CVE-2020-15195 : What You Need to Know

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, and 2.3.1, a heap buffer overflow vulnerability was identified in the implementation of

SparseFillEmptyRowsGrad

due to a double indexing pattern.

Understanding CVE-2020-15195

This CVE involves a critical heap buffer overflow vulnerability in Tensorflow versions prior to 1.15.4, 2.0.3, 2.1.2, 2.2.1, and 2.3.1.

What is CVE-2020-15195?

This vulnerability in Tensorflow versions before the specified patches could allow an attacker to trigger a heap buffer overflow by exploiting the

SparseFillEmptyRowsGrad

implementation.

The Impact of CVE-2020-15195

The impact of this vulnerability is rated as HIGH with a CVSS base score of 8.5. It affects confidentiality, integrity, and availability, with a low level of privileges required for exploitation.

Technical Details of CVE-2020-15195

This section provides detailed technical information about the vulnerability.

Vulnerability Description

The issue arises from the use of a double indexing pattern in

SparseFillEmptyRowsGrad

, leading to a heap buffer overflow due to an out-of-bounds index.

Affected Systems and Versions

Tensorflow versions < 1.15.4
Tensorflow versions >= 2.0.0, < 2.0.3
Tensorflow versions >= 2.1.0, < 2.1.2
Tensorflow versions >= 2.2.0, < 2.2.1
Tensorflow versions >= 2.3.0, < 2.3.1

Exploitation Mechanism

The vulnerability can be exploited by manipulating the

reverse_index_map(i)

function to access memory outside the bounds of

grad_values

, resulting in a heap buffer overflow.

Mitigation and Prevention

To address CVE-2020-15195, follow these mitigation strategies:

Immediate Steps to Take

Update Tensorflow to versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1 that contain the necessary patches.
Monitor for any unusual activities on the network that could indicate exploitation of this vulnerability.

Long-Term Security Practices

Regularly update software and libraries to the latest secure versions.
Conduct security audits and code reviews to identify and address potential vulnerabilities.

Patching and Updates

Apply the patches provided by Tensorflow for the respective affected versions to eliminate the heap buffer overflow vulnerability.