7.8

CVE-2021-29607

Exploit

TensorFlow is an end-to-end open source platform for machine learning. Incomplete validation in `SparseAdd` results in allowing attackers to exploit undefined behavior (dereferencing null pointers) as well as write outside of bounds of heap allocated data. The implementation(https://github.com/tensorflow/tensorflow/blob/656e7673b14acd7835dc778867f84916c6d1cac2/tensorflow/core/kernels/sparse_sparse_binary_op_shared.cc) has a large set of validation for the two sparse tensor inputs (6 tensors in total), but does not validate that the tensors are not empty or that the second dimension of `*_indices` matches the size of corresponding `*_shape`. This allows attackers to send tensor triples that represent invalid sparse tensors to abuse code assumptions that are not protected by validation. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

Data is provided by the National Vulnerability Database (NVD)
Google ≫ Tensorflow Version < 2.1.4
Google ≫ Tensorflow Version >= 2.2.0 < 2.2.3
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 0.05% 0.119
CVSS Metriken
Source Base Score Exploit Score Impact Score Vector string
nvd@nist.gov 7.8 1.8 5.9
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
nvd@nist.gov 4.6 3.9 6.4
AV:L/AC:L/Au:N/C:P/I:P/A:P
security-advisories@github.com 5.3 1 4.2
CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:L/A:H
CWE-754 Improper Check for Unusual or Exceptional Conditions

The product does not check or incorrectly checks for unusual or exceptional conditions that are not expected to occur frequently during day to day operation of the product.