CVE-2025-43854 is a clickjacking vulnerability identified in the langgenius DIFY platform, an open-source application development environment for large language models (LLMs). The vulnerability affects all versions prior to 1.3.0 of DIFY. Clickjacking occurs when an attacker tricks a user into clicking on hidden or disguised UI elements by overlaying transparent or misleading frames or layers on a legitimate web page. In this case, the improper restriction of rendered UI layers or frames (CWE-1021) allows malicious actors to embed the DIFY application interface within an attacker-controlled frame, deceiving users into performing unintended actions without their knowledge or consent. These unauthorized clicks can lead to execution of sensitive operations, potentially compromising user security and privacy. The vulnerability requires no prior authentication but does require user interaction (clicking). The CVSS 4.0 base score is 2.3, reflecting a low severity due to limited impact on confidentiality, integrity, and availability, and the necessity of user interaction. The issue has been addressed and fixed in version 1.3.0 of DIFY. There are no known exploits in the wild at this time. Given that DIFY is a platform for developing LLM applications, exploitation could indirectly affect the integrity of applications built on it if users are tricked into unintended actions during development or deployment phases.

For European organizations utilizing the DIFY platform (versions prior to 1.3.0), this vulnerability could lead to unauthorized actions being performed on their LLM app development environment. While the direct impact is limited due to the low severity and requirement for user interaction, successful exploitation could result in compromised development workflows, inadvertent configuration changes, or exposure of sensitive development data. This could undermine the integrity of AI applications under development, potentially leading to flawed or malicious AI behavior once deployed. Organizations in sectors with high reliance on AI and LLMs—such as finance, healthcare, and critical infrastructure—may face increased risk if attackers leverage clickjacking to manipulate development environments. However, the absence of known exploits and the low CVSS score suggest the immediate risk is limited. The vulnerability does not affect confidentiality or availability directly, but the integrity of development processes could be impacted if exploited.

1. Upgrade all instances of the DIFY platform to version 1.3.0 or later immediately to ensure the clickjacking vulnerability is patched. 2. Implement Content Security Policy (CSP) headers with frame-ancestors directives to restrict which domains can embed the DIFY application, preventing unauthorized framing. 3. Use X-Frame-Options HTTP headers (e.g., DENY or SAMEORIGIN) as an additional layer to block framing by untrusted sources. 4. Educate developers and users of the platform about the risks of clickjacking and encourage vigilance when interacting with embedded or framed content. 5. Monitor web application logs for suspicious framing attempts or unusual user interactions that could indicate exploitation attempts. 6. For organizations deploying DIFY-based applications, conduct security reviews of the UI to ensure no additional clickjacking vectors exist. 7. Employ browser security features and extensions that can detect or block clickjacking attempts during development and testing phases.