How severe is CVE-2022-35938?

CVE-2022-35938 has a CVSS 3.x base score of 7.0, rated high severity. It is exploitable over network with high attack complexity, requires no privileges and no user interaction. Impact on confidentiality is low, integrity low, and availability high.

Is CVE-2022-35938 being actively exploited?

It is not currently listed in CISA's KEV catalog. Its EPSS exploit-prediction score is 0% (36th percentile), an estimate of the probability of exploitation in the next 30 days.

What products are affected by CVE-2022-35938?

CVE-2022-35938 primarily affects Google Tensorflow. In total, 5 product configurations (CPEs) are listed as vulnerable; see the affected-products list for the exact versions.

How do I fix CVE-2022-35938?

Review the linked vendor and NVD advisories for patched versions and mitigations, then upgrade or apply the recommended workaround. Given its high severity, prioritise patching exposed systems.

When was CVE-2022-35938 published?

CVE-2022-35938 was published on 2022-09-16 and last updated on 2026-06-17.

CVE-2022-35938

CVE-2022-35938 is a high-severity vulnerability in Google Tensorflow with a CVSS 3.x base score of 7.0. 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-125.

Key facts

Severity: High (CVSS 3.x base score 7.0)
EPSS exploit prediction: 0% (36th percentile)
Actively exploited: Not listed in CISA KEV
Weakness: CWE-125
Affected product: Google Tensorflow
Published: 2022-09-16
Last modified: 2026-06-17

Description

TensorFlow is an open source platform for machine learning. The `GatherNd` function takes arguments that determine the sizes of inputs and outputs. If the inputs given are greater than or equal to the sizes of the outputs, an out-of-bounds memory read or a crash is triggered. This issue has been patched in GitHub commit 4142e47e9e31db481781b955ed3ff807a781b494. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

Frequently asked questions

What is CVE-2022-35938?: TensorFlow is an open source platform for machine learning. The `GatherNd` function takes arguments that determine the sizes of inputs and outputs. If the inputs given are greater than or equal to the sizes of the outputs, an out-of-bounds memory read or a crash is triggered. This issue has been patched in GitHub commit 4142e47e9e31db481781b955ed3ff807a781b494. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
How severe is CVE-2022-35938?: CVE-2022-35938 has a CVSS 3.x base score of 7.0, rated high severity. It is exploitable over network with high attack complexity, requires no privileges and no user interaction. Impact on confidentiality is low, integrity low, and availability high.
Is CVE-2022-35938 being actively exploited?: It is not currently listed in CISA's KEV catalog. Its EPSS exploit-prediction score is 0% (36th percentile), an estimate of the probability of exploitation in the next 30 days.
What products are affected by CVE-2022-35938?: CVE-2022-35938 primarily affects Google Tensorflow. In total, 5 product configurations (CPEs) are listed as vulnerable; see the affected-products list for the exact versions.
How do I fix CVE-2022-35938?: Review the linked vendor and NVD advisories for patched versions and mitigations, then upgrade or apply the recommended workaround. Given its high severity, prioritise patching exposed systems.
When was CVE-2022-35938 published?: CVE-2022-35938 was published on 2022-09-16 and last updated on 2026-06-17.

References

Affected products (5)

cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*
cpe:2.3:a:google:tensorflow:2.10:rc0:*:*:*:*:*:*
cpe:2.3:a:google:tensorflow:2.10:rc1:*:*:*:*:*:*
cpe:2.3:a:google:tensorflow:2.10:rc2:*:*:*:*:*:*
cpe:2.3:a:google:tensorflow:2.10:rc3:*:*:*:*:*:*

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