Buffer overflow in Google Tensorflow
CVE-2020-15210
In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, if a TFLite saved model uses the same tensor as both input and output of an operator, then, depending on the operator, we can observe a segmentation fault or just memory corruption. We have patched the issue in d58c96946b and will release patch releases for all versions between 1.15 and 2.3. We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.
Vulnerability class: Drupalgeddon 2 (CVE-2018-7600)
EPSS: 0.007 (50.9th percentile) — read the EPSS interpretation.
CVSS v3 metric
CVSS v3 base score 6.5 (Medium). Vector: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:L/A:H.
Affected products
- Google Tensorflow
- Tensorflow — versions < 1.15.4, >= 2.0.0, < 2.0.3, >= 2.1.0, < 2.1.2
- Opensuse Leap — versions 15.2
Weakness classification (CWE)
References
- security-advisories@github.com (Third Party Advisory, x_refsource_MISC)
- security-advisories@github.com (x_refsource_CONFIRM, Exploit, Third Party Advisory)
- security-advisories@github.com (Patch, Third Party Advisory, x_refsource_MISC)
- security-advisories@github.com (vendor-advisory, Mailing List, Third Party Advisory, x_refsource_SUSE)
Frequently asked questions
- What is CVE-2020-15210?
- CVE-2020-15210 is a medium-severity vulnerability in Google Tensorflow, classified under Improper Input Validation. CVSS score: 6.5/10. Published 2020-09-25.
- How severe is CVE-2020-15210?
- Medium severity. CVSS v3 base score is 6.5 out of 10.