CVE-2026-51893 in ragflow
Summary
by MITRE • 10/02/2026
infiniflow ragflow 0.24.0 is vulnerable to Incorrect Access Control via trace_mindmap. An externally reachable path accepts a caller-selected object or tenant identifier and reaches a data-access operation without a visible owner, tenant, workspace, or membership binding on that object.
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Analysis
by VulDB Data Team • 10/02/2026
The vulnerability identified in InfiniFlow Ragflow version 0.24.0 represents a critical failure in access control mechanisms within the trace_mindmap functionality. This flaw allows an externally reachable endpoint to accept user-supplied identifiers for objects, tenants, or workspaces without performing adequate authorization checks. Specifically, when a request is made using these caller-selected parameters, the system proceeds with data-access operations that lack binding verification against visible owner, tenant, workspace, or membership contexts. This absence of proper validation means that authenticated users can potentially access resources belonging to other entities within the same deployment instance, violating the principle of least privilege and isolation between multi-tenant environments.
From a technical perspective, this issue stems from an insecure direct object reference pattern where the application relies on client-provided identifiers without cross-referencing them against session-based permissions or database-level ownership records. The trace_mindmap feature likely aggregates data for visualization purposes, but in doing so, it fails to enforce strict boundary checks before retrieving and returning sensitive information. This type of flaw is commonly associated with CWE-284 Improper Access Control and CWE-639 Authorization Bypass Through User-Controlled Key. Attackers can exploit this by manipulating the input parameters sent to the API endpoint, effectively bypassing logical access controls that should restrict data visibility based on user roles or organizational boundaries.
The operational impact of this vulnerability is significant for organizations utilizing Ragflow in multi-user or SaaS-like configurations where tenant isolation is paramount. Successful exploitation could lead to unauthorized disclosure of proprietary documents, internal knowledge bases, and sensitive analytical insights stored within the platform. Since mindmaps often contain structured representations of complex information systems, leaking these structures may reveal architectural details or strategic planning data that were intended for specific teams only. Furthermore, if combined with other vulnerabilities such as SQL injection or server-side request forgery, this access control flaw could serve as an initial foothold for deeper system compromise, although the primary risk here remains horizontal privilege escalation and data exfiltration across tenant boundaries.
To mitigate this vulnerability, immediate patching to a version of Ragflow that addresses this authorization logic is required. In the interim, administrators should implement strict input validation on all API endpoints related to trace_mindmap, ensuring that every request includes server-side verification of user permissions against the requested resource identifiers. Additionally, deploying web application firewalls with rules targeting improper access control patterns can provide a layer of defense by blocking requests that exhibit signs of parameter tampering or unauthorized key usage. Long-term remediation should involve adopting secure coding practices that enforce explicit authorization checks at every data-access point, aligning with industry standards such as OWASP API Security Top 10 and MITRE ATT&CK techniques related to privilege escalation and collection via internal spearphishing if the leaked data is used for further social engineering attacks.