CVE-2021-29521 | Date: (C)2021-05-17 (M)2023-12-22 |
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` (i.e., `std::vector>`(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.
CVSS Score and Metrics +CVSS Score and Metrics -CVSS V3 Severity: | CVSS V2 Severity: |
CVSS Score : 5.5 | CVSS Score : 2.1 |
Exploit Score: 1.8 | Exploit Score: 3.9 |
Impact Score: 3.6 | Impact Score: 2.9 |
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CVSS V3 Metrics: | CVSS V2 Metrics: |
Attack Vector: LOCAL | Access Vector: LOCAL |
Attack Complexity: LOW | Access Complexity: LOW |
Privileges Required: LOW | Authentication: NONE |
User Interaction: NONE | Confidentiality: NONE |
Scope: UNCHANGED | Integrity: NONE |
Confidentiality: NONE | Availability: PARTIAL |
Integrity: NONE | |
Availability: HIGH | |
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