Executive brief
FlowiseAI, an open-source tool for building LLM applications, contains a security flaw in its authentication system. Attackers can perform unlimited login attempts to guess administrative credentials because the system lacks rate limiting and uses insecure comparison methods. If successful, an attacker could gain full access to the application and its configured AI workflows.
Technical details
The `checkBasicAuth` endpoint in `account.controller.ts` validates credentials by comparing plaintext request body values directly against environment variables using the JavaScript `===` operator. This implementation lacks rate limiting, enabling high-speed brute-force attacks, and is susceptible to timing attacks because the comparison is not constant-time. Additionally, the endpoint returns distinct success and failure messages, allowing for credential enumeration. An attacker can exploit these weaknesses to gain unauthorized access to the Flowise server. The vulnerability is addressed in version 3.1.2.
Affected products
- FlowiseAI flowise <= 3.1.1
Timeline
- 2026-05-14: disclosed
- 2026-05-14: advisory
- 2026-05-14: patched: Fixed in version 3.1.2
References
- https://api.github.com/users/kolega-ai-dev
- https://github.com/kolega-ai-dev
- https://api.github.com/users/kolega-ai-dev/gists%7B/gist_id%7D
- https://api.github.com/users/kolega-ai-dev/repos
- https://avatars.githubusercontent.com/u/250560052?v=4
- https://api.github.com/users/kolega-ai-dev/events%7B/privacy%7D