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Medium · 5.9 CVE-2020-15200 BIT-tensorflow-2020-15200EUVD-2020-0196GHSA-x7rp-74x2-mjf3PYSEC-2020-123PYSEC-2020-280PYSEC-2020-315

Segfault in Tensorflow

Published Sep 25, 2020 · Updated Aug 4, 2024 · Assigned by GitHub_M

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

VendorProductAffectedFixed
tensorflow tensorflow = 2.3.0 —

Affected packages

EcosystemPackageAffectedFixedRecord
PyPI tensorflow >= 2.3.0, < 2.3.1 2.3.1 GHSA-x7rp-74x2-mjf3
PyPI tensorflow < 2.3.1 2.3.1 PYSEC-2020-123
PyPI tensorflow-cpu >= 2.3.0, < 2.3.1 2.3.1 GHSA-x7rp-74x2-mjf3
PyPI tensorflow-cpu < 2.3.1 2.3.1 PYSEC-2020-280
PyPI tensorflow-gpu >= 2.3.0, < 2.3.1 2.3.1 GHSA-x7rp-74x2-mjf3
PyPI tensorflow-gpu < 2.3.1 2.3.1 PYSEC-2020-315

References