FlowiseAI Exposes Basic Auth Credentials via API

FlowiseAI, a low-code platform for building AI applications, contains a vulnerability in its basic authentication mechanism. Specifically, the checkBasicAuth endpoint validates credentials in plaintext without rate limiting, making it susceptible to brute-force attacks. The vulnerability, present in versions 3.1.1 and earlier, stems from the lack of rate limiting and the use of non-constant time comparison. The endpoint also returns distinct messages for successful and failed attempts, enabling attackers to enumerate valid usernames. Exploitation allows unauthorized access to the application’s functionalities and data.

Attack Chain

1. Attacker identifies the checkBasicAuth endpoint, typically /api/v1/checkBasicAuth, which is used for basic authentication.
2. The attacker crafts an HTTP POST request to the checkBasicAuth endpoint, including a username and password in the request body.
3. The server receives the request and retrieves the username and password from the request body.
4. The server compares the provided username and password directly with the values stored in the FLOWISE_USERNAME and FLOWISE_PASSWORD environment variables using the JavaScript === operator.
5. If the credentials match, the server responds with a JSON message indicating “Authentication successful”.
6. If the credentials do not match, the server responds with a different JSON message indicating “Authentication failed”. This allows enumeration.
7. The attacker iteratively sends multiple requests with different username and password combinations, exploiting the lack of rate limiting to brute-force the credentials.
8. Upon successful authentication, the attacker gains unauthorized access to the FlowiseAI application and its resources.

Impact

Successful exploitation of this vulnerability allows attackers to bypass authentication and gain unauthorized access to FlowiseAI applications. This can lead to data breaches, unauthorized modification of AI workflows, and potential compromise of sensitive information processed by the AI models. Given the lack of rate limiting, even relatively weak passwords can be compromised through brute-force attacks. This issue affects FlowiseAI installations up to version 3.1.1.

Recommendation

• Implement rate limiting on the /api/v1/checkBasicAuth endpoint to prevent brute-force attacks.
• Deploy the Sigma rule “Detect FlowiseAI Basic Auth Brute Force Attempts” to identify suspicious activity on the vulnerable endpoint.
• Modify the authentication logic to use constant-time comparison functions to mitigate timing attacks, as described in the overview section of this brief.
• Change the application to return generic error messages to prevent username enumeration, as described in the overview section of this brief.
• Upgrade FlowiseAI to a version beyond 3.1.1 where this vulnerability is resolved.