How severe is CVE-2020-15198?

CVE-2020-15198 has a CVSS 3.x base score of 5.4, rated medium severity. It is exploitable over network with high attack complexity, requires no privileges and no user interaction. Impact on confidentiality is low, integrity low, and availability none.

Is CVE-2020-15198 being actively exploited?

It is not currently listed in CISA's KEV catalog. Its EPSS exploit-prediction score is 1% (41st percentile), an estimate of the probability of exploitation in the next 30 days.

What products are affected by CVE-2020-15198?

CVE-2020-15198 affects Google Tensorflow. See the affected-products list for the exact vulnerable versions.

How do I fix CVE-2020-15198?

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

When was CVE-2020-15198 published?

CVE-2020-15198 was published on 2020-09-25 and last updated on 2026-06-17.

CVE-2020-15198

CVE-2020-15198 is a medium-severity vulnerability in Google Tensorflow with a CVSS 3.x base score of 5.4. 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: Medium (CVSS 3.x base score 5.4)
CVSS v2: 5.8
EPSS exploit prediction: 1% (41st percentile)
Actively exploited: Not listed in CISA KEV
Weakness: CWE-119
Affected product: Google Tensorflow
Published: 2020-09-25
Last modified: 2026-06-17

Description

In Tensorflow before version 2.3.1, the `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has the same shape as the `values` one. The values in these tensors are always accessed in parallel. Thus, a shape mismatch can result in accesses outside the bounds of heap allocated buffers. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.

Frequently asked questions

What is CVE-2020-15198?: In Tensorflow before version 2.3.1, the `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has the same shape as the `values` one. The values in these tensors are always accessed in parallel. Thus, a shape mismatch can result in accesses outside the bounds of heap allocated buffers. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.
How severe is CVE-2020-15198?: CVE-2020-15198 has a CVSS 3.x base score of 5.4, rated medium severity. It is exploitable over network with high attack complexity, requires no privileges and no user interaction. Impact on confidentiality is low, integrity low, and availability none.
Is CVE-2020-15198 being actively exploited?: It is not currently listed in CISA's KEV catalog. Its EPSS exploit-prediction score is 1% (41st percentile), an estimate of the probability of exploitation in the next 30 days.
What products are affected by CVE-2020-15198?: CVE-2020-15198 affects Google Tensorflow. See the affected-products list for the exact vulnerable versions.
How do I fix CVE-2020-15198?: Review the linked vendor and NVD advisories for patched versions and mitigations, then upgrade or apply the recommended workaround.
When was CVE-2020-15198 published?: CVE-2020-15198 was published on 2020-09-25 and last updated on 2026-06-17.

References

Affected products (1)

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

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