Upstream information
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.SUSE information
Overall state of this security issue: Does not affect SUSE products
This issue is currently rated as having important severity.
National Vulnerability Database | |
---|---|
Base Score | 2.1 |
Vector | AV:L/AC:L/Au:N/C:N/I:N/A:P |
Access Vector | Local |
Access Complexity | Low |
Authentication | None |
Confidentiality Impact | None |
Integrity Impact | None |
Availability Impact | Partial |
National Vulnerability Database | |
---|---|
Base Score | 5.5 |
Vector | CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H |
Attack Vector | Local |
Attack Complexity | Low |
Privileges Required | Low |
User Interaction | None |
Scope | Unchanged |
Confidentiality Impact | None |
Integrity Impact | None |
Availability Impact | High |
CVSSv3 Version | 3.1 |
SUSE Timeline for this CVE
CVE page created: Mon May 17 08:58:28 2021CVE page last modified: Sat Mar 30 16:29:23 2024