# CVE-2022-21731: Type confusion leading to segfault in Tensorflow

> A type confusion in TensorFlow's ConcatV2 shape inference allows attackers to trigger a segmentation fault, causing a denial of service.

- **Severity:** Medium 6.5 (`CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H`)
- **Exploited in the wild:** Not known
- **Login needed:** Any signed-in user
- **Attackable:** Over the internet
- **Victim action needed:** Not needed
- **Fix available:** Yes
- **Published:** 3 Feb 2022
- **Updated:** 5 May 2025
- **Also known as:** BIT-tensorflow-2022-21731, GHSA-m4hf-j54p-p353, PYSEC-2022-110, PYSEC-2022-55, PYSEC-2026-3211

## What is CVE-2022-21731?

CVE-2022-21731 is a medium-severity denial of service vulnerability in Google Tensorflow, published on 3 Feb 2022. Any signed-in user can exploit it over the network, with no action from the victim.

### Official description

Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `ConcatV2` can be used to trigger a denial of service attack via a segfault caused by a type confusion. The `axis` argument is translated into `concat_dim` in the `ConcatShapeHelper` helper function. Then, a value for `min_rank` is computed based on `concat_dim`. This is then used to validate that the `values` tensor has at least the required rank. However, `WithRankAtLeast` receives the lower bound as a 64-bits value and then compares it against the maximum 32-bits integer value that could be represented. Due to the fact that `min_rank` is a 32-bits value and the value of `axis`, the `rank` argument is a negative value, so the error check is bypassed. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Weakness: CWE-843 (Access of Resource Using Incompatible Type)

## Which versions are affected by CVE-2022-21731?

22 open source packages ship an affected version, including tensorflow, tensorflow-cpu and tensorflow-gpu. It affects 1 product.


| Package | Ecosystem | Affected | Fixed in |
| --- | --- | --- | --- |
| `tensorflow` | Bitnami | All versions | 2.5.3, 2.6.3, 2.7.1 |
| `tensorflow` | PyPI | All versions | 2.5.3, 2.6.3, 2.7.1 |
| `tensorflow` | PyPI | All versions | 2.5.3 |
| `tensorflow` | PyPI | All versions | 2.5.3 |
| `tensorflow` | PyPI | From 2.6.0 | 2.6.3 |
| `tensorflow` | PyPI | From 2.6.0 | 2.6.3 |
| `tensorflow` | PyPI | From 2.7.0 | 2.7.1 |
| `tensorflow` | PyPI | From 2.7.0 | 2.7.1 |
| `tensorflow-cpu` | PyPI | All versions | 2.5.3, 2.6.3 |
| `tensorflow-cpu` | PyPI | All versions | 2.5.3 |
| `tensorflow-cpu` | PyPI | All versions | 2.5.3 |
| `tensorflow-cpu` | PyPI | From 2.6.0 | 2.6.3 |
| `tensorflow-cpu` | PyPI | From 2.6.0 | 2.6.3 |
| `tensorflow-cpu` | PyPI | From 2.7.0 | 2.7.1 |
| `tensorflow-cpu` | PyPI | From 2.7.0 | 2.7.1 |
| `tensorflow-gpu` | PyPI | All versions | 2.5.3, 2.6.3 |
| `tensorflow-gpu` | PyPI | All versions | 2.5.3 |
| `tensorflow-gpu` | PyPI | All versions | 2.5.3 |
| `tensorflow-gpu` | PyPI | From 2.6.0 | 2.6.3 |
| `tensorflow-gpu` | PyPI | From 2.6.0 | 2.6.3 |
| `tensorflow-gpu` | PyPI | From 2.7.0 | 2.7.1 |
| `tensorflow-gpu` | PyPI | From 2.7.0 | 2.7.1 |

Products: Google Tensorflow.

## How do I fix CVE-2022-21731?

Upgrade tensorflow to a fixed version for your release line: 2.5.3, 2.6.3 or 2.7.1.

## Is CVE-2022-21731 being exploited?

It is not confirmed as exploited in the wild, but public exploit code for CVE-2022-21731 exists.

## Other vulnerabilities in Google Tensorflow

- [CVE-2023-25668](https://insights.sbomify.com/CVE-2023-25668/): TensorFlow vulnerable to heap out-of-buffer read in the QuantizeAndDequantize operation (critical 9.8)
- [CVE-2018-7575](https://insights.sbomify.com/CVE-2018-7575/): Integer Overflow or Wraparound in Google TensorFlow (critical 9.8)
- [CVE-2021-37678](https://insights.sbomify.com/CVE-2021-37678/): Arbitrary code execution due to YAML deserialization (critical 9.3)
- [CVE-2021-35958](https://insights.sbomify.com/CVE-2021-35958/): Path traversal in n/a (critical 9.1)
- [CVE-2020-15202](https://insights.sbomify.com/CVE-2020-15202/): Integer truncation in Shard API usage (critical 9.0)

## Fix prompt for AI coding agents

```text
Check this codebase for CVE-2022-21731 and fix it if it is affected.

What it is: CVE-2022-21731 is a medium-severity denial of service vulnerability in Google Tensorflow, published on 3 Feb 2022. Any signed-in user can exploit it over the network, with no action from the victim.
Exploitation: It is not confirmed as exploited in the wild, but public exploit code for CVE-2022-21731 exists.

Affected packages and fixed versions:
- tensorflow (Bitnami): affected all versions; fixed in 2.5.3, 2.6.3, 2.7.1
- tensorflow (PyPI): affected all versions; fixed in 2.5.3, 2.6.3, 2.7.1
- tensorflow (PyPI): affected all versions; fixed in 2.5.3
- tensorflow (PyPI): affected all versions; fixed in 2.5.3
- tensorflow (PyPI): affected from 2.6.0; fixed in 2.6.3
- tensorflow (PyPI): affected from 2.6.0; fixed in 2.6.3
- tensorflow (PyPI): affected from 2.7.0; fixed in 2.7.1
- tensorflow (PyPI): affected from 2.7.0; fixed in 2.7.1
- tensorflow-cpu (PyPI): affected all versions; fixed in 2.5.3, 2.6.3
- tensorflow-cpu (PyPI): affected all versions; fixed in 2.5.3
- tensorflow-cpu (PyPI): affected all versions; fixed in 2.5.3
- tensorflow-cpu (PyPI): affected from 2.6.0; fixed in 2.6.3

Task:
1. Search the dependency manifests and lockfiles (for example package.json, package-lock.json, requirements.txt, poetry.lock, uv.lock, pom.xml, build.gradle, go.mod, Cargo.lock, Gemfile.lock) and any Dockerfiles for the affected packages, including transitive dependencies.
2. If an affected version is in use, upgrade it to the fixed version for its release line with the project's package manager, so the lockfile is regenerated. Prefer the smallest upgrade that fixes it.
3. If there is no fix, or the upgrade would break the build, do not guess: explain the risk and the safest workaround instead.
4. Run the tests and summarise what changed and why.
5. If nothing in the project is affected, say so and change nothing.

Reference: https://insights.sbomify.com/CVE-2022-21731/ (Markdown: https://insights.sbomify.com/CVE-2022-21731/index.md)
```

## Sources

- CVE record: https://www.cve.org/CVERecord?id=CVE-2022-21731
- NVD: https://nvd.nist.gov/vuln/detail/CVE-2022-21731
- OSV: https://osv.dev/vulnerability/CVE-2022-21731

---
From sbomify Insights: https://insights.sbomify.com/CVE-2022-21731/
Summaries are generated and may contain mistakes; the official description above is the record.
