How severe is CVE-2022-21726?

CVE-2022-21726 has a CVSS 3.x base score of 8.1, rated high severity. It is exploitable over network with low attack complexity, requires low privileges and no user interaction. Impact on confidentiality is high, integrity none, and availability high.

Is CVE-2022-21726 being actively exploited?

It is not currently listed in CISA's KEV catalog. Its EPSS exploit-prediction score is 1% (53rd percentile), an estimate of the probability of exploitation in the next 30 days.

What products are affected by CVE-2022-21726?

CVE-2022-21726 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-2022-21726?

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-2022-21726 published?

CVE-2022-21726 was published on 2022-02-03 and last updated on 2026-06-17.

CVE-2022-21726

CVE-2022-21726 is a high-severity vulnerability in Google Tensorflow with a CVSS 3.x base score of 8.1. 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 8.1)
CVSS v2: 6.5
EPSS exploit prediction: 1% (53rd percentile)
Actively exploited: Not listed in CISA KEV
Weakness: CWE-125
Affected product: Google Tensorflow
Published: 2022-02-03
Last modified: 2026-06-17

Description

Tensorflow is an Open Source Machine Learning Framework. The implementation of `Dequantize` does not fully validate the value of `axis` and can result in heap OOB accesses. The `axis` argument can be `-1` (the default value for the optional argument) or any other positive value at most the number of dimensions of the input. Unfortunately, the upper bound is not checked and this results in reading past the end of the array containing the dimensions of the input tensor. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Frequently asked questions

What is CVE-2022-21726?: Tensorflow is an Open Source Machine Learning Framework. The implementation of `Dequantize` does not fully validate the value of `axis` and can result in heap OOB accesses. The `axis` argument can be `-1` (the default value for the optional argument) or any other positive value at most the number of dimensions of the input. Unfortunately, the upper bound is not checked and this results in reading past the end of the array containing the dimensions of the input tensor. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
How severe is CVE-2022-21726?: CVE-2022-21726 has a CVSS 3.x base score of 8.1, rated high severity. It is exploitable over network with low attack complexity, requires low privileges and no user interaction. Impact on confidentiality is high, integrity none, and availability high.
Is CVE-2022-21726 being actively exploited?: It is not currently listed in CISA's KEV catalog. Its EPSS exploit-prediction score is 1% (53rd percentile), an estimate of the probability of exploitation in the next 30 days.
What products are affected by CVE-2022-21726?: CVE-2022-21726 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-2022-21726?: 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-2022-21726 published?: CVE-2022-21726 was published on 2022-02-03 and last updated on 2026-06-17.

References

Affected products (2)

cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*
cpe:2.3:a:google:tensorflow:2.7.0:*:*:*:*:*:*:*

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