 2.5.0, < 2.5.2'
  - tensorflow-gpu < 2.4.4
patched:
  - tensorflow 2.6.1
  - tensorflow 2.5.2
  - tensorflow 2.4.4
  - tensorflow-cpu 2.6.1
  - tensorflow-cpu 2.5.2
  - tensorflow-cpu 2.4.4
  - tensorflow-gpu 2.6.1
  - tensorflow-gpu 2.5.2
  - tensorflow-gpu 2.4.4
published: '2021-11-10'
updated: '2026-07-08'
source: OSV
sourceUrl: 'https://osv.dev/vulnerability/GHSA-2p25-55c9-h58q'
references:
  - url: >-
      https://github.com/tensorflow/tensorflow/security/advisories/GHSA-2p25-55c9-h58q
  - url: 'https://nvd.nist.gov/vuln/detail/CVE-2021-41198'
  - url: 'https://github.com/tensorflow/tensorflow/issues/46911'
  - url: >-
      https://github.com/tensorflow/tensorflow/commit/9294094df6fea79271778eb7e7ae1bad8b5ef98f
  - url: >-
      https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-608.yaml
  - url: >-
      https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-806.yaml
  - url: >-
      https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-391.yaml
  - url: 'https://github.com/tensorflow/tensorflow'
tags:
  - osv
  - pip
epss: 0.00238
epssPercentile: 0.15071
ingestedAt: '2026-07-08T18:25:44.581Z'
---

## Overview

### Impact
If `tf.tile` is called with a large input argument then the TensorFlow process will crash due to a `CHECK`-failure caused by an overflow.

```python
import tensorflow as tf
import numpy as np
tf.keras.backend.tile(x=np.ones((1,1,1)), n=[100000000,100000000, 100000000])
```

The number of elements in the output tensor is too much for the `int64_t` type and the overflow is detected via a `CHECK` statement. This aborts the process.

### Patches
We have patched the issue in GitHub commit [9294094df6fea79271778eb7e7ae1bad8b5ef98f](https://github.com/tensorflow/tensorflow/commit/9294094df6fea79271778eb7e7ae1bad8b5ef98f) (merging [#51138](https://github.com/tensorflow/tensorflow/pull/51138)).

The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.

### 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 externally via a [GitHub issue](https://github.com/tensorflow/tensorflow/issues/46911).

## Affected packages

- `tensorflow >= 2.6.0, < 2.6.1`
- `tensorflow >= 2.5.0, < 2.5.2`
- `tensorflow < 2.4.4`
- `tensorflow-cpu >= 2.6.0, < 2.6.1`
- `tensorflow-cpu >= 2.5.0, < 2.5.2`
- `tensorflow-cpu < 2.4.4`
- `tensorflow-gpu >= 2.6.0, < 2.6.1`
- `tensorflow-gpu >= 2.5.0, < 2.5.2`
- `tensorflow-gpu < 2.4.4`

## Remediation

Upgrade to a patched release:

- `tensorflow 2.6.1`
- `tensorflow 2.5.2`
- `tensorflow 2.4.4`
- `tensorflow-cpu 2.6.1`
- `tensorflow-cpu 2.5.2`
- `tensorflow-cpu 2.4.4`
- `tensorflow-gpu 2.6.1`
- `tensorflow-gpu 2.5.2`
- `tensorflow-gpu 2.4.4`