CVE-2021-29521
Summary
| CVE | CVE-2021-29521 |
| State | PUBLIC |
| Assigner | [email protected] |
| Source Priority | CVE Program / NVD first with legacy fallback |
| Published | 2021-05-14 20:15:00 UTC |
| Updated | 2021-05-20 17:19:00 UTC |
| 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. |
NVD Known Affected Configurations (CPE 2.3)
| Type | Vendor | Product | Version | Update | Edition | Language |
|---|
| Application |
Google |
Tensorflow |
All |
All |
All |
All |
References
| Reference | Source | Link | Tags |
|---|
| Fix the segfault in `tf.raw_ops.SparseCountSparseOutput`. · tensorflow/tensorflow@c57c0b9 · GitHub |
MISC |
github.com |
|
| Segfault in `SparseCountSparseOutput` · Advisory · tensorflow/tensorflow · GitHub |
CONFIRM |
github.com |
|
| CVE Program record |
CVE.ORG |
www.cve.org |
canonical |
| NVD vulnerability detail |
NVD |
nvd.nist.gov |
canonical, analysis |
No vendor comments have been submitted for this CVE.
Legacy QID Mappings
- 982525 Python (pip) Security Update for tensorflow-gpu (GHSA-hr84-fqvp-48mm)