Executive Summary

This vulnerability exists in the langflow-ai langflow software up to version 1.8.3, specifically in the function create_project/encrypt_auth_settings within the Project Creation Endpoint component. The issue arises because the argument auth_settings is manipulated in a way that causes sensitive authentication settings to be stored in cleartext on disk or in a file. This means that confidential information is not properly encrypted and can be accessed by unauthorized parties.

The vulnerability can be exploited remotely, allowing attackers to potentially access sensitive authentication data without needing physical access to the system.

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Impact Analysis

The impact of this vulnerability is that sensitive authentication settings may be exposed in cleartext, which can lead to unauthorized access to systems or data. Attackers exploiting this vulnerability could gain access to authentication credentials or other sensitive information stored by the application, potentially compromising the security of the affected system.

Since the exploit can be launched remotely, it increases the risk of unauthorized access without physical presence, making it easier for attackers to compromise the system.

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Compliance Impact

This vulnerability involves the cleartext storage of authentication settings on disk, which can lead to unauthorized access to sensitive information if exploited.

Such insecure handling of authentication data may impact compliance with standards and regulations like GDPR and HIPAA, which require protection of sensitive data and proper security controls to prevent unauthorized access.

However, specific impacts on compliance are not detailed in the provided information.

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Detection Guidance

This vulnerability can be detected by inspecting the stored project data for plaintext sensitive authentication credentials, especially in the auth_settings field. Since the vulnerability involves cleartext storage of sensitive fields like passwords or secret tokens, you can query the project retrieval API endpoint to check if such fields are returned unencrypted.

A practical approach is to create a project with known sensitive auth_settings (e.g., a password) and then retrieve the project data via the API to see if the sensitive data is stored and returned in plaintext.

Example commands to detect the vulnerability might include:

• Use curl or similar tools to create a project with sensitive auth_settings, e.g.: curl -X POST http://<langflow-host>/api/v1/projects -H 'Content-Type: application/json' -d '{"auth_settings": {"db_password": "SECRET123"}, "other_project_data": "..."}'
• Retrieve the project data and check if the sensitive field is returned in plaintext: curl http://<langflow-host>/api/v1/projects/<project_id>

If the sensitive fields like db_password appear unencrypted in the response, the vulnerability is present.

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Mitigation Strategies

Immediate mitigation steps include avoiding the storage of sensitive authentication credentials in the vulnerable versions of Langflow, especially in the auth_settings field.

Since the vulnerability arises from incomplete encryption of sensitive fields, you should:

• Avoid using or storing sensitive fields that are not covered by the encryption allowlist (e.g., passwords, secret tokens) until a patch or update is available.
• Restrict access to the Langflow database and API endpoints to trusted and authenticated users only, minimizing exposure risk.
• Monitor for updates or patches from the vendor or community that address the encryption shortcomings and apply them as soon as they become available.

If possible, consider encrypting sensitive data before submitting it to the Langflow system as a temporary workaround.

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