CVE-2026-67926 in JeecgBoot
Summary
by MITRE • 08/18/2026
An issue in JeecgBoot v.3.9.2 allows a remote attacker to execute arbitrary code via the files Parameter in JeecgBoot AI Chat Module
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Analysis
by VulDB Data Team • 08/18/2026
The vulnerability identified in JeecgBoot version 3.9.2, specifically within its integrated AI Chat module, represents a critical server-side security flaw that permits Remote Code Execution (RCE). This issue stems from improper validation and sanitization of user-supplied input passed through the files parameter mechanism. In modern web applications utilizing large language model integrations or similar interactive modules, file uploads are often processed to extract context for AI responses. However, in this specific implementation, the system fails to adequately restrict the types of files accepted or properly sanitize the content before processing. This oversight allows a remote attacker to craft malicious requests that bypass standard security controls, effectively injecting executable code into the server environment through the guise of legitimate file uploads intended for the chat interface.
From a technical perspective, this vulnerability is classified under CWE-94 as Improper Control of Generation of Code (Code Injection). The root cause lies in the backend handling logic where user-controlled data from the files parameter is directly utilized without sufficient isolation or sandboxing. When an attacker submits a specially crafted file payload, such as a script disguised with a benign extension or containing obfuscated executable content, the application processes this input and executes it within the server's runtime context. This bypasses typical web application firewalls because the request appears to be a standard multipart form-data upload rather than a direct command injection attempt. The lack of strict file type whitelisting and insufficient inspection of file contents creates an attack vector that exploits trust in user-provided data, leading to arbitrary code execution with the privileges of the underlying application process.
The operational impact of this vulnerability is severe, as it grants attackers full control over the affected server infrastructure. Once remote code execution is achieved, malicious actors can perform a wide range of destructive activities including but not limited to stealing sensitive data such as user credentials and proprietary business information, installing backdoors for persistent access, pivoting to other systems within the internal network, or deploying ransomware that encrypts critical files. Given that JeecgBoot is often used in enterprise environments for rapid application development, this vulnerability poses a significant risk to organizations relying on it for mission-critical applications. The ability to execute code remotely means that even if the web interface is not directly exposed to the public internet, any internal service exposing the AI chat module remains vulnerable to exploitation by authenticated or unauthenticated users depending on the specific deployment configuration and access controls in place.
To mitigate this risk, immediate action is required to update JeecgBoot to a patched version where these input validation mechanisms have been hardened. In addition to upgrading software, organizations should implement defense-in-depth strategies such as deploying Web Application Firewalls configured to detect anomalous file upload patterns and blocking known malicious payloads. It is also crucial to enforce strict file type restrictions on the server side using MIME type verification rather than relying solely on client-side checks or file extensions. Furthermore, running the application with least privilege principles ensures that even if an exploit succeeds, the potential damage is contained by limiting the permissions of the process executing the code. Regular security audits and penetration testing focused on AI module integrations can help identify similar vulnerabilities before they are exploited in production environments.
This incident highlights the growing attack surface associated with integrating artificial intelligence components into traditional enterprise software frameworks. As developers increasingly adopt low-code platforms like JeecgBoot to accelerate development cycles, ensuring that third-party modules undergo rigorous security review is paramount. The vulnerability aligns with MITRE ATT&CK technique T1059 Command and Scripting Interpreter, as it allows attackers to execute commands via the application's backend logic. By understanding these patterns, security teams can better monitor for indicators of compromise related to unusual file processing activities within AI chat interfaces and other dynamic content handlers.