How severe is CVE-2022-35967?

CVE-2022-35967 has a CVSS 3.x base score of 5.9, rated medium severity. It is exploitable over network with high attack complexity, requires no privileges and no user interaction. Impact on confidentiality is none, integrity none, and availability high.

Is CVE-2022-35967 being actively exploited?

It is not currently listed in CISA's KEV catalog. Its EPSS exploit-prediction score is 0% (33rd percentile), an estimate of the probability of exploitation in the next 30 days.

What products are affected by CVE-2022-35967?

CVE-2022-35967 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-2022-35967?

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

When was CVE-2022-35967 published?

CVE-2022-35967 was published on 2022-09-16 and last updated on 2026-06-17.

CVE-2022-35967

CVE-2022-35967 is a medium-severity vulnerability in Google Tensorflow with a CVSS 3.x base score of 5.9. 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-20.

Key facts

Severity: Medium (CVSS 3.x base score 5.9)
EPSS exploit prediction: 0% (33rd percentile)
Actively exploited: Not listed in CISA KEV
Weakness: CWE-20
Affected product: Google Tensorflow
Published: 2022-09-16
Last modified: 2026-06-17

Description

TensorFlow is an open source platform for machine learning. If `QuantizedAdd` is given `min_input` or `max_input` tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 49b3824d83af706df0ad07e4e677d88659756d89. 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-2022-35967?: TensorFlow is an open source platform for machine learning. If `QuantizedAdd` is given `min_input` or `max_input` tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 49b3824d83af706df0ad07e4e677d88659756d89. 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-2022-35967?: CVE-2022-35967 has a CVSS 3.x base score of 5.9, rated medium severity. It is exploitable over network with high attack complexity, requires no privileges and no user interaction. Impact on confidentiality is none, integrity none, and availability high.
Is CVE-2022-35967 being actively exploited?: It is not currently listed in CISA's KEV catalog. Its EPSS exploit-prediction score is 0% (33rd percentile), an estimate of the probability of exploitation in the next 30 days.
What products are affected by CVE-2022-35967?: CVE-2022-35967 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-2022-35967?: Review the linked vendor and NVD advisories for patched versions and mitigations, then upgrade or apply the recommended workaround.
When was CVE-2022-35967 published?: CVE-2022-35967 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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