CVE-2025-49131 is a medium-severity vulnerability affecting labring's FastGPT platform, specifically versions prior to 4.9.11. FastGPT is an open-source framework designed to build, deploy, and operate AI-driven workflows and conversational agents. A critical component of FastGPT is the fastgpt-sandbox, a containerized isolated environment intended to securely execute user-submitted or dynamically generated code. The vulnerability arises from incorrect permission assignment and insufficient sandbox isolation, categorized under CWE-732 (Incorrect Permission Assignment for Critical Resource). Prior to version 4.9.11, the sandbox allowed overly permissive system calls (syscalls), which enabled attackers to escape the sandbox boundaries. This escape permits unauthorized reading and overwriting of arbitrary files on the host system and bypassing of Python module import restrictions, potentially allowing execution of malicious code outside the sandbox. The vulnerability does not require user interaction but does require low privileges (PR:L) on the system. The attack vector is network-based (AV:N), meaning exploitation can occur remotely. The vulnerability impacts confidentiality, integrity, and availability to a limited extent (C:L/I:L/A:L). The patch in version 4.9.11 addresses the issue by restricting allowed syscalls to a safer subset and improving error messaging to prevent sandbox escapes. No known exploits are currently reported in the wild, but the potential for sandbox escape in an AI workflow platform poses a significant risk if left unpatched.

For European organizations, the exploitation of this vulnerability could lead to unauthorized access to sensitive data processed within AI-driven workflows, including intellectual property, personal data, or proprietary algorithms. The ability to overwrite arbitrary files could allow attackers to modify or corrupt critical system or application files, potentially disrupting AI services or causing denial of service. Bypassing Python module import restrictions could enable execution of arbitrary malicious code, leading to further compromise of internal networks or lateral movement. Organizations relying on FastGPT for AI operations in sectors such as finance, healthcare, or critical infrastructure could face data breaches, operational disruptions, and regulatory non-compliance risks under GDPR. The medium severity rating suggests moderate risk, but the nature of sandbox escapes in AI environments could amplify impact if exploited at scale. Given the increasing adoption of AI platforms in Europe, this vulnerability could undermine trust in AI deployments and expose organizations to targeted attacks.

European organizations using FastGPT should immediately upgrade to version 4.9.11 or later to apply the official patch that restricts syscalls and enhances sandbox isolation. Until patching is possible, organizations should implement strict network segmentation to isolate FastGPT environments from sensitive internal networks. Employ runtime monitoring and anomaly detection focused on syscall patterns and file system changes within sandbox containers to detect potential escape attempts. Limit user privileges to the minimum necessary to reduce the risk of exploitation (principle of least privilege). Additionally, enforce strict code review and validation for any user-submitted or dynamically generated code executed within FastGPT to prevent malicious payloads. Consider deploying container security tools that enforce mandatory access controls (e.g., SELinux, AppArmor) to further restrict sandbox capabilities. Regularly audit and monitor logs for unusual access or modification attempts related to FastGPT sandbox environments. Finally, maintain an incident response plan tailored to AI platform compromises.