CVE-2025-9225 in MiR Robots
Summary
by MITRE • 08/20/2025
Stored cross-site scripting (XSS) in the web interface of MiR software versions prior to 3.0.0 on MiR Robots and MiR Fleet allows execution of arbitrary JavaScript code in a victim’s browser
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Analysis
by VulDB Data Team • 08/20/2025
The vulnerability identified as CVE-2025-9225 represents a critical stored cross-site scripting flaw within the web interface of MiR software versions prior to 3.0.0 that operates on MiR Robots and MiR Fleet systems. This vulnerability resides in the web application layer of the robot management platform, where user-supplied input is improperly validated and sanitized before being stored and subsequently rendered in web pages. The flaw allows attackers to inject malicious JavaScript code into the application's database through legitimate user interface interactions, which then executes automatically when other users access the affected web interface. This stored nature of the vulnerability means that the malicious payload persists even after the initial injection, making it particularly dangerous as it can affect multiple users over extended periods.
The technical implementation of this vulnerability stems from inadequate input validation and output encoding mechanisms within the MiR software's web interface components. When users interact with the system through web forms, configuration panels, or other input mechanisms, the application fails to properly sanitize user-provided data before storing it in the backend database. The stored data is then retrieved and displayed in web pages without appropriate context-dependent encoding, allowing the injected JavaScript code to execute in the victim's browser context. This vulnerability aligns with CWE-79 which specifically addresses cross-site scripting flaws, and represents a direct violation of secure coding practices that mandate proper input sanitization and output encoding. The attack vector involves an authenticated user with access to the web interface, though the impact extends beyond the immediate user to all other system users who may encounter the malicious content.
The operational impact of CVE-2025-9225 extends beyond simple code execution, as the stored XSS vulnerability creates a persistent threat vector that can be leveraged for various malicious activities. An attacker could potentially steal session cookies, redirect users to malicious sites, deface web interfaces, or even escalate privileges within the robot management system. The vulnerability is particularly concerning in industrial environments where MiR robots are deployed, as it could be exploited to manipulate robot operations, access sensitive operational data, or compromise the integrity of autonomous robot fleets. The persistent nature of stored XSS means that once exploited, the malicious code remains active until manually removed from the database, potentially allowing for long-term surveillance or continued exploitation. This vulnerability directly impacts the CIA triad by compromising confidentiality through data theft, integrity through potential data manipulation, and availability through possible system disruption. From an attack framework perspective, this vulnerability maps to multiple ATT&CK techniques including T1566 for credential access through phishing and T1059 for command and scripting interpreter execution.
Mitigation strategies for CVE-2025-9225 should focus on immediate remediation through upgrading to MiR software version 3.0.0 or later, which contains the necessary patches to address the stored XSS vulnerability. Organizations should implement comprehensive input validation mechanisms that sanitize all user-supplied data before storage, employ context-dependent output encoding for all dynamic content, and establish robust web application firewall rules to detect and block suspicious payloads. Additional protective measures include implementing strict access controls to limit user privileges, conducting regular security assessments of the web interface components, and establishing monitoring procedures to detect potential exploitation attempts. Network segmentation and intrusion detection systems should be deployed to monitor for unusual traffic patterns that may indicate exploitation attempts. The vulnerability highlights the importance of maintaining up-to-date software versions and implementing defense-in-depth strategies that protect against both known and emerging threats in industrial automation environments. Organizations should also consider implementing regular security training for personnel who interact with the MiR systems to reduce the risk of social engineering attacks that could lead to exploitation of this vulnerability.