Integer overflow in Google Tensorflow

CVE-2021-41203

TensorFlow is an open source platform for machine learning. In affected versions an attacker can trigger undefined behavior, integer overflows, segfaults and `CHECK`-fail crashes if they can change saved checkpoints from outside of TensorFlow. This is because the checkpoints loading infrastructure is missing validation for invalid file formats. The fixes will be included in TensorFlow 2.7.0. We will also cherrypick these commits on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.

Published · last modified .

CVSS v3 metric

CVSS v3 base score 7.8 (High). Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H.

EPSS exploit prediction

EPSS: 0.002 (7.6th percentile), scored .

Very low probability of exploitation in the next 30 days; routine patching cadence is appropriate. 8th percentile — 7.6% of CVEs in the catalogue have a lower EPSS than this one. How to read EPSS.

EPSS trend (30 days)EPSS over the last 30 days for CVE-2021-41203: held from 0.002 to 0.002.

EPSS over last 30 days · oldest: 0.002 · newest: 0.002 · change: 0.000

Affected products

Weakness classification (CWE)

Public proof-of-concept exploits

References

Frequently asked questions

What is CVE-2021-41203?
CVE-2021-41203 is a high-severity vulnerability in Google Tensorflow, classified under Insufficient Verification of Data Authenticity. CVSS score: 7.8/10. Published 2021-11-05.
How severe is CVE-2021-41203?
High severity. CVSS v3 base score is 7.8 out of 10.
Is CVE-2021-41203 known to be exploited?
2 public proof-of-concept repositories are indexed. Not currently listed in the CISA KEV catalog.