CVE-2026-47408 in PraisonAI
Summary
by MITRE • 07/21/2026
PraisonAI Platform is the platform layer for the PraisonAI multi-agent teams system. Versions prior to 0.1.4 have an Insecure Direct Object Reference. The `GET /workspaces/{workspace_id}/issues/{issue_id}/activity` endpoint is gated by `require_workspace_member(workspace_id)` and dispatches to `ActivityService.list_for_issue(issue_id)`, which executes `SELECT * FROM activity WHERE issue_id = :issue_id` with no workspace constraint. A user who is a member of any workspace can read the full activity log of any issue across the entire multi-tenant deployment. PraisonAI Platform version 0.1.4 patches the issue.
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Analysis
by VulDB Data Team • 07/21/2026
The PraisonAI Platform vulnerability represents a critical Insecure Direct Object Reference flaw that undermines the multi-tenant security model of the system. This weakness allows unauthorized access to sensitive data by bypassing proper authorization checks within the platform's API endpoints. The vulnerability specifically affects versions prior to 0.1.4 and stems from a fundamental design flaw in how the activity logging service handles issue-related requests. When users make requests to the `GET /workspaces/{workspace_id}/issues/{issue_id}/activity` endpoint, the system correctly validates that the user belongs to the specified workspace but fails to enforce proper access controls when retrieving activity logs for specific issues.
The technical implementation of this vulnerability occurs at the database query level where the ActivityService.list_for_issue method executes a direct SQL query without applying any workspace constraints. This query structure `SELECT * FROM activity WHERE issue_id = :issue_id` processes all activity records associated with a given issue regardless of which workspace owns that issue, effectively creating a cross-tenant data leakage scenario. The flaw demonstrates poor adherence to the principle of least privilege and violates fundamental security concepts that should prevent users from accessing resources outside their designated access boundaries. This issue maps directly to CWE-284 which defines Insecure Direct Object Reference as an access control vulnerability where the application provides direct access to objects based on user-supplied input without proper authorization checks.
The operational impact of this vulnerability extends beyond simple data exposure to encompass significant risks for multi-tenant deployments. Any authenticated user within the system can traverse the entire activity log of any issue across all workspaces, potentially accessing sensitive project information, team communications, development activities, and other confidential data that should remain isolated within specific workspace boundaries. This breach compromises the core tenets of multi-tenancy by allowing data cross-contamination between different organizational units or projects that should be completely isolated from each other. The vulnerability particularly affects organizations using PraisonAI for collaborative development environments where different teams or clients might share the same platform instance but require complete data separation.
The security implications of this vulnerability align with several ATT&CK framework techniques including T1087 for account access and T1566 for credential harvesting, as unauthorized users could potentially exploit this flaw to gather intelligence about other workspaces and their activities. The lack of proper workspace constraints in the database query execution creates an information disclosure risk that could enable attackers to map out project structures, identify sensitive issues, and understand development workflows across multiple teams. Organizations relying on PraisonAI for collaborative AI development may face compliance violations if their data handling practices do not meet regulatory requirements for data isolation and access control. The patch implemented in version 0.1.4 addresses this issue by enforcing proper workspace boundaries during activity log retrieval, ensuring that database queries include appropriate workspace constraints to maintain tenant isolation.
Mitigation strategies should focus on implementing robust access control mechanisms throughout the platform's API layer, including proper validation of user permissions before executing any data retrieval operations. Organizations should enforce comprehensive input validation and implement proper database query parameterization techniques to prevent unauthorized data access patterns. Regular security audits and penetration testing should verify that all API endpoints properly enforce authorization boundaries, particularly in multi-tenant environments where cross-tenant data access represents a significant risk. The vulnerability serves as a reminder of the critical importance of maintaining strict access controls even in seemingly simple database operations within multi-tenant applications.