CVE-2025-53927 is a medium severity vulnerability classified under CWE-94 (Improper Control of Generation of Code, commonly known as code injection) affecting versions of the open-source AI assistant MaxKB prior to 2.0.0. MaxKB is developed by 1Panel-dev and is designed for enterprise use. The vulnerability arises from an inadequate sandbox design that attempts to restrict executable file permissions only within a specific directory. However, this restriction can be bypassed because MaxKB allows the use of Python's shutil.copy2 method to copy arbitrary commands or files into the executable directory. This bypass enables an attacker to execute arbitrary code, potentially establishing a reverse shell on the affected system. The vulnerability requires low privileges (PR:L) and user interaction (UI:R), with a network attack vector (AV:N) but high attack complexity (AC:H). The impact on confidentiality, integrity, and availability is low to medium, as indicated by the CVSS score of 4.6. The issue was resolved in MaxKB version 2.0.0 by improving sandbox restrictions to prevent such directory bypasses and unauthorized code execution. No known exploits are currently reported in the wild, but the vulnerability presents a risk if exploited, especially in enterprise environments where MaxKB is deployed.

For European organizations, this vulnerability could lead to unauthorized code execution within enterprise AI assistant environments, potentially allowing attackers to gain a foothold in internal networks. Although the CVSS score is medium, the ability to execute arbitrary commands and establish reverse shells could facilitate lateral movement, data exfiltration, or disruption of AI assistant services. Enterprises relying on MaxKB for sensitive or critical operations may face confidentiality breaches or service interruptions. The requirement for user interaction and low privileges somewhat limits the ease of exploitation; however, social engineering or insider threats could still trigger attacks. Given the increasing adoption of AI assistants in business workflows across Europe, exploitation could impact productivity and data security, especially in sectors like finance, healthcare, and government where AI assistants may handle sensitive information.

European organizations using MaxKB should immediately upgrade to version 2.0.0 or later, where the sandbox bypass vulnerability is fixed. Until upgrading, organizations should implement strict access controls to limit user permissions on systems running MaxKB, preventing unauthorized file copying or execution. Network segmentation should isolate AI assistant environments from critical infrastructure to contain potential breaches. Monitoring for unusual file operations involving shutil.copy2 or unexpected executable file creation in restricted directories can help detect exploitation attempts. Additionally, user training to recognize social engineering attempts that could trigger user interaction-based exploits is essential. Employing application whitelisting and endpoint detection and response (EDR) tools can further reduce risk by blocking unauthorized code execution and alerting on suspicious activities related to MaxKB.