CVE-2020-15206 Explained : Impact and Mitigation

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, and 2.3.1, altering the TensorFlow's

SavedModel

protocol buffer can lead to denial of service attacks.

Understanding CVE-2020-15206

Tensorflow versions prior to 1.15.4, 2.0.3, 2.1.2, 2.2.1, and 2.3.1 are susceptible to a denial of service vulnerability.

What is CVE-2020-15206?

In Tensorflow versions before 1.15.4, 2.0.3, 2.1.2, 2.2.1, and 2.3.1, modifying the

SavedModel

protocol buffer can result in segfaults and data corruption, potentially leading to denial of service attacks.

The Impact of CVE-2020-15206

CVSS Score: 9 (Critical)
Attack Vector: Network
Attack Complexity: High
Privileges Required: None
Scope: Changed
Confidentiality Impact: High
Integrity Impact: High
Availability Impact: High
This vulnerability can cause denial of service in products using

tensorflow-serving

or similar inference-as-a-service setups.

Technical Details of CVE-2020-15206

Tensorflow versions affected, vulnerability description, affected systems, and exploitation mechanism.

Vulnerability Description

Changing the

SavedModel

protocol buffer in Tensorflow versions before 1.15.4, 2.0.3, 2.1.2, 2.2.1, and 2.3.1 can lead to segfaults and data corruption during model loading, potentially causing denial of service.

Affected Systems and Versions

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

Exploitation Mechanism

The vulnerability can be exploited by manipulating the

SavedModel

protocol buffer, resulting in data corruption and segfaults during model loading.

Mitigation and Prevention

Steps to mitigate and prevent the CVE-2020-15206 vulnerability.

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 security advisories for any further updates or patches.

Long-Term Security Practices

Regularly update software and libraries to the latest versions.
Implement input validation mechanisms to prevent similar vulnerabilities.

Patching and Updates

Apply the patches provided in Tensorflow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1 to address the vulnerability.