How severe is CVE-2021-29546?

CVE-2021-29546 has a CVSS 3.x base score of 2.5, rated low severity. It is exploitable over local access with high attack complexity, requires low privileges and no user interaction. Impact on confidentiality is none, integrity none, and availability low.

Is CVE-2021-29546 being actively exploited?

It is not currently listed in CISA's KEV catalog. Its EPSS exploit-prediction score is 0% (10th percentile), an estimate of the probability of exploitation in the next 30 days.

What products are affected by CVE-2021-29546?

CVE-2021-29546 affects Google Tensorflow. See the affected-products list for the exact vulnerable versions.

How do I fix CVE-2021-29546?

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

When was CVE-2021-29546 published?

CVE-2021-29546 was published on 2021-05-14 and last updated on 2026-06-17.

CVE-2021-29546

CVE-2021-29546 is a low-severity vulnerability in Google Tensorflow with a CVSS 3.x base score of 2.5. 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-369.

Key facts

Severity: Low (CVSS 3.x base score 2.5)
CVSS v2: 4.6
EPSS exploit prediction: 0% (10th percentile)
Actively exploited: Not listed in CISA KEV
Weakness: CWE-369
Affected product: Google Tensorflow
Published: 2021-05-14
Last modified: 2026-06-17

Description

TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger an integer division by zero undefined behavior in `tf.raw_ops.QuantizedBiasAdd`. This is because the implementation of the Eigen kernel(https://github.com/tensorflow/tensorflow/blob/61bca8bd5ba8a68b2d97435ddfafcdf2b85672cd/tensorflow/core/kernels/quantization_utils.h#L812-L849) does a division by the number of elements of the smaller input (based on shape) without checking that this is not zero. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

Frequently asked questions

What is CVE-2021-29546?: TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger an integer division by zero undefined behavior in `tf.raw_ops.QuantizedBiasAdd`. This is because the implementation of the Eigen kernel(https://github.com/tensorflow/tensorflow/blob/61bca8bd5ba8a68b2d97435ddfafcdf2b85672cd/tensorflow/core/kernels/quantization_utils.h#L812-L849) does a division by the number of elements of the smaller input (based on shape) without checking that this is not zero. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
How severe is CVE-2021-29546?: CVE-2021-29546 has a CVSS 3.x base score of 2.5, rated low severity. It is exploitable over local access with high attack complexity, requires low privileges and no user interaction. Impact on confidentiality is none, integrity none, and availability low.
Is CVE-2021-29546 being actively exploited?: It is not currently listed in CISA's KEV catalog. Its EPSS exploit-prediction score is 0% (10th percentile), an estimate of the probability of exploitation in the next 30 days.
What products are affected by CVE-2021-29546?: CVE-2021-29546 affects Google Tensorflow. See the affected-products list for the exact vulnerable versions.
How do I fix CVE-2021-29546?: Review the linked vendor and NVD advisories for patched versions and mitigations, then upgrade or apply the recommended workaround.
When was CVE-2021-29546 published?: CVE-2021-29546 was published on 2021-05-14 and last updated on 2026-06-17.

References

Affected products (1)

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

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