In lunary-ai/lunary version 1.2.4, an improper access control vulnerability allows members with team management permissions to manipulate project identifiers in requests, enabling them to invite users to projects in other organizations, change members to projects in other organizations with escalated privileges, and change members from other organizations to their own or other projects, also with escalated privileges. This vulnerability is due to the backend's failure to validate project identifiers against the current user's organization ID and projects belonging to it, as well as a misconfiguration in attribute naming (`org_id` should be `orgId`) that prevents proper user organization validation. As a result, attackers can cause inconsistencies on the platform for affected users and organizations, including unauthorized privilege escalation. The issue is present in the backend API endpoints for user invitation and modification, specifically in the handling of project IDs in requests.
In lunary-ai/lunary version 1.2.13, an insufficient granularity of access control vulnerability allows users to create, update, get, and delete prompt variations for datasets not owned by their organization. This issue arises due to the application not properly validating the ownership of dataset prompts and their variations against the organization or project of the requesting user. As a result, unauthorized modifications to dataset prompts can occur, leading to altered or removed dataset prompts without proper authorization. This vulnerability impacts the integrity and consistency of dataset information, potentially affecting the results of experiments.
In lunary-ai/lunary version v1.2.13, an incorrect authorization vulnerability exists that allows unauthorized users to access and manipulate projects within an organization they should not have access to. Specifically, the vulnerability is located in the `checkProjectAccess` method within the authorization middleware, which fails to adequately verify if a user has the correct permissions to access a specific project. Instead, it only checks if the user is part of the organization owning the project, overlooking the necessary check against the `account_project` table for explicit project access rights. This flaw enables attackers to gain complete control over all resources within a project, including the ability to create, update, read, and delete any resource, compromising the privacy and security of sensitive information.
A Server-Side Request Forgery (SSRF) vulnerability exists in the lunary-ai/lunary application, specifically within the endpoint '/auth/saml/tto/download-idp-xml'. The vulnerability arises due to the application's failure to validate user-supplied URLs before using them in server-side requests. An attacker can exploit this vulnerability by sending a specially crafted request to the affected endpoint, allowing them to make unauthorized requests to internal or external resources. This could lead to the disclosure of sensitive information, service disruption, or further attacks against the network infrastructure. The issue affects the latest version of the application as of the report.
A Cross-site Scripting (XSS) vulnerability exists in the SAML metadata endpoint `/auth/saml/${org?.id}/metadata` of lunary-ai/lunary version 1.2.7. The vulnerability arises due to the application's failure to escape or validate the `orgId` parameter supplied by the user before incorporating it into the generated response. Specifically, the endpoint generates XML responses for SAML metadata, where the `orgId` parameter is directly embedded into the XML structure without proper sanitization or validation. This flaw allows an attacker to inject arbitrary JavaScript code into the generated SAML metadata page, leading to potential theft of user cookies or authentication tokens.
In lunary-ai/lunary version 1.2.5, an improper access control vulnerability exists due to a missing permission check in the `GET /v1/users/me/org` endpoint. The platform's role definitions restrict the `Prompt Editor` role to prompt management and project viewing/listing capabilities, explicitly excluding access to user information. However, the endpoint fails to enforce this restriction, allowing users with the `Prompt Editor` role to access the full list of users in the organization. This vulnerability allows unauthorized access to sensitive user information, violating the intended access controls.
An Improper Access Control vulnerability exists in the lunary-ai/lunary repository, affecting versions up to and including 1.2.2. The vulnerability allows unauthorized users to view any prompts in any projects by supplying a specific prompt ID to an endpoint that does not adequately verify the ownership of the prompt ID. This issue was fixed in version 1.2.25.
In lunary-ai/lunary version 1.2.4, an account takeover vulnerability exists due to the exposure of password recovery tokens in API responses. Specifically, when a user initiates the password reset process, the recovery token is included in the response of the `GET /v1/users/me/org` endpoint, which lists all users in a team. This allows any authenticated user to capture the recovery token of another user and subsequently change that user's password without consent, effectively taking over the account. The issue lies in the inclusion of the `recovery_token` attribute in the users object returned by the API.
An improper access control vulnerability exists in the lunary-ai/lunary repository, specifically within the versions.patch functionality for updating prompts. Affected versions include 1.2.2 up to but not including 1.2.25. The vulnerability allows unauthorized users to update prompt details due to insufficient access control checks. This issue was addressed and fixed in version 1.2.25.
An Insecure Direct Object Reference (IDOR) vulnerability was identified in lunary-ai/lunary, affecting versions up to and including 1.2.2. This vulnerability allows unauthorized users to view, update, or delete any dataset_prompt or dataset_prompt_variation within any dataset or project. The issue stems from improper access control checks in the dataset management endpoints, where direct references to object IDs are not adequately secured against unauthorized access. This vulnerability was fixed in version 1.2.25.