CVE-2025-59417 is a cross-site scripting (XSS) vulnerability identified in the open-source AI chat framework lobe-chat, specifically affecting versions prior to 1.129.4. The vulnerability arises from improper neutralization of input during web page generation (CWE-79). In lobe-chat, server responses containing <lobeArtifact> nodes are rendered differently based on their type. When the lobeArtifact type is image/svg+xml, the content is rendered using the SVGRender component, which employs React's dangerouslySetInnerHTML to inject SVG content directly into the DOM without sanitization. This unsafe rendering allows malicious SVG content to execute arbitrary JavaScript in the context of the user’s browser, leading to an XSS attack. Exploitation requires an attacker to inject malicious content into chat messages, which can be achieved by hosting a malicious page designed for prompt injection, compromising the Message Control Protocol (MCP) server, or abusing tool integrations that feed content into lobe-chat. The vulnerability can escalate from XSS to remote code execution on the user's machine, significantly increasing the risk. The flaw is fixed in version 1.129.4 of lobe-chat. The CVSS 4.0 base score is 6.8 (medium severity), reflecting network attack vector, high complexity, no privileges required, user interaction needed, and high impact on confidentiality, integrity, and availability. No known exploits are reported in the wild yet.

For European organizations using lobe-chat versions prior to 1.129.4, this vulnerability poses a significant risk. Since lobe-chat is an AI chat framework, it is likely integrated into internal communication, customer support, or AI-driven workflows. Successful exploitation could lead to unauthorized script execution within users’ browsers, enabling data theft, session hijacking, or further malware delivery. The escalation to remote code execution could compromise endpoint security, leading to broader network infiltration, data breaches, or disruption of services. Given the increasing adoption of AI chat tools in European enterprises, especially in sectors like finance, healthcare, and government, the impact could be substantial. Additionally, the vulnerability’s exploitation does not require authentication but does require user interaction, making phishing or social engineering plausible attack vectors. The lack of known exploits currently provides a window for proactive mitigation, but the potential for rapid weaponization exists due to the widespread use of SVG rendering and AI chat frameworks.

European organizations should immediately audit their use of lobe-chat and identify any deployments running versions earlier than 1.129.4. The primary mitigation is to upgrade to version 1.129.4 or later, where the vulnerability is patched. For environments where immediate upgrade is not feasible, organizations should implement strict input validation and sanitization on all chat message inputs, especially those capable of injecting SVG content. Disabling or restricting the rendering of SVG content within chat messages can reduce attack surface. Network-level controls such as Content Security Policy (CSP) headers should be enforced to restrict script execution and mitigate XSS impact. Monitoring and logging chat message content for anomalous or suspicious SVG payloads can aid in early detection. Additionally, organizations should review and secure any MCP servers and tool integrations feeding content into lobe-chat to prevent unauthorized content injection. User awareness training to recognize suspicious chat content and avoid interaction with untrusted messages will further reduce risk.