CVE-2026-26075 is a medium-severity Cross-Site Request Forgery (CSRF) vulnerability identified in labring's FastGPT platform, an AI Agent building tool that facilitates automated data acquisition through web page and HTTP nodes. These nodes initiate requests to servers to collect data, but due to insufficient CSRF protections, an attacker can craft malicious web requests that cause the FastGPT server to execute unintended actions without the user's consent. The vulnerability stems from the platform's handling of internal network requests and lack of robust CSRF tokens or validation mechanisms. To mitigate risk, FastGPT's deployment environment employs internal network isolation and enhanced detection of internal network addresses, reducing the attack surface. The vulnerability affects all versions prior to 4.14.7, where the issue has been fixed. The CVSS 4.0 vector indicates the attack can be performed remotely over the network without authentication or user interaction, but the impact on confidentiality and integrity is limited, and availability is unaffected. No public exploits have been reported, but the vulnerability could allow attackers to manipulate server-side processes or data acquisition workflows, potentially leading to unauthorized data access or manipulation within the AI platform's operational context.

The primary impact of this CSRF vulnerability is the potential for unauthorized commands to be executed on the FastGPT platform by an attacker who tricks an authenticated user into visiting a malicious website. This could lead to unauthorized data acquisition requests or manipulation of AI agent behaviors, potentially compromising data integrity and operational reliability. While confidentiality impact is limited, attackers might leverage this to alter data collection processes or inject malicious data, affecting downstream AI outputs. Organizations relying on FastGPT for critical AI workflows could face disruptions or data corruption. Since the vulnerability requires no authentication or user interaction, it poses a moderate risk especially in environments where FastGPT is exposed to untrusted networks or users. The lack of known exploits reduces immediate threat but does not eliminate future risk, particularly as FastGPT adoption grows in AI development sectors.

Organizations should immediately upgrade all FastGPT instances to version 4.14.7 or later, where the vulnerability is patched. In addition, deployments should enforce strict internal network isolation to limit exposure of FastGPT nodes to untrusted networks. Implementing web application firewalls (WAFs) with CSRF detection rules can provide an additional layer of defense. Administrators should audit and restrict access to FastGPT management interfaces, ensuring they are not publicly accessible. Monitoring network traffic for unusual or unauthorized data acquisition requests can help detect exploitation attempts. Developers should verify that all state-changing requests in FastGPT require valid anti-CSRF tokens and consider adopting security headers such as SameSite cookies to mitigate CSRF risks. Regular security assessments and penetration testing focused on CSRF and related web vulnerabilities are recommended to maintain a robust security posture.