How severe is CVE-2022-35970?

CVE-2022-35970 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-2022-35970 being actively exploited?

It is not currently listed in CISA's KEV catalog. Its EPSS exploit-prediction score is 0% (38th percentile), an estimate of the probability of exploitation in the next 30 days.

What products are affected by CVE-2022-35970?

CVE-2022-35970 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-2022-35970?

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

When was CVE-2022-35970 published?

CVE-2022-35970 was published on 2022-09-16 and last updated on 2026-06-17.

CVE-2022-35970

CVE-2022-35970 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% (38th 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 `QuantizedInstanceNorm` is given `x_min` or `x_max` 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 785d67a78a1d533759fcd2f5e8d6ef778de849e0. 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-2022-35970?: TensorFlow is an open source platform for machine learning. If `QuantizedInstanceNorm` is given `x_min` or `x_max` 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 785d67a78a1d533759fcd2f5e8d6ef778de849e0. 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-2022-35970?: CVE-2022-35970 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-2022-35970 being actively exploited?: It is not currently listed in CISA's KEV catalog. Its EPSS exploit-prediction score is 0% (38th percentile), an estimate of the probability of exploitation in the next 30 days.
What products are affected by CVE-2022-35970?: CVE-2022-35970 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-2022-35970?: Review the linked vendor and NVD advisories for patched versions and mitigations, then upgrade or apply the recommended workaround.
When was CVE-2022-35970 published?: CVE-2022-35970 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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