How severe is CVE-2022-41889?

CVE-2022-41889 has a CVSS 3.x base score of 5.5, rated medium severity. It is exploitable over local access with low attack complexity, requires low privileges and no user interaction. Impact on confidentiality is none, integrity none, and availability high.

Is CVE-2022-41889 being actively exploited?

It is not currently listed in CISA's KEV catalog. Its EPSS exploit-prediction score is 0% (32nd percentile), an estimate of the probability of exploitation in the next 30 days.

What products are affected by CVE-2022-41889?

CVE-2022-41889 affects Google Tensorflow. See the affected-products list for the exact vulnerable versions.

How do I fix CVE-2022-41889?

Review the linked vendor and NVD advisories for patched versions and mitigations, then upgrade or apply the recommended workaround.

When was CVE-2022-41889 published?

CVE-2022-41889 was published on 2022-11-18 and last updated on 2026-06-17.

CVE-2022-41889

CVE-2022-41889 is a medium-severity vulnerability in Google Tensorflow with a CVSS 3.x base score of 5.5. It is not currently listed as actively exploited by CISA, and its EPSS exploit-prediction score is low. The underlying weakness is classified as CWE-476.

Key facts

Severity: Medium (CVSS 3.x base score 5.5)
EPSS exploit prediction: 0% (32nd percentile)
Actively exploited: Not listed in CISA KEV
Weakness: CWE-476
Affected product: Google Tensorflow
Published: 2022-11-18
Last modified: 2026-06-17

Description

TensorFlow is an open source platform for machine learning. If a list of quantized tensors is assigned to an attribute, the pywrap code fails to parse the tensor and returns a `nullptr`, which is not caught. An example can be seen in `tf.compat.v1.extract_volume_patches` by passing in quantized tensors as input `ksizes`. We have patched the issue in GitHub commit e9e95553e5411834d215e6770c81a83a3d0866ce. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.

Frequently asked questions

What is CVE-2022-41889?: TensorFlow is an open source platform for machine learning. If a list of quantized tensors is assigned to an attribute, the pywrap code fails to parse the tensor and returns a `nullptr`, which is not caught. An example can be seen in `tf.compat.v1.extract_volume_patches` by passing in quantized tensors as input `ksizes`. We have patched the issue in GitHub commit e9e95553e5411834d215e6770c81a83a3d0866ce. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.
How severe is CVE-2022-41889?: CVE-2022-41889 has a CVSS 3.x base score of 5.5, rated medium severity. It is exploitable over local access with low attack complexity, requires low privileges and no user interaction. Impact on confidentiality is none, integrity none, and availability high.
Is CVE-2022-41889 being actively exploited?: It is not currently listed in CISA's KEV catalog. Its EPSS exploit-prediction score is 0% (32nd percentile), an estimate of the probability of exploitation in the next 30 days.
What products are affected by CVE-2022-41889?: CVE-2022-41889 affects Google Tensorflow. See the affected-products list for the exact vulnerable versions.
How do I fix CVE-2022-41889?: Review the linked vendor and NVD advisories for patched versions and mitigations, then upgrade or apply the recommended workaround.
When was CVE-2022-41889 published?: CVE-2022-41889 was published on 2022-11-18 and last updated on 2026-06-17.

References

Affected products (1)

cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*

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