Improper input validation in Google Tensorflow
CVE-2020-15199
In Tensorflow before version 2.3.1, the `RaggedCountSparseOutput` does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the `splits` tensor has the minimum required number of elements. Code uses this quantity to initialize a different data structure. Since `BatchedMap` is equivalent to a vector, it needs to have at least one element to not be `nullptr`. If user passes a `splits` tensor that is empty or has exactly one element, we get a `SIGABRT` signal raised by the operating system. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.
Vulnerability class: Drupalgeddon 2 (CVE-2018-7600)
EPSS: 0.008 (53.3th percentile) — read the EPSS interpretation.
CVSS v3 metric
CVSS v3 base score 5.9 (Medium). Vector: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H.
Affected products
- Google Tensorflow — versions 2.3.0
- Tensorflow — versions = 2.3.0
Weakness classification (CWE)
References
- security-advisories@github.com (Third Party Advisory, x_refsource_MISC)
- security-advisories@github.com (Patch, Third Party Advisory, x_refsource_MISC)
- security-advisories@github.com (x_refsource_CONFIRM, Exploit, Third Party Advisory)
Frequently asked questions
- What is CVE-2020-15199?
- CVE-2020-15199 is a medium-severity vulnerability in Google Tensorflow, classified under Improper Input Validation. CVSS score: 5.9/10. Published 2020-09-25.
- How severe is CVE-2020-15199?
- Medium severity. CVSS v3 base score is 5.9 out of 10.