CVE-2022-21738: Tensorflow Integer Overflow Leading To Crash Vulnerability

HIGH
Advisory Identifier: GHSA-x4qx-4fjv-hmw6
CVSS 6.5
CWE-190
Published
Advisory Summary

CVE-2022-21738 is a HIGH (CVSS 6.5) integer overflow leading to crash vulnerability (CWE-190: Integer Overflow or Wraparound) affecting Tensorflow libraries in the PyPI ecosystem. The issue involves integer overflow leading to crash in tensorflow. Remediation is available by upgrading affected packages to version 2.5.3, 2.6.3, 2.7.1.

CVE-2022-21738 at a Glance

CVE Identifier CVE-2022-21738
GHSA Identifier GHSA-x4qx-4fjv-hmw6
Severity HIGH
CVSS v3.1 Base Score 6.5
CWE Classification CWE-190: Integer Overflow or Wraparound
Affected Product Tensorflow
Package Ecosystem PyPI
Published Date
Last Updated

Security Impact

CVSS: 6.5

The security impact metrics below are parsed directly from the CVSS v3.1 vector string (CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H).

Attack Vector Network (AV:N)
Attack Complexity Low (AC:L)
Privileges Required Low (PR:L)
User Interaction None (UI:N)
Scope Unchanged (S:U)
Confidentiality None (C:N)
Integrity None (I:N)
Availability High (A:H)

How to Fix CVE-2022-21738

To remediate this vulnerability, upgrade all affected Tensorflow dependencies to a patched release. Both direct and transitive dependencies should be checked, as frameworks or security libraries may pull in vulnerable versions transitively.

tensorflow fixed: 2.5.3
pip install tensorflow>=2.5.3
tensorflow fixed: 2.6.3
pip install tensorflow>=2.6.3
tensorflow fixed: 2.7.1
pip install tensorflow>=2.7.1
tensorflow-cpu fixed: 2.5.3
pip install tensorflow-cpu>=2.5.3
tensorflow-cpu fixed: 2.6.3
pip install tensorflow-cpu>=2.6.3
tensorflow-cpu fixed: 2.7.1
pip install tensorflow-cpu>=2.7.1
tensorflow-gpu fixed: 2.5.3
pip install tensorflow-gpu>=2.5.3
tensorflow-gpu fixed: 2.6.3
pip install tensorflow-gpu>=2.6.3
tensorflow-gpu fixed: 2.7.1
pip install tensorflow-gpu>=2.7.1
Verify Direct and Transitive Dependencies

Run the following command in your project directory to verify that all resolved dependencies use the patched release:

pip show tensorflow

How to Check if You Are Affected

To determine whether your Python environment is affected by CVE-2022-21738, inspect your installed packages using pip:

pip show tensorflow

Analyze the terminal output to locate any version of Tensorflow in your dependency tree. If any resolved version matches the vulnerable ranges listed in the table below (for example, versions earlier than 2.5.3), your application is affected.

Note: The pip show tensorflow command checks currently installed packages in your active Python environment.

Technical Details

Vulnerability Mechanism & Technical Analysis

This vulnerability is classified under CWE-190: Integer Overflow or Wraparound, where the product performs a calculation that can produce an integer overflow or wraparound when the logic assumes that the resulting value will always be larger than the original value. this occurs when an integer value is incremented to a value that is too large to store in the associated representation. when this occurs, the value may become a very small or negative number. In Tensorflow, software state validation or input boundaries are circumvented during processing. Review the official source advisory statement below for specific affected components, classes, and reproduction details.

Source Advisory Statement

### Impact The [implementation of `SparseCountSparseOutput`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/count_ops.cc#L168-L273) can be made to crash a TensorFlow process by an integer overflow whose result is then used in a memory allocation: ```python import tensorflow as tf import numpy as np tf.raw_ops.SparseCountSparseOutput( indices=[[1,1]], values=[2], dense_shape=[2 ** 31, 2 ** 32], weights=[1], binary_output=True, minlength=-1, maxlength=-1, name=None) ``` ### Patches We have patched the issue in GitHub commit [6f4d3e8139ec724dbbcb40505891c81dd1052c4a](https://github.com/tensorflow/tensorflow/commit/6f4d3e8139ec724dbbcb40505891c81dd1052c4a). 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. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions. ### Attribution This vulnerability has been reported by Faysal Hossain Shezan from University of Virginia.

CVE-2022-21738 Affected Tensorflow Versions

9 component(s)
Fixed Versions:
2.5.32.6.32.7.1
Product / Package Ecosystem Affected Versions Fixed Version
tensorflow
PyPI
< 2.5.3
2.5.3
tensorflow
PyPI
≥ 2.6.0
< 2.6.3
2.6.3
tensorflow
PyPI
≥ 2.7.0
< 2.7.1
All 1 versions
2.7.0
2.7.1
tensorflow-cpu
PyPI
< 2.5.3
2.5.3
tensorflow-cpu
PyPI
≥ 2.6.0
< 2.6.3
2.6.3
tensorflow-cpu
PyPI
≥ 2.7.0
< 2.7.1
All 1 versions
2.7.0
2.7.1
tensorflow-gpu
PyPI
< 2.5.3
2.5.3
tensorflow-gpu
PyPI
≥ 2.6.0
< 2.6.3
2.6.3
tensorflow-gpu
PyPI
≥ 2.7.0
< 2.7.1
All 1 versions
2.7.0
2.7.1

References

Frequently Asked Questions

What is CVE-2022-21738?
CVE-2022-21738 is a security vulnerability in Tensorflow involving Integer overflow leading to crash in Tensorflow under CWE-190: Integer Overflow or Wraparound.
Which Tensorflow versions are affected?
Affected versions include releases prior to 2.5.3, 2.6.3, 2.7.1 across affected packages: tensorflow, tensorflow-cpu, tensorflow-gpu.
What version fixes CVE-2022-21738?
Upgrading to 2.5.3, 2.6.3, 2.7.1 (or the latest patched release for your respective branch) resolves the vulnerability.
Is tensorflow affected?
Yes, tensorflow is affected in releases prior to 2.5.3, 2.6.3, 2.7.1. Upgrade your dependency to 2.5.3, 2.6.3, 2.7.1 or later.
Is tensorflow-cpu affected?
Yes, tensorflow-cpu is affected in releases prior to 2.5.3, 2.6.3, 2.7.1. Upgrade your dependency to 2.5.3, 2.6.3, 2.7.1 or later.
What is the CVSS score of CVE-2022-21738?
CVE-2022-21738 has a CVSS v3.1 base score of 6.5 (HIGH) with vector string CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H.
What CWE is associated with CVE-2022-21738?
CVE-2022-21738 is classified under CWE-190: Integer Overflow or Wraparound (The product performs a calculation that can produce an integer overflow or wraparound when the logic assumes that the resulting value will always be larger than the original value. This occurs when an integer value is incremented to a value that is too large to store in the associated representation. When this occurs, the value may become a very small or negative number.).
How can I check PyPI dependencies for CVE-2022-21738?
Run the dependency tree command: 'pip show tensorflow'. This command lists direct and transitive dependencies in your build configuration so you can verify if a vulnerable version is resolved.
Machine-readable OSV JSON OSV v1.5 Schema
Normalized schema output
{
  "schema_version" : "1.4.0",
  "id" : "GHSA-x4qx-4fjv-hmw6",
  "modified" : "2024-11-13T22:33:01Z",
  "published" : "2022-02-09T23:45:09Z",
  "aliases" : [ "CVE-2022-21738" ],
  "summary" : "Integer overflow leading to crash in Tensorflow",
  "details" : "### Impact \nThe [implementation of `SparseCountSparseOutput`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/count_ops.cc#L168-L273) can be made to crash a TensorFlow process by an integer overflow whose result is then used in a memory allocation:\n\n```python\nimport tensorflow as tf\nimport numpy as np\n    \ntf.raw_ops.SparseCountSparseOutput(\n  indices=[[1,1]],\n  values=[2],\n  dense_shape=[2 ** 31, 2 ** 32],\n  weights=[1],\n  binary_output=True,\n  minlength=-1,\n  maxlength=-1,\n  name=None)\n```\n\n### Patches\nWe have patched the issue in GitHub commit [6f4d3e8139ec724dbbcb40505891c81dd1052c4a](https://github.com/tensorflow/tensorflow/commit/6f4d3e8139ec724dbbcb40505891c81dd1052c4a).\n\nThe 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.\n\n### For more information\nPlease consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.\n\n### Attribution\nThis vulnerability has been reported by Faysal Hossain Shezan from University of Virginia.",
  "severity" : [ {
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  "references" : [ {
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    "url" : "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x4qx-4fjv-hmw6"
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    "url" : "https://nvd.nist.gov/vuln/detail/CVE-2022-21738"
  }, {
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}