Flowise 3.0.4 suffers from a critical remote code execution vulnerability that allows attackers to execute arbitrary commands on the server hosting the application. Flowise is a web-based tool used for building AI workflows, and the vulnerability likely stems from insufficient input validation or unsafe deserialization within the web interface or API endpoints. The exploit enables attackers to bypass authentication or leverage existing access to inject and execute malicious code remotely, potentially leading to full system compromise. The availability of a Python-based exploit code on Exploit-DB facilitates rapid weaponization by threat actors. Although no official patches or mitigations have been published, the vulnerability's critical nature and the presence of exploit code indicate a high risk of exploitation. This vulnerability impacts the confidentiality, integrity, and availability of affected systems, as attackers can steal sensitive data, alter workflows, or disrupt services. Organizations relying on Flowise for AI workflow orchestration must urgently assess exposure and implement defensive controls. The lack of a CVSS score requires severity assessment based on impact and exploitability, which is critical in this case.

For European organizations, exploitation of this RCE vulnerability in Flowise 3.0.4 could lead to unauthorized access to sensitive AI workflows and data, disruption of AI-driven business processes, and potential lateral movement within internal networks. Confidential data processed or stored by Flowise could be exfiltrated or manipulated, undermining data integrity and compliance with regulations such as GDPR. The availability of AI services may be compromised, affecting operational continuity. Given the increasing adoption of AI tools in sectors like finance, healthcare, and manufacturing across Europe, the impact could be significant. Attackers could leverage this vulnerability to deploy ransomware, steal intellectual property, or conduct espionage. The presence of exploit code lowers the barrier for attackers, increasing the likelihood of targeted attacks against European entities using Flowise.

Immediate mitigation steps include isolating Flowise instances from public internet exposure and restricting access to trusted networks only. Organizations should implement strict input validation and web application firewalls (WAFs) to detect and block suspicious payloads targeting Flowise endpoints. Monitoring network traffic and logs for unusual activity related to Flowise is critical. Until an official patch is released, consider disabling or limiting features that accept external input or executing workflows remotely. Employ network segmentation to contain potential breaches. Regularly back up AI workflow configurations and data to enable recovery in case of compromise. Engage with Flowise developers or community to obtain updates or patches as soon as they become available. Additionally, conduct penetration testing focused on Flowise to identify and remediate other potential weaknesses.