CVE-2020-15197
Published: Sep 25, 2020
Modified: Aug 4, 2024
CVSS v3.1
6.3
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.
| Vendor | Product | Versions |
|---|---|---|
tensorflow | tensorflow | affected = 2.3.0 |
CVSS v3.1 Details
CVSS v3.1 Vector
CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:C/C:N/I:N/A:H
Attack Vector
Attack Complexity
Privileges Required
User Interaction
Scope
Confidentiality
Integrity
Availability
References
Security Training
Train your team to recognize and prevent security threats with our comprehensive security awareness program.
Start TrainingVulnerability Scanning
Discover vulnerabilities in your applications and infrastructure before attackers do.
Scan Now