What’s Vulnerable › Vulnerabilities

CVE-2020-15201: Heap buffer overflow in Tensorflow

• Severity: medium (CVSS 4.8 v3.1)
• Exploited in the wild: not listed in CISA KEV
• EPSS: 0.6% probability of exploitation in the next 30 days
• Public exploit or detection template: yes
• Published: 2020-09-25 · updated 2026-06-17
• Weakness: CWE-20

Description

In Tensorflow before version 2.3.1, the `RaggedCountSparseOutput` implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the `splits` tensor generate a valid partitioning of the `values` tensor. Hence, the code is prone to heap buffer overflow. If `split_values` does not end with a value at least `num_values` then the `while` loop condition will trigger a read outside of the bounds of `split_values` once `batch_idx` grows too large. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.

Affected products

• tensorflow: 2.3.0

References

• https://github.com/tensorflow/tensorflow/commit/3cbb917b4714766030b28eba9fb41bb97ce9ee02
• https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1
• https://github.com/tensorflow/tensorflow/security/advisories/GHSA-p5f8-gfw5-33w4
• https://github.com/tensorflow/tensorflow/commit/3cbb917b4714766030b28eba9fb41bb97ce9ee02
• https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1
• https://github.com/tensorflow/tensorflow/security/advisories/GHSA-p5f8-gfw5-33w4

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