5.5

CVE-2021-37661

TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause a denial of service in `boosted_trees_create_quantile_stream_resource` by using negative arguments. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantile_ops.cc#L96) does not validate that `num_streams` only contains non-negative numbers. In turn, [this results in using this value to allocate memory](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantiles/quantile_stream_resource.h#L31-L40). However, `reserve` receives an unsigned integer so there is an implicit conversion from a negative value to a large positive unsigned. This results in a crash from the standard library. We have patched the issue in GitHub commit 8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

Daten sind bereitgestellt durch National Vulnerability Database (NVD)
GoogleTensorflow Version >= 2.3.0 < 2.3.4
GoogleTensorflow Version >= 2.4.0 < 2.4.3
GoogleTensorflow Version2.5.0
GoogleTensorflow Version2.6.0 Updaterc0
GoogleTensorflow Version2.6.0 Updaterc1
GoogleTensorflow Version2.6.0 Updaterc2
Zu dieser CVE wurde keine CISA KEV oder CERT.AT-Warnung gefunden.
EPSS Metriken
Typ Quelle Score Percentile
EPSS FIRST.org 0.01% 0.011
CVSS Metriken
Quelle 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 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
CWE-681 Incorrect Conversion between Numeric Types

When converting from one data type to another, such as long to integer, data can be omitted or translated in a way that produces unexpected values. If the resulting values are used in a sensitive context, then dangerous behaviors may occur.