CVE-2025-52656 is a high-severity vulnerability affecting HCL MyXalytics version 6.6, categorized under CWE-915 (Improperly Controlled Modification of Dynamically-Determined Object Attributes), commonly known as a Mass Assignment vulnerability. This vulnerability arises when user-supplied input is automatically bound to application objects without sufficient validation or access control checks. In this scenario, attackers can manipulate input parameters to modify sensitive object fields that should otherwise be protected, potentially leading to unauthorized changes in application state or data. The vulnerability is remotely exploitable over the network (AV:N), requires no privileges (PR:N), but does require some user interaction (UI:R). The scope is unchanged (S:U), meaning the impact is confined to the vulnerable component. The CVSS v3.1 base score is 7.6, reflecting a high severity due to the combination of ease of exploitation and the potential impact on integrity and availability. Specifically, the vulnerability allows an attacker to cause low confidentiality impact (some information disclosure or data exposure), high integrity impact (unauthorized modification of data or application behavior), and low availability impact (minor disruption). Although no known exploits are currently reported in the wild, the nature of mass assignment vulnerabilities makes them attractive targets for attackers seeking to escalate privileges or manipulate application logic. Since HCL MyXalytics is an analytics platform used for data-driven decision-making, unauthorized modifications could lead to corrupted analytics data, misleading reports, or unauthorized access to sensitive business information. The lack of available patches at the time of publication increases the urgency for organizations to implement interim mitigations and monitor for suspicious activity.

For European organizations using HCL MyXalytics 6.6, this vulnerability poses significant risks to data integrity and trustworthiness of analytics outputs. Compromised analytics data can lead to flawed business decisions, regulatory non-compliance (especially under GDPR if personal data is involved), and potential reputational damage. Attackers exploiting this vulnerability could manipulate reports or dashboards, potentially masking fraudulent activities or causing operational disruptions. Given the high integrity impact, critical business processes relying on accurate analytics could be undermined. Additionally, unauthorized changes could expose sensitive internal metrics or strategic information, impacting confidentiality to a lesser extent. The requirement for user interaction suggests phishing or social engineering could be vectors, emphasizing the need for user awareness. The vulnerability's network accessibility means attackers can attempt exploitation remotely, increasing the threat surface. European organizations in sectors such as finance, manufacturing, retail, and government—where HCL MyXalytics might be deployed—are particularly at risk due to the strategic importance of analytics in these industries.

1. Immediate mitigation should include implementing strict input validation and access control at the application layer to prevent unauthorized binding of user input to sensitive object fields. 2. Employ web application firewalls (WAFs) with custom rules to detect and block suspicious parameter tampering indicative of mass assignment attempts. 3. Conduct thorough code reviews and security testing focusing on object binding mechanisms to identify and remediate insecure mass assignment patterns. 4. Restrict user permissions and roles within HCL MyXalytics to the principle of least privilege, minimizing the impact of any successful exploitation. 5. Monitor application logs and analytics for unusual changes or anomalies that could indicate exploitation attempts. 6. Educate users about phishing and social engineering risks, as user interaction is required for exploitation. 7. Coordinate with HCL for timely patch releases and apply updates as soon as they become available. 8. Consider isolating or segmenting the analytics environment to limit exposure and potential lateral movement in case of compromise.