Summary
RAGFlow contains an improper access control vulnerability in the evaluation application's get_dataset functionality. Depending on the exposed entry and deployment configuration, an attacker may be able to trigger attacker-controlled code or command execution.
RAGFlow contains an improper access control vulnerability in the evaluation application's get_dataset functionality. Depending on the exposed entry and deployment configuration, an attacker may be able to trigger attacker-controlled code or command execution.
Affected context
The issue occurs in RAGFlow's evaluation application, specifically around the get_dataset functionality. Risk depends on whether the relevant entry is exposed to an attacker and whether authorization checks sufficiently restrict access to dataset-related operations or execution paths.
The issue occurs in RAGFlow's evaluation application, specifically around the get_dataset functionality. Risk depends on whether the relevant entry is exposed to an attacker and whether authorization checks sufficiently restrict access to dataset-related operations or execution paths.
Exploit preconditions
- Attack surface: The evaluation application's get_dataset entry or a related exposed endpoint
- Required access: Access to the exposed interface; authentication requirements depend on deployment configuration
- Trigger point: A request that reaches the vulnerable dataset-handling path
- Why exploitation is possible: Insufficient authorization enforcement may allow an attacker-controlled operation to reach code or command execution behavior
- Attack surface: The evaluation application's get_dataset entry or a related exposed endpoint
- Required access: Access to the exposed interface; authentication requirements depend on deployment configuration
- Trigger point: A request that reaches the vulnerable dataset-handling path
- Why exploitation is possible: Insufficient authorization enforcement may allow an attacker-controlled operation to reach code or command execution behavior
Why this happens
The underlying issue is an authorization boundary failure in which access to a sensitive application function is not consistently restricted before attacker-controlled input reaches a consequential execution path. This maps to CWE-284, Improper Access Control, because the application may fail to enforce the intended permissions for a protected operation. The insecure pattern is treating endpoint reachability or partial validation as sufficient authorization.
The underlying issue is an authorization boundary failure in which access to a sensitive application function is not consistently restricted before attacker-controlled input reaches a consequential execution path. This maps to CWE-284, Improper Access Control, because the application may fail to enforce the intended permissions for a protected operation. The insecure pattern is treating endpoint reachability or partial validation as sufficient authorization.
Potential impact
- An attacker may execute arbitrary code within the affected application context.
- An attacker could execute operating-system commands with the privileges of the service.
- The vulnerability may enable unauthorized access to datasets or application resources.
- A compromised service could be used for lateral movement or data manipulation.
- An attacker may execute arbitrary code within the affected application context.
- An attacker could execute operating-system commands with the privileges of the service.
- The vulnerability may enable unauthorized access to datasets or application resources.
- A compromised service could be used for lateral movement or data manipulation.
General mitigation guidance
Mitigation generally focuses on enforcing authorization at the server-side function boundary and reducing the ability of request data to influence execution behavior. Common defensive patterns include requiring explicit authentication and narrowly scoped authorization for dataset operations, applying deny-by-default access policies, validating inputs against strict schemas, separating data handling from command execution, and avoiding dynamic evaluation of user-controlled values. Running the service with least privilege, isolating execution components, and limiting filesystem and network permissions can reduce impact if a control is bypassed.
Mitigation generally focuses on enforcing authorization at the server-side function boundary and reducing the ability of request data to influence execution behavior. Common defensive patterns include requiring explicit authentication and narrowly scoped authorization for dataset operations, applying deny-by-default access policies, validating inputs against strict schemas, separating data handling from command execution, and avoiding dynamic evaluation of user-controlled values. Running the service with least privilege, isolating execution components, and limiting filesystem and network permissions can reduce impact if a control is bypassed.
How teams detect issues like this
- Use static analysis and code review to identify sensitive handlers that lack centralized authorization checks.
- Search for get_dataset and related evaluation paths where request-controlled values reach subprocess, shell, interpreter, or dynamic execution APIs.
- Review route registration and middleware configuration for publicly reachable evaluation endpoints.
- Monitor access logs for unexpected calls, authorization failures, unusual dataset identifiers, and process creation by the application.
- Enforce policy checks in CI to require authorization annotations or centralized access-control middleware on sensitive routes.
- Neutral automated code-review tools may help identify missing access checks and dangerous data-to-execution flows.
- Use static analysis and code review to identify sensitive handlers that lack centralized authorization checks.
- Search for get_dataset and related evaluation paths where request-controlled values reach subprocess, shell, interpreter, or dynamic execution APIs.
- Review route registration and middleware configuration for publicly reachable evaluation endpoints.
- Monitor access logs for unexpected calls, authorization failures, unusual dataset identifiers, and process creation by the application.
- Enforce policy checks in CI to require authorization annotations or centralized access-control middleware on sensitive routes.
- Neutral automated code-review tools may help identify missing access checks and dangerous data-to-execution flows.
Sources
| Source | Link |
|---|---|
| gist. | gist.github.com/ |
