What’s Vulnerable › Vulnerabilities

CVE-2020-15196: Heap buffer overflow in Tensorflow

• Severity: critical (CVSS 9.9 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-119

Description

In Tensorflow version 2.3.0, the `SparseCountSparseOutput` and `RaggedCountSparseOutput` implementations don't validate that the `weights` tensor has the same shape as the data. The check exists for `DenseCountSparseOutput`, where both tensors are fully specified. In the sparse and ragged count weights are still accessed in parallel with the data. But, since there is no validation, a user passing fewer weights than the values for the tensors can generate a read from outside the bounds of the heap buffer allocated for the weights. 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-pg59-2f92-5cph
• 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-pg59-2f92-5cph

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