5.5

CVE-2021-29521

Exploit

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.

Data is provided by the National Vulnerability Database (NVD)
Google ≫ Tensorflow Version >= 2.3.0 < 2.3.3
Google ≫ Tensorflow Version >= 2.4.0 < 2.4.2
Zu dieser CVE wurde keine CISA KEV oder CERT.AT-Warnung gefunden.
EPSS Metriken
Type Source Score Percentile
EPSS FIRST.org 0.02% 0.014
CVSS Metriken
Source Base Score Exploit Score Impact Score Vector string
nvd@nist.gov 5.5 1.8 3.6
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
nvd@nist.gov 2.1 3.9 2.9
AV:L/AC:L/Au:N/C:N/I:N/A:P
security-advisories@github.com 2.5 1 1.4
CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L
CWE-131 Incorrect Calculation of Buffer Size

The product does not correctly calculate the size to be used when allocating a buffer, which could lead to a buffer overflow.