CVE-2020-5215 : What You Need to Know
Learn about CVE-2020-5215, a vulnerability in TensorFlow versions before 1.15.2 and 2.0.1. Attackers can exploit this issue by converting Python strings to tf.float16 values, leading to potential denial of service attacks.
In TensorFlow before 1.15.2 and 2.0.1, a vulnerability exists that can lead to a denial of service attack. This issue arises when converting a Python string to a tf.float16 value, resulting in a segmentation fault in eager mode. Attackers can exploit this to send malicious data points, causing potential service disruption.
Understanding CVE-2020-5215
This CVE highlights a vulnerability in TensorFlow versions prior to 1.15.2 and 2.0.1, where converting a Python string to a tf.float16 value can trigger a segmentation fault, potentially leading to denial of service attacks.
What is CVE-2020-5215?
The vulnerability in TensorFlow allows attackers to cause a denial of service by manipulating data points and saved models, triggering a segmentation fault when converting a Python string to a tf.float16 value.
The Impact of CVE-2020-5215
The vulnerability can be exploited by malicious actors to disrupt services by sending data points containing strings instead of tf.float16 values, leading to potential denial of service in inference/training scenarios.
Technical Details of CVE-2020-5215
This section provides detailed technical information about the vulnerability in TensorFlow.
Vulnerability Description
The issue arises when converting a Python string to a tf.float16 value in TensorFlow versions before 1.15.2 and 2.0.1, resulting in a segmentation fault in eager mode.
Affected Systems and Versions
- Affected versions: < 1.15.2, = 2.0.0
Exploitation Mechanism
- Attack Complexity: HIGH
- Attack Vector: LOCAL
- Privileges Required: LOW
- User Interaction: REQUIRED
- Scope: CHANGED
- CVSS Base Score: 5 (MEDIUM)
Mitigation and Prevention
To address CVE-2020-5215 and enhance security, users are advised to take the following steps:
Immediate Steps to Take
- Upgrade to TensorFlow 1.15.1, 2.0.1, or 2.1.0 to mitigate the vulnerability.
Long-Term Security Practices
- Regularly update TensorFlow to the latest versions to ensure security patches are applied.
Patching and Updates
- Apply patches provided by TensorFlow to address the vulnerability.