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CVE-2020-15200: Segfault in Tensorflow

• Severity: medium (CVSS 5.9 v3.1)
• Exploited in the wild: not listed in CISA KEV
• EPSS: 0.9% 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. Thus, the code sets up conditions to cause a heap buffer overflow. A `BatchedMap` is equivalent to a vector where each element is a hashmap. However, if the first element of `splits_values` is not 0, `batch_idx` will never be 1, hence there will be no hashmap at index 0 in `per_batch_counts`. Trying to access that in the user code results in a segmentation fault. 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-x7rp-74x2-mjf3
• 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-x7rp-74x2-mjf3

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