Integer overflow in Google Tensorflow
CVE-2021-41196
TensorFlow is an open source platform for machine learning. In affected versions the Keras pooling layers can trigger a segfault if the size of the pool is 0 or if a dimension is negative. This is due to the TensorFlow's implementation of pooling operations where the values in the sliding window are not checked to be strictly positive. 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 (14.0th 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
- 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, Exploit, Third Party Advisory)
- security-advisories@github.com (Exploit, Third Party Advisory, x_refsource_MISC)
- security-advisories@github.com (Patch, Third Party Advisory, x_refsource_MISC)
Frequently asked questions
- What is CVE-2021-41196?
- CVE-2021-41196 is a medium-severity vulnerability in Google Tensorflow, classified under Integer Underflow. CVSS score: 5.5/10. Published 2021-11-05.
- How severe is CVE-2021-41196?
- Medium severity. CVSS v3 base score is 5.5 out of 10.
- Is CVE-2021-41196 known to be exploited?
- 2 public proof-of-concept repositories are indexed. Not currently listed in the CISA KEV catalog.