CVE-2020-15197
6.3
Vector
CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:C/C:N/I:N/A:H
Exploitability: 1.8 / Impact: 4.0
Source: NVD
Description
In Tensorflow before version 2.3.1, the `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has rank 2. This tensor must be a matrix because code assumes its elements are accessed as elements of a matrix. However, malicious users can pass in tensors of different rank, resulting in a `CHECK` assertion failure and a crash. This can be used to cause denial of service in serving installations, if users are allowed to control the components of the input sparse tensor. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.
Affected (1)
Products: Google: Tensorflow
Configuration A
| Vulnerable Software | Affected Versions |
|---|---|
| Version 2.3.0 |
Related CWEs
CWE-20
Improper Input Validation
The product receives input or data, but it does
not validate or incorrectly validates that the input has the
properties that are required to process the data safely and
correctly.
CWE-617
Reachable Assertion
The product contains an assert() or similar statement that can be triggered by an attacker, which leads to an application exit or other behavior that is more severe than necessary.
References (6)
Source: security-advisories@github.com
PatchThird Party Advisory
Source: security-advisories@github.com
Third Party Advisory
Source: security-advisories@github.com
ExploitThird Party Advisory
Source: af854a3a-2127-422b-91ae-364da2661108
PatchThird Party Advisory
Source: af854a3a-2127-422b-91ae-364da2661108
Third Party Advisory
Source: af854a3a-2127-422b-91ae-364da2661108
ExploitThird Party Advisory
Timeline
No history available yet.