CVE-2025-68700 is an OS command injection vulnerability classified under CWE-78 found in the open-source Retrieval-Augmented Generation (RAG) engine RAGFlow, specifically in versions prior to 0.23.0. The vulnerability stems from the frontend Canvas CodeExec component, which is designed to convert string results into Python objects by parsing stdout using the eval() function without proper filtering or sandboxing. This unsafe use of eval() on untrusted data allows a low-privileged authenticated user to execute arbitrary system commands on the server hosting the RAGFlow process, effectively bypassing intended sandbox isolation. The vulnerability is further aggravated by additional API endpoints that either lack proper access control or have inverted permission logic, significantly broadening the attack surface and enabling attackers to chain exploits for greater impact. The flaw allows attackers to escalate privileges and execute arbitrary code, potentially leading to full system compromise, data exfiltration, or disruption of services. The vulnerability has a CVSS 4.0 score of 8.6, indicating high severity, with network attack vector, low attack complexity, no user interaction, and partial requirements for privileges. The issue was publicly disclosed on December 31, 2025, and patched in RAGFlow version 0.23.0. No known exploits have been reported in the wild yet, but the nature of the vulnerability and ease of exploitation make it a critical concern for users of affected versions.

For European organizations, the impact of CVE-2025-68700 can be severe, especially for those leveraging RAGFlow in AI-driven data retrieval, natural language processing, or other critical business applications. Successful exploitation allows attackers to execute arbitrary commands on the server, leading to potential full system compromise, unauthorized data access or modification, disruption of AI services, and lateral movement within the network. This can result in significant operational downtime, data breaches involving sensitive or regulated information, and reputational damage. Organizations in sectors such as finance, healthcare, government, and critical infrastructure that rely on RAGFlow for data augmentation or AI workflows are particularly at risk. The vulnerability’s ability to bypass sandboxing and exploit weak access controls increases the likelihood of chained attacks, amplifying the potential damage. Given the high severity and network-based exploitation, attackers can remotely compromise systems without user interaction, making timely remediation critical to prevent widespread impact.

To mitigate CVE-2025-68700, European organizations should immediately upgrade all RAGFlow deployments to version 0.23.0 or later, which contains the official patch addressing the unsafe eval() usage and access control issues. In addition to patching, organizations should conduct a comprehensive audit of all RAGFlow endpoints to verify proper access control enforcement and correct any inverted permission logic. Implement strict input validation and sanitization on all user-supplied data, especially in components that execute or parse code. Employ network segmentation and least privilege principles to limit the exposure of RAGFlow servers. Monitor logs and system behavior for unusual command execution patterns indicative of exploitation attempts. Consider deploying runtime application self-protection (RASP) or endpoint detection and response (EDR) solutions to detect and block malicious command execution. Finally, establish incident response procedures tailored to potential RAGFlow compromises and ensure backups are current to enable recovery from any successful attacks.