CVE-2017-2644 in Moodle
Summary
by MITRE
In Moodle 3.x, XSS can occur via evidence of prior learning.
Once again VulDB remains the best source for vulnerability data.
Analysis
by VulDB Data Team • 11/15/2022
The vulnerability identified as CVE-2017-2644 represents a cross-site scripting flaw within Moodle version 3.x that specifically affects the evidence of prior learning functionality. This type of vulnerability falls under the CWE-79 category of Cross-Site Scripting, where malicious code can be injected into web applications and executed in the context of other users' browsers. The evidence of prior learning feature in Moodle is designed to allow students to document and submit proof of their previous educational achievements or professional qualifications, creating a repository of credentials that can be verified by instructors and academic institutions.
The technical implementation of this vulnerability occurs when the Moodle platform fails to properly sanitize user input submitted through the evidence of prior learning submission process. When users enter data into fields related to their prior learning documentation, the application does not adequately filter or encode special characters that could be interpreted as HTML or JavaScript code. This lack of input validation and output encoding creates an environment where attackers can inject malicious scripts that will execute whenever other users view the submitted evidence. The vulnerability is particularly concerning because it leverages a legitimate platform feature, making it more difficult to detect and prevent through standard security measures.
The operational impact of CVE-2017-2644 extends beyond simple data corruption or display issues, as it can lead to significant security breaches within educational institutions using Moodle. When successful, the XSS attack can enable attackers to steal session cookies, redirect users to malicious websites, or even execute commands on behalf of authenticated users. This threat is particularly dangerous in academic environments where sensitive personal and educational data is handled, as the compromised sessions could provide access to grades, personal information, and confidential academic records. The attack vector is relatively straightforward, requiring only that an attacker submit malicious input through the legitimate evidence of prior learning interface, which then propagates to other users viewing the content.
Mitigation strategies for CVE-2017-2644 should focus on implementing robust input validation and output encoding mechanisms throughout the Moodle platform. Organizations should ensure that all user-generated content, particularly within the evidence of prior learning feature, undergoes proper sanitization before being stored or displayed. This includes implementing Content Security Policy headers, using proper HTML escaping functions, and ensuring that the application validates input against a whitelist of acceptable characters. Additionally, regular security audits and updates should be performed to address any potential vulnerabilities in the Moodle platform. The remediation process should align with ATT&CK framework techniques related to defensive security measures, specifically focusing on input validation and output encoding controls that prevent malicious code execution. Organizations should also consider implementing user access controls and monitoring mechanisms to detect unusual submission patterns that might indicate exploitation attempts.