CVE-2021-41197 : Vulnerability Insights and Analysis

TensorFlow allows tensors to have a large number of dimensions, leading to crashes due to overflow. Learn about the impact, technical details, and mitigation of this vulnerability.

Understanding CVE-2021-41197

TensorFlow's large tensor shapes can cause crashes due to overflow, impacting the system's availability.

What is CVE-2021-41197?

TensorFlow's affected versions allow tensors with extensive dimensions, resulting in an overflow that triggers crashes.

The Impact of CVE-2021-41197

CVSS Score: 5.5 (Medium)
Attack Complexity: Low
Privileges Required: Low
Availability Impact: High
The vulnerability allows malicious actors to cause crashes by exploiting large tensor shapes in TensorFlow.

Technical Details of CVE-2021-41197

TensorFlow vulnerability details and affected systems.

Vulnerability Description

Tensors can have numerous dimensions, leading to an overflow that causes crashes in TensorFlow.

Affected Systems and Versions

TensorFlow versions:
= 2.6.0, < 2.6.1

= 2.5.0, < 2.5.2

< 2.4.4

Exploitation Mechanism

The total number of elements in a tensor must fit within

int64_t

. An overflow triggers a

MultiplyWithoutOverflow

issue and leads to crashes.

Mitigation and Prevention

Steps to mitigate the CVE-2021-41197 vulnerability.

Immediate Steps to Take

Update TensorFlow to version 2.7.0 or apply the fix available in versions 2.6.1, 2.5.2, and 2.4.4.
Monitor for any abnormal tensor behavior that could indicate an overflow.

Long-Term Security Practices

Regularly update TensorFlow to the latest versions to patch vulnerabilities promptly.

Patching and Updates

Apply security patches and fixes provided by TensorFlow to prevent crashes due to tensor overflows.