How severe is CVE-2020-15266?

CVE-2020-15266 has a CVSS 3.x base score of 3.7, rated low 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 low.

Is CVE-2020-15266 being actively exploited?

It is not currently listed in CISA's KEV catalog. Its EPSS exploit-prediction score is 1% (56th percentile), an estimate of the probability of exploitation in the next 30 days.

What products are affected by CVE-2020-15266?

CVE-2020-15266 affects Google Tensorflow. See the affected-products list for the exact vulnerable versions.

How do I fix CVE-2020-15266?

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

When was CVE-2020-15266 published?

CVE-2020-15266 was published on 2020-10-21 and last updated on 2026-06-17.

CVE-2020-15266

CVE-2020-15266 is a low-severity vulnerability in Google Tensorflow with a CVSS 3.x base score of 3.7. 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-119.

Key facts

Severity: Low (CVSS 3.x base score 3.7)
CVSS v2: 5.0
EPSS exploit prediction: 1% (56th percentile)
Actively exploited: Not listed in CISA KEV
Weakness: CWE-119
Affected product: Google Tensorflow
Published: 2020-10-21
Last modified: 2026-06-17

Description

In Tensorflow before version 2.4.0, when the `boxes` argument of `tf.image.crop_and_resize` has a very large value, the CPU kernel implementation receives it as a C++ `nan` floating point value. Attempting to operate on this is undefined behavior which later produces a segmentation fault. The issue is patched in eccb7ec454e6617738554a255d77f08e60ee0808 and TensorFlow 2.4.0 will be released containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.

Frequently asked questions

What is CVE-2020-15266?: In Tensorflow before version 2.4.0, when the `boxes` argument of `tf.image.crop_and_resize` has a very large value, the CPU kernel implementation receives it as a C++ `nan` floating point value. Attempting to operate on this is undefined behavior which later produces a segmentation fault. The issue is patched in eccb7ec454e6617738554a255d77f08e60ee0808 and TensorFlow 2.4.0 will be released containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.
How severe is CVE-2020-15266?: CVE-2020-15266 has a CVSS 3.x base score of 3.7, rated low 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 low.
Is CVE-2020-15266 being actively exploited?: It is not currently listed in CISA's KEV catalog. Its EPSS exploit-prediction score is 1% (56th percentile), an estimate of the probability of exploitation in the next 30 days.
What products are affected by CVE-2020-15266?: CVE-2020-15266 affects Google Tensorflow. See the affected-products list for the exact vulnerable versions.
How do I fix CVE-2020-15266?: Review the linked vendor and NVD advisories for patched versions and mitigations, then upgrade or apply the recommended workaround.
When was CVE-2020-15266 published?: CVE-2020-15266 was published on 2020-10-21 and last updated on 2026-06-17.

References

Affected products (1)

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

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