CVE-2020-15197 : Vulnerability Insights and Analysis

In Tensorflow before version 2.3.1, a vulnerability allows malicious users to cause denial of service by passing in tensors of different rank, resulting in a crash.

Understanding CVE-2020-15197

This CVE involves a vulnerability in Tensorflow that could lead to denial of service attacks.

What is CVE-2020-15197?

In Tensorflow before version 2.3.1, the

SparseCountSparseOutput

implementation lacks validation for input arguments, allowing malicious users to trigger a crash, leading to denial of service.

The Impact of CVE-2020-15197

The vulnerability can be exploited by malicious users to cause denial of service in serving installations by passing tensors of different rank, triggering a crash.

Technical Details of CVE-2020-15197

This section provides detailed technical information about the CVE.

Vulnerability Description

The issue arises from the lack of validation in the

SparseCountSparseOutput

implementation, allowing for a denial of service attack.

Affected Systems and Versions

Product: Tensorflow
Vendor: Tensorflow
Versions Affected: 2.3.0

Exploitation Mechanism

Attack Complexity: High
Attack Vector: Network
Privileges Required: Low
Scope: Changed
Availability Impact: High

Mitigation and Prevention

Steps to address and prevent the CVE.

Immediate Steps to Take

Update Tensorflow to version 2.3.1 or later.
Restrict user input to prevent malicious tensor manipulation.

Long-Term Security Practices

Regularly update software to the latest versions.
Implement input validation checks in code to prevent similar vulnerabilities.

Patching and Updates

Patch the vulnerability by updating to Tensorflow version 2.3.1 or above.