CVE-2023-28331 in Moodle
Summary
by MITRE • 03/23/2023
Content output by the database auto-linking filter required additional sanitizing to prevent an XSS risk.
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Analysis
by VulDB Data Team • 07/06/2025
The vulnerability identified as CVE-2023-28331 represents a cross-site scripting weakness within database auto-linking filter functionality that processes content output. This flaw resides in the insufficient sanitization of data generated by the auto-linking mechanism, which automatically identifies and converts text patterns into hyperlinks. The vulnerability specifically affects systems where database content undergoes automatic hyperlink generation without proper input validation and output encoding measures. When the auto-linking filter processes user-supplied or dynamic content, it fails to adequately sanitize the output before rendering it in web interfaces, creating an avenue for malicious actors to inject harmful scripts.
The technical implementation of this vulnerability stems from inadequate security controls in the content processing pipeline where the auto-linking filter operates. The filter typically scans text for patterns such as URLs, email addresses, or other identifiable elements and automatically converts them into clickable links. However, the sanitization process that occurs after this conversion is insufficient to prevent malicious script injection. This weakness allows attackers to craft input data that, when processed by the auto-linking filter, results in executable code being embedded within the rendered output. The vulnerability manifests when the system fails to properly encode special characters or validate the content of automatically generated links, particularly in contexts where the output is directly rendered in web browsers without additional security layers.
The operational impact of CVE-2023-28331 extends beyond simple script execution as it represents a critical security gap that could enable various attack vectors within web applications. An attacker could leverage this vulnerability to execute malicious JavaScript code within the context of authenticated users' browsers, potentially leading to session hijacking, data theft, or privilege escalation. The risk is particularly severe in applications where users can submit content that gets processed through the auto-linking filter, as this creates multiple entry points for exploitation. The vulnerability could be exploited through various means including user-generated content submissions, database entries, or any input that passes through the affected filtering mechanism. This type of vulnerability falls under the CWE-79 category of Cross-Site Scripting, specifically addressing the improper neutralization of input during web page generation.
Mitigation strategies for CVE-2023-28331 must focus on implementing robust input validation and output encoding mechanisms throughout the content processing pipeline. Organizations should ensure that all auto-linking filters employ comprehensive sanitization routines that properly encode special characters and validate content before rendering. The implementation should follow established security practices such as context-aware encoding, where output is encoded according to the specific context in which it will be rendered, whether HTML, JavaScript, or CSS. Additionally, the security controls should include proper content validation to prevent malicious patterns from being processed through the auto-linking mechanism. This vulnerability aligns with ATT&CK technique T1203 - Exploitation for Client Execution, where attackers leverage web application vulnerabilities to execute malicious code in user browsers. The remediation process should involve comprehensive code review of all auto-linking functionality, implementation of proper security libraries for output encoding, and regular security testing to prevent similar issues in future development cycles.