Description: An attacker compromises the application's dependency injection (DI) configuration or deployment pipeline to inject malicious behaviors into the MediatR pipeline. These injected behaviors execute as part of the request processing flow within MediatR, allowing the attacker to intercept and manipulate requests and responses. A sophisticated attacker could use this to bypass authorization checks implemented in handlers, log or exfiltrate sensitive data processed by MediatR, modify request payloads before they reach handlers, or even inject malicious responses back to the client, all within the MediatR execution context. Impact: Critical. Full compromise of application logic flow within MediatR, potentially leading to complete data breaches, unauthorized access to all resources handled by MediatR, and manipulation of application behavior at a fundamental level. MediatR Component Affected: MediatR Pipeline, Pipeline Behaviors, Dependency Injection integration with MediatR. Risk Severity: Critical. Mitigation Strategies: * Strictly control and secure the application's build and deployment pipeline. Implement robust access controls and auditing for all changes to the deployment environment and application configuration. * Implement code signing and integrity checks for application binaries and configuration files. Verify the integrity of deployed components to prevent unauthorized modifications. * Regularly audit and monitor registered pipeline behaviors in production. Implement mechanisms to detect unexpected or unauthorized behaviors added to the MediatR pipeline. * Minimize dynamic behavior registration in production environments. Favor compile-time behavior registration where possible to reduce runtime configuration vulnerabilities. * Apply principle of least privilege to the processes and accounts managing application deployment and configuration. Limit access to only authorized personnel and systems.
Description: When exceptions occur during request processing within the MediatR pipeline (either in behaviors or handlers), and these exceptions are not properly handled by the application's global exception handling or within custom MediatR behaviors, sensitive information can be inadvertently leaked. MediatR's default behavior might propagate exception details up the call stack, potentially exposing internal server paths, database connection strings, or even snippets of data being processed at the time of the error in stack traces or error messages. If these unhandled exceptions are exposed in API responses or logs accessible to attackers, it provides valuable reconnaissance information. Impact: High. Information disclosure of sensitive application internals, potentially aiding attackers in identifying further vulnerabilities or gaining deeper understanding of the system's architecture and data flows. This leaked information can significantly lower the barrier to further, more impactful attacks. MediatR Component Affected: MediatR Pipeline's exception handling mechanism, error propagation within the pipeline, and integration with application-level exception handling. Risk Severity: High. Mitigation Strategies: * Implement robust global exception handling at the application level that sanitizes error messages before logging or exposing them. Ensure generic error responses are returned to clients in production, avoiding detailed exception information. * Configure MediatR pipeline to handle exceptions gracefully using custom behaviors. Implement exception handling behaviors that log errors appropriately (to secure logs, not exposed to users) and prevent sensitive details from propagating outwards. * Avoid relying on default exception handling behaviors in production. Explicitly define how exceptions within the MediatR pipeline are managed and logged. * Regularly review application logs for unexpected exceptions originating from the MediatR pipeline. Monitor for patterns that might indicate information leakage or potential attack attempts. * Perform penetration testing and security audits to identify potential information leakage points through error handling in the MediatR pipeline.