CVE-2023-37528 in BigFix Platform
Summary
by MITRE • 02/03/2024
A cross-site scripting (XSS) vulnerability in the Web Reports component of HCL BigFix Platform can possibly allow an attack to exploit an application parameter during execution of the Save Report.
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Analysis
by VulDB Data Team • 06/04/2025
The vulnerability identified as CVE-2023-37528 represents a critical cross-site scripting flaw within the Web Reports component of the HCL BigFix Platform ecosystem. This vulnerability manifests during the execution of the Save Report functionality, where an attacker can manipulate application parameters to inject malicious scripts into the web application's response. The flaw resides in the platform's insufficient input validation and output encoding mechanisms, creating an avenue for malicious actors to execute arbitrary JavaScript code within the context of a victim's browser session. Such vulnerabilities are particularly dangerous in enterprise environments where privileged users may interact with the BigFix platform for security monitoring and compliance reporting.
The technical exploitation of this XSS vulnerability occurs when an attacker crafts malicious input parameters that are not properly sanitized before being processed by the Web Reports component. The vulnerability specifically impacts the Save Report function, suggesting that when users attempt to save report configurations or data, the platform fails to adequately validate or encode user-supplied input. This allows attackers to inject script tags or other malicious code that executes in the browser of authenticated users who view the compromised report. The flaw operates under CWE-79 which classifies cross-site scripting as a weakness that allows attackers to inject client-side scripts into web applications. The vulnerability's impact is amplified by the fact that it affects a core reporting component that likely handles sensitive operational data and security metrics.
The operational impact of this vulnerability extends beyond simple script execution, potentially enabling attackers to escalate privileges, steal session cookies, redirect users to malicious sites, or access sensitive data within the BigFix platform. In enterprise security environments, where BigFix platforms are used for vulnerability management, compliance monitoring, and security analytics, this vulnerability could allow attackers to gain unauthorized access to critical security information. The attack surface is particularly concerning as it targets the reporting functionality, which typically requires elevated privileges and handles sensitive operational data. Attackers could leverage this vulnerability to perform session hijacking, modify report configurations, or exfiltrate data from the platform. This aligns with ATT&CK technique T1566 which covers social engineering through malicious content delivery, and T1071 which encompasses application layer protocol usage.
Mitigation strategies for CVE-2023-37528 should prioritize immediate patching of the affected HCL BigFix Platform components, as this represents the most effective defense against exploitation. Organizations should implement comprehensive input validation and output encoding measures to prevent script injection attacks, ensuring that all user-supplied parameters are properly sanitized before processing. The platform should enforce strict content security policies that prevent execution of unauthorized scripts, including implementing proper HTTP headers such as Content-Security-Policy. Network segmentation and monitoring should be enhanced to detect potential exploitation attempts, while privileged user access should be restricted through multi-factor authentication and principle of least privilege enforcement. Security teams should conduct thorough penetration testing to identify additional vectors of attack and ensure that the patched environment maintains proper security posture. Regular security assessments should be performed to validate that the vulnerability has been properly addressed and that no similar issues exist within the platform's codebase.