- Description
- TensorFlow is an end-to-end open source platform for machine learning. Specifying a negative dense shape in `tf.raw_ops.SparseCountSparseOutput` results in a segmentation fault being thrown out from the standard library as `std::vector` invariants are broken. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/8f7b60ee8c0206a2c99802e3a4d1bb55d2bc0624/tensorflow/core/kernels/count_ops.cc#L199-L213) assumes the first element of the dense shape is always positive and uses it to initialize a `BatchedMap<T>` (i.e., `std::vector<absl::flat_hash_map<int64,T>>`(https://github.com/tensorflow/tensorflow/blob/8f7b60ee8c0206a2c99802e3a4d1bb55d2bc0624/tensorflow/core/kernels/count_ops.cc#L27)) data structure. If the `shape` tensor has more than one element, `num_batches` is the first value in `shape`. Ensuring that the `dense_shape` argument is a valid tensor shape (that is, all elements are non-negative) solves this issue. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 and TensorFlow 2.3.3.
- Source
- security-advisories@github.com
- NVD status
- Analyzed
CVSS 3.1
- Type
- Primary
- Base score
- 5.5
- Impact score
- 3.6
- Exploitability score
- 1.8
- Vector string
- CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
- Severity
- MEDIUM
CVSS 2.0
- Type
- Primary
- Base score
- 2.1
- Impact score
- 2.9
- Exploitability score
- 3.9
- Vector string
- AV:L/AC:L/Au:N/C:N/I:N/A:P
- security-advisories@github.com
- CWE-131
- Hype score
- Not currently trending
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