# CVE-2022-41900: FractionalMaxPool and FractionalAVGPool heap out-of-bounds acess in Tensorflow

> Attackers can trigger heap out-of-bounds access in FractionalMaxPool and FractionalAVGPool, leading to crashes or remote code execution.

- **Severity:** High 7.1 (`CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:H/I:H/A:H`)
- **Exploited in the wild:** Not known
- **Login needed:** Any signed-in user
- **Attackable:** Over the internet
- **Victim action needed:** A user has to click or open something
- **Fix available:** Yes
- **Published:** 18 Nov 2022
- **Updated:** 22 Apr 2025
- **Also known as:** AZL-11539, BIT-tensorflow-2022-41900, GHSA-xvwp-h6jv-7472, PYSEC-2026-1049, PYSEC-2026-3261, PYSEC-2026-3383

## What is CVE-2022-41900?

CVE-2022-41900 is a high-severity memory corruption vulnerability in Google Tensorflow, published on 18 Nov 2022. Any signed-in user can exploit it over the network, and only if a user opens a file or follows a link.

### Official description

TensorFlow is an open source platform for machine learning. The security vulnerability results in FractionalMax(AVG)Pool with illegal pooling_ratio. Attackers using Tensorflow can exploit the vulnerability. They can access heap memory which is not in the control of user, leading to a crash or remote code execution. We have patched the issue in GitHub commit 216525144ee7c910296f5b05d214ca1327c9ce48. The fix will be included in TensorFlow 2.11.0. We will also cherry pick this commit on TensorFlow 2.10.1.

Weakness: CWE-787 (Out-of-bounds Write), CWE-125 (Out-of-bounds Read)

## Which versions are affected by CVE-2022-41900?

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 | 2.8.4, 2.9.3, 2.10.1 |
| `tensorflow` | PyPI | All versions | 2.8.4, 2.9.3, 2.10.1 |
| `tensorflow` | PyPI | All versions | 2.8.4 |
| `tensorflow` | PyPI | All versions | 2.8.4 |
| `tensorflow` | PyPI | From 2.10.0 | 2.10.1 |
| `tensorflow` | PyPI | From 2.10.0 | 2.10.1 |
| `tensorflow` | PyPI | From 2.9.0 | 2.9.3 |
| `tensorflow` | PyPI | From 2.9.0 | 2.9.3 |
| `tensorflow-cpu` | PyPI | All versions | 2.8.4, 2.9.3, 2.10.1 |
| `tensorflow-cpu` | PyPI | All versions | 2.8.4 |
| `tensorflow-cpu` | PyPI | All versions | 2.8.4 |
| `tensorflow-cpu` | PyPI | From 2.10.0 | 2.10.1 |
| `tensorflow-cpu` | PyPI | From 2.10.0 | 2.10.1 |
| `tensorflow-cpu` | PyPI | From 2.9.0 | 2.9.3 |
| `tensorflow-cpu` | PyPI | From 2.9.0 | 2.9.3 |
| `tensorflow-gpu` | PyPI | All versions | 2.8.4, 2.9.3, 2.10.1 |
| `tensorflow-gpu` | PyPI | All versions | 2.8.4 |
| `tensorflow-gpu` | PyPI | All versions | 2.8.4 |
| `tensorflow-gpu` | PyPI | From 2.10.0 | 2.10.1 |
| `tensorflow-gpu` | PyPI | From 2.10.0 | 2.10.1 |
| `tensorflow-gpu` | PyPI | From 2.9.0 | 2.9.3 |
| `tensorflow-gpu` | PyPI | From 2.9.0 | 2.9.3 |

Products: Google Tensorflow.

## How do I fix CVE-2022-41900?

Upgrade tensorflow to a fixed version for your release line: 2.8.4, 2.9.3 or 2.10.1.

## Is CVE-2022-41900 being exploited?

It is not confirmed as exploited in the wild, but public exploit code for CVE-2022-41900 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-2022-41900 and fix it if it is affected.

What it is: CVE-2022-41900 is a high-severity memory corruption vulnerability in Google Tensorflow, published on 18 Nov 2022. Any signed-in user can exploit it over the network, and only if a user opens a file or follows a link.
Exploitation: It is not confirmed as exploited in the wild, but public exploit code for CVE-2022-41900 exists.

Affected packages and fixed versions:
- tensorflow (Bitnami): affected all versions; fixed in 2.8.4, 2.9.3, 2.10.1
- tensorflow (PyPI): affected all versions; fixed in 2.8.4, 2.9.3, 2.10.1
- tensorflow (PyPI): affected all versions; fixed in 2.8.4
- tensorflow (PyPI): affected all versions; fixed in 2.8.4
- tensorflow (PyPI): affected from 2.10.0; fixed in 2.10.1
- tensorflow (PyPI): affected from 2.10.0; fixed in 2.10.1
- tensorflow (PyPI): affected from 2.9.0; fixed in 2.9.3
- tensorflow (PyPI): affected from 2.9.0; fixed in 2.9.3
- tensorflow-cpu (PyPI): affected all versions; fixed in 2.8.4, 2.9.3, 2.10.1
- tensorflow-cpu (PyPI): affected all versions; fixed in 2.8.4
- tensorflow-cpu (PyPI): affected all versions; fixed in 2.8.4
- tensorflow-cpu (PyPI): affected from 2.10.0; fixed in 2.10.1

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-2022-41900/ (Markdown: https://insights.sbomify.com/CVE-2022-41900/index.md)
```

## Sources

- CVE record: https://www.cve.org/CVERecord?id=CVE-2022-41900
- NVD: https://nvd.nist.gov/vuln/detail/CVE-2022-41900
- OSV: https://osv.dev/vulnerability/CVE-2022-41900

---
From sbomify Insights: https://insights.sbomify.com/CVE-2022-41900/
Summaries are generated and may contain mistakes; the official description above is the record.
