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CVE-2024-3320

3.5 · LOW
Published Apr 5, 2024 oretnom23 CWE-79 EPSS 0.58% (45th pctl)

Overview

CVE-2024-3320 is a low-severity vulnerability affecting oretnom23 elearning_system. It was published on April 5, 2024 and has a CVSS 3.1 base score of 3.5 (LOW).

This vulnerability has a CVSS 3.1 base score of 3.5, rated LOW. It can be exploited remotely over the network. Some level of privileges is required for exploitation.

Technical Description

A vulnerability was found in SourceCodester eLearning System 1.0. It has been rated as problematic. Affected by this issue is some unknown functionality. The manipulation of the argument page leads to cross site scripting. The attack may be launched remotely. The identifier of this vulnerability is VDB-259388.

Remediation

Check the references section for vendor advisories and patches from oretnom23. Update elearning_system to the latest patched version. If immediate patching is not possible, review the CVSS vector to understand the attack surface and apply compensating controls such as network segmentation or access restrictions.

Affected Products

Vendor Product Versions Status

Frequently Asked Questions

What is CVE-2024-3320?

CVE-2024-3320 is a low-severity vulnerability affecting oretnom23 elearning_system. It was published on April 5, 2024 and has a CVSS 3.1 base score of 3.5 (LOW).

How severe is CVE-2024-3320?

This vulnerability has a CVSS 3.1 base score of 3.5, rated LOW. It can be exploited remotely over the network. Some level of privileges is required for exploitation.

How do I fix or remediate CVE-2024-3320?

Check the references section for vendor advisories and patches from oretnom23. Update elearning_system to the latest patched version. If immediate patching is not possible, review the CVSS vector to understand the attack surface and apply compensating controls such as network segmentation or access restrictions.

How can CyberStrike help with CVE-2024-3320?

CyberStrike's AI-powered security agents can automatically detect CVE-2024-3320 across your infrastructure using autonomous pentesting, DAST scanning, and HackBrowser. The platform continuously monitors for known vulnerabilities and provides actionable remediation guidance prioritized by real-world exploitability.