How severe is CVE-2022-41887?

CVE-2022-41887 has a CVSS 3.x base score of 4.8, rated medium severity. It is exploitable over network with high attack complexity, requires low privileges and user interaction. Impact on confidentiality is none, integrity none, and availability high.

Is CVE-2022-41887 being actively exploited?

It is not currently listed in CISA's KEV catalog. Its EPSS exploit-prediction score is 0% (35th percentile), an estimate of the probability of exploitation in the next 30 days.

What products are affected by CVE-2022-41887?

CVE-2022-41887 primarily affects Google Tensorflow. In total, 2 product configurations (CPEs) are listed as vulnerable; see the affected-products list for the exact versions.

How do I fix CVE-2022-41887?

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

When was CVE-2022-41887 published?

CVE-2022-41887 was published on 2022-11-18 and last updated on 2026-06-17.

CVE-2022-41887

CVE-2022-41887 is a medium-severity vulnerability in Google Tensorflow with a CVSS 3.x base score of 4.8. 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-131.

Key facts

Severity: Medium (CVSS 3.x base score 4.8)
EPSS exploit prediction: 0% (35th percentile)
Actively exploited: Not listed in CISA KEV
Weakness: CWE-131
Affected product: Google Tensorflow
Published: 2022-11-18
Last modified: 2026-06-17

Description

TensorFlow is an open source platform for machine learning. `tf.keras.losses.poisson` receives a `y_pred` and `y_true` that are passed through `functor::mul` in `BinaryOp`. If the resulting dimensions overflow an `int32`, TensorFlow will crash due to a size mismatch during broadcast assignment. We have patched the issue in GitHub commit c5b30379ba87cbe774b08ac50c1f6d36df4ebb7c. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1 and 2.9.3, as these are also affected and still in supported range. However, we will not cherrypick this commit into TensorFlow 2.8.x, as it depends on Eigen behavior that changed between 2.8 and 2.9.

Frequently asked questions

What is CVE-2022-41887?: TensorFlow is an open source platform for machine learning. `tf.keras.losses.poisson` receives a `y_pred` and `y_true` that are passed through `functor::mul` in `BinaryOp`. If the resulting dimensions overflow an `int32`, TensorFlow will crash due to a size mismatch during broadcast assignment. We have patched the issue in GitHub commit c5b30379ba87cbe774b08ac50c1f6d36df4ebb7c. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1 and 2.9.3, as these are also affected and still in supported range. However, we will not cherrypick this commit into TensorFlow 2.8.x, as it depends on Eigen behavior that changed between 2.8 and 2.9.
How severe is CVE-2022-41887?: CVE-2022-41887 has a CVSS 3.x base score of 4.8, rated medium severity. It is exploitable over network with high attack complexity, requires low privileges and user interaction. Impact on confidentiality is none, integrity none, and availability high.
Is CVE-2022-41887 being actively exploited?: It is not currently listed in CISA's KEV catalog. Its EPSS exploit-prediction score is 0% (35th percentile), an estimate of the probability of exploitation in the next 30 days.
What products are affected by CVE-2022-41887?: CVE-2022-41887 primarily affects Google Tensorflow. In total, 2 product configurations (CPEs) are listed as vulnerable; see the affected-products list for the exact versions.
How do I fix CVE-2022-41887?: Review the linked vendor and NVD advisories for patched versions and mitigations, then upgrade or apply the recommended workaround.
When was CVE-2022-41887 published?: CVE-2022-41887 was published on 2022-11-18 and last updated on 2026-06-17.

References

Affected products (2)

cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*
cpe:2.3:a:google:tensorflow:2.10.0:*:*:*:*:*:*:*

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