CVE-2020-15194 : Exploit Details and Defense Strategies

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, and 2.3.1, a vulnerability exists in the

SparseFillEmptyRowsGrad

implementation, allowing malicious users to trigger an assertion failure, leading to denial of service.

Understanding CVE-2020-15194

This CVE describes a denial of service vulnerability in Tensorflow due to incomplete validation of argument shapes in a specific implementation.

What is CVE-2020-15194?

In Tensorflow versions prior to 1.15.4, 2.0.3, 2.1.2, 2.2.1, and 2.3.1, a flaw in the

SparseFillEmptyRowsGrad

implementation allows attackers to cause denial of service by passing a malicious argument.

The Impact of CVE-2020-15194

The vulnerability can be exploited by malicious users to trigger an assertion failure, resulting in denial of service in affected installations.

Technical Details of CVE-2020-15194

This section provides detailed technical information about the vulnerability.

Vulnerability Description

The

SparseFillEmptyRowsGrad

implementation in Tensorflow lacks complete validation of argument shapes, enabling attackers to exploit this flaw for denial of service.

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

Attackers can pass a malicious argument to the

SparseFillEmptyRowsGrad

function, triggering an assertion failure and causing denial of service.

Mitigation and Prevention

To address CVE-2020-15194, 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 patch.
Monitor for any unusual activities that could indicate exploitation of the vulnerability.

Long-Term Security Practices

Regularly update Tensorflow and other software components to the latest versions to prevent known vulnerabilities.
Implement proper input validation mechanisms in your applications to mitigate similar issues.

Patching and Updates

Apply the necessary patches provided by Tensorflow to fix the vulnerability and prevent exploitation.