CVE-2025-27367 is a medium-severity vulnerability affecting IBM OpenPages with Watson versions 8.3 and 9.0. The vulnerability arises from improper input validation due to reliance on client-side enforcement of server-side security controls. Specifically, the product performs validation of data types and requiredness of fields for Governance, Risk, and Compliance (GRC) Objects on the client side. However, an authenticated user can bypass these client-side validations by sending a specially crafted payload directly to the server. This allows the user to save data without including required fields, violating data integrity rules. The vulnerability is categorized under CWE-602, which refers to Client-Side Enforcement of Server-Side Security, highlighting the risk of trusting client-side controls without adequate server-side validation. The CVSS v3.1 base score is 5.3, reflecting a medium severity level, with the vector indicating network attack vector (AV:N), high attack complexity (AC:H), low privileges required (PR:L), no user interaction (UI:N), unchanged scope (S:U), no confidentiality impact (C:N), high integrity impact (I:H), and no availability impact (A:N). There are no known exploits in the wild at the time of publication, and no patches have been linked yet. The vulnerability could allow malicious insiders or compromised authenticated users to corrupt or manipulate critical GRC data, potentially undermining compliance reporting and risk management processes.

For European organizations, especially those in regulated industries such as finance, healthcare, and critical infrastructure, this vulnerability poses a significant risk to the integrity of governance, risk, and compliance data managed within IBM OpenPages with Watson. Manipulation or omission of required fields in GRC objects can lead to inaccurate compliance reporting, flawed risk assessments, and ultimately regulatory non-compliance, which can result in legal penalties, reputational damage, and financial losses. Since IBM OpenPages is widely used by large enterprises and public sector organizations in Europe for integrated risk management, the impact could be substantial if exploited. The vulnerability requires authenticated access, so the threat is primarily from insider threats or attackers who have obtained legitimate credentials. The absence of confidentiality and availability impacts means data leakage or system downtime is unlikely, but the integrity compromise can severely affect decision-making and audit trails. Organizations relying heavily on automated compliance workflows and reporting may face operational disruptions and increased scrutiny from regulators if data integrity is compromised.

To mitigate this vulnerability, European organizations should implement the following specific measures: 1) Enforce strict server-side validation of all input data for GRC objects, ensuring that required fields and data types are validated independently of client-side controls. 2) Conduct a thorough review and hardening of the IBM OpenPages application configuration to detect and block malformed or incomplete payloads at the server level. 3) Implement enhanced monitoring and alerting on anomalous data submissions or changes to critical GRC data fields, focusing on unusual patterns that bypass normal validation workflows. 4) Restrict and audit user privileges to minimize the number of users with write access to sensitive GRC data, applying the principle of least privilege. 5) Employ multi-factor authentication and session management controls to reduce the risk of credential compromise. 6) Engage with IBM support or security advisories to obtain and apply patches or updates once available. 7) Conduct regular security assessments and penetration testing focused on input validation and data integrity controls within OpenPages. 8) Train administrators and users on the risks of client-side validation bypass and the importance of reporting suspicious behavior. These steps go beyond generic advice by focusing on server-side validation enforcement, privilege management, and anomaly detection tailored to the affected product and vulnerability.