5.5

CVE-2021-41213

TensorFlow is an open source platform for machine learning. In affected versions the code behind `tf.function` API can be made to deadlock when two `tf.function` decorated Python functions are mutually recursive. This occurs due to using a non-reentrant `Lock` Python object. Loading any model which contains mutually recursive functions is vulnerable. An attacker can cause denial of service by causing users to load such models and calling a recursive `tf.function`, although this is not a frequent scenario. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.

Daten sind bereitgestellt durch National Vulnerability Database (NVD)
Google ≫ Tensorflow Version >= 2.4.0 < 2.4.4
Google ≫ Tensorflow Version >= 2.5.0 < 2.5.2
Google ≫ Tensorflow Version >= 2.6.0 < 2.6.1
Google ≫ Tensorflow Version2.7.0 Updaterc0
Google ≫ Tensorflow Version2.7.0 Updaterc1
Zu dieser CVE wurde keine CISA KEV oder CERT.AT-Warnung gefunden.
EPSS Metriken
Typ Quelle Score Percentile
EPSS FIRST.org 0.08% 0.248
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:N/UI:R/S:U/C:N/I:N/A:H
nvd@nist.gov 4.3 8.6 2.9
AV:N/AC:M/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-662 Improper Synchronization

The product utilizes multiple threads or processes to allow temporary access to a shared resource that can only be exclusive to one process at a time, but it does not properly synchronize these actions, which might cause simultaneous accesses of this resource by multiple threads or processes.

CWE-667 Improper Locking

The product does not properly acquire or release a lock on a resource, leading to unexpected resource state changes and behaviors.