Vulnerability in Google Tensorflow
CVE-2022-23573
Tensorflow is an Open Source Machine Learning Framework. The implementation of `AssignOp` can result in copying uninitialized data to a new tensor. This later results in undefined behavior. The implementation has a check that the left hand side of the assignment is initialized (to minimize number of allocations), but does not check that the right hand side is also initialized. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
EPSS: 0.008 (51.4th percentile) — read the EPSS interpretation.
CVSS v3 metric
CVSS v3 base score 7.6 (High). Vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:H.
Affected products
- Google Tensorflow — versions 2.7.0
- Tensorflow — versions >= 2.7.0, < 2.7.1, >= 2.6.0, < 2.6.3, < 2.5.3
Weakness classification (CWE)
Public proof-of-concept exploits
References
- security-advisories@github.com (x_refsource_CONFIRM, Patch, Third Party Advisory)
- security-advisories@github.com (Patch, Third Party Advisory, x_refsource_MISC)
- security-advisories@github.com (Exploit, Third Party Advisory, x_refsource_MISC)
Frequently asked questions
- What is CVE-2022-23573?
- CVE-2022-23573 is a high-severity vulnerability in Google Tensorflow, classified under Use of Uninitialized Resource. CVSS score: 7.6/10. Published 2022-02-04.
- How severe is CVE-2022-23573?
- High severity. CVSS v3 base score is 7.6 out of 10.
- Is CVE-2022-23573 known to be exploited?
- 1 public proof-of-concept repositories are indexed. Not currently listed in the CISA KEV catalog.