CVE-2022-23585: Tensorflow Memory Leak Vulnerability

MODERATE
Advisory Identifier: GHSA-fq6p-6334-8gr4
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CVSS 4.3
CWE-401
Published
Advisory Summary

CVE-2022-23585 is a MODERATE (CVSS 4.3) memory leak vulnerability (CWE-401: Missing Release of Memory after Effective Lifetime) affecting Tensorflow libraries in the PyPI ecosystem. The issue involves memory leak in decoding png images. Remediation is available by upgrading affected packages to version 2.5.3, 2.6.3, 2.7.1.

CVE-2022-23585 at a Glance

CVE Identifier CVE-2022-23585
GHSA Identifier GHSA-fq6p-6334-8gr4
Severity MODERATE
CVSS v3.1 Base Score 4.3
CWE Classification CWE-401: Missing Release of Memory after Effective Lifetime
Affected Product Tensorflow
Package Ecosystem PyPI
Published Date
Last Updated

Security Impact

CVSS: 4.3

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:L).

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 Low (A:L)

How to Fix CVE-2022-23585

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-2022-23585, 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-401: Missing Release of Memory after Effective Lifetime, where the product does not sufficiently track and release allocated memory after it has been used, making the memory unavailable for reallocation and reuse. 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 When [decoding PNG images](https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/kernels/image/decode_image_op.cc#L322-L416) TensorFlow can produce a memory leak if the image is invalid. After calling `png::CommonInitDecode(..., &decode)`, the `decode` value contains allocated buffers which can only be freed by calling `png::CommonFreeDecode(&decode)`. However, several error case in the function implementation invoke the `OP_REQUIRES` macro which immediately terminates the execution of the function, without allowing for the memory free to occur. ### Patches We have patched the issue in GitHub commit [ab51e5b813573dc9f51efa335aebcf2994125ee9](https://github.com/tensorflow/tensorflow/commit/ab51e5b813573dc9f51efa335aebcf2994125ee9). 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.

CVE-2022-23585 Affected Tensorflow Versions

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

References

GitHub Advisory / Wiki ADVISORY
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-fq6p-6334-8gr4
NVD — CVE-2022-23585 NVD
https://nvd.nist.gov/vuln/detail/CVE-2022-23585
Security Fix Commit FIX COMMIT
https://github.com/tensorflow/tensorflow/commit/ab51e5b813573dc9f51efa335aebcf2994125ee9
Tensorflow Source Repository REPOSITORY
https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-94.yaml
Tensorflow Source Repository REPOSITORY
https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-149.yaml
Tensorflow Source Repository REPOSITORY
https://github.com/tensorflow/tensorflow
Tensorflow Source Repository REPOSITORY
https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/kernels/image/decode_image_op.cc#L322-L416

Frequently Asked Questions

What is CVE-2022-23585?
CVE-2022-23585 is a security vulnerability in Tensorflow involving Memory leak in decoding PNG images under CWE-401: Missing Release of Memory after Effective Lifetime.
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-2022-23585?
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-2022-23585?
CVE-2022-23585 has a CVSS v3.1 base score of 4.3 (MODERATE) with vector string CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L.
What CWE is associated with CVE-2022-23585?
CVE-2022-23585 is classified under CWE-401: Missing Release of Memory after Effective Lifetime (The product does not sufficiently track and release allocated memory after it has been used, making the memory unavailable for reallocation and reuse.).
How can I check PyPI dependencies for CVE-2022-23585?
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
View Raw JSON 
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  "id" : "GHSA-fq6p-6334-8gr4",
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  "published" : "2022-02-09T23:26:08Z",
  "aliases" : [ "CVE-2022-23585" ],
  "summary" : "Memory leak in decoding PNG images",
  "details" : "### Impact\nWhen [decoding PNG images](https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/kernels/image/decode_image_op.cc#L322-L416) TensorFlow can produce a memory leak if the image is invalid.\nAfter calling `png::CommonInitDecode(..., &decode)`, the `decode` value contains allocated buffers which can only be freed by calling `png::CommonFreeDecode(&decode)`. However, several error case in the function implementation invoke the `OP_REQUIRES` macro which immediately terminates the execution of the function, without allowing for the memory free to occur.\n  \n### Patches   \nWe have patched the issue in GitHub commit [ab51e5b813573dc9f51efa335aebcf2994125ee9](https://github.com/tensorflow/tensorflow/commit/ab51e5b813573dc9f51efa335aebcf2994125ee9).\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.",
  "severity" : [ {
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