Vulnerability in Google Tensorflow
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.
EPSS: 0.002 (14.6th percentile) — read the EPSS interpretation.
CVSS v3 metric
CVSS v3 base score 5.5 (Medium). Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H.
Affected products
- Google Tensorflow — versions 2.7.0
- Tensorflow — versions >= 2.6.0, < 2.6.1, >= 2.5.0, < 2.5.2, < 2.4.4
Weakness classification (CWE)
Public proof-of-concept exploits
References
- security-advisories@github.com (x_refsource_CONFIRM, Third Party Advisory)
- security-advisories@github.com (Patch, Third Party Advisory, x_refsource_MISC)
Frequently asked questions
- What is CVE-2021-41213?
- CVE-2021-41213 is a medium-severity vulnerability in Google Tensorflow, classified under Improper Locking. CVSS score: 5.5/10. Published 2021-11-05.
- How severe is CVE-2021-41213?
- Medium severity. CVSS v3 base score is 5.5 out of 10.
- Is CVE-2021-41213 known to be exploited?
- 2 public proof-of-concept repositories are indexed. Not currently listed in the CISA KEV catalog.